From 6b57265a6cc49af00242c0c690ee5496ad0c4562 Mon Sep 17 00:00:00 2001 From: Ethan <291938975@qq.com> Date: Wed, 27 Nov 2024 09:00:55 +1100 Subject: [PATCH 01/27] model create --- .idea/.gitignore | 8 + .idea/deployment.xml | 14 + .idea/encodings.xml | 7 + .../inspectionProfiles/profiles_settings.xml | 6 + .idea/misc.xml | 7 + .idea/modules.xml | 8 + .idea/project-Ethan.iml | 8 + .idea/vcs.xml | 6 + BNN_predictor.py | 250 + CNN_predictor.py | 252 + LSTM_predictor.py | 252 + MLP_predictor.py | 200 + README.md | 32 - RandomForests_ensemble.py | 245 + XGBoost_ensemble.py | 266 + agendas/README.md | 1 - checklists/README.md | 1 - config.py | 62 + data/totaldemand_nsw_hourly.csv | 98258 ++++++++++++++++ data_preprocessor.py | 234 + dataset.py | 69 + gantt_chart/README.md | 1 - main.py | 411 + minutes/README.md | 1 - prophet.md | 71 + prophet_predictor.py | 258 + report/README.md | 1 - .../GoogleColab-checkpoint.ipynb | 103 - src/GoogleColab.ipynb | 103 - src/README.md | 1 - time_series_predictor.py | 247 + utils.py | 140 + visualizer.py | 207 + 33 files changed, 101486 insertions(+), 244 deletions(-) create mode 100644 .idea/.gitignore create mode 100644 .idea/deployment.xml create mode 100644 .idea/encodings.xml create mode 100644 .idea/inspectionProfiles/profiles_settings.xml create mode 100644 .idea/misc.xml create mode 100644 .idea/modules.xml create mode 100644 .idea/project-Ethan.iml create mode 100644 .idea/vcs.xml create mode 100644 BNN_predictor.py create mode 100644 CNN_predictor.py create mode 100644 LSTM_predictor.py create mode 100644 MLP_predictor.py create mode 100644 RandomForests_ensemble.py create mode 100644 XGBoost_ensemble.py delete mode 100644 agendas/README.md delete mode 100644 checklists/README.md create mode 100644 config.py create mode 100644 data/totaldemand_nsw_hourly.csv create mode 100644 data_preprocessor.py create mode 100644 dataset.py delete mode 100644 gantt_chart/README.md create mode 100644 main.py delete mode 100644 minutes/README.md create mode 100644 prophet.md create mode 100644 prophet_predictor.py delete mode 100644 report/README.md delete mode 100644 src/.ipynb_checkpoints/GoogleColab-checkpoint.ipynb delete mode 100644 src/GoogleColab.ipynb delete mode 100644 src/README.md create mode 100644 time_series_predictor.py create mode 100644 utils.py create mode 100644 visualizer.py diff --git a/.idea/.gitignore b/.idea/.gitignore new file mode 100644 index 000000000..35410cacd --- /dev/null +++ b/.idea/.gitignore @@ -0,0 +1,8 @@ +# 默认忽略的文件 +/shelf/ +/workspace.xml +# 基于编辑器的 HTTP 客户端请求 +/httpRequests/ +# Datasource local storage ignored files +/dataSources/ +/dataSources.local.xml diff --git a/.idea/deployment.xml b/.idea/deployment.xml new file mode 100644 index 000000000..086641d2e --- /dev/null +++ b/.idea/deployment.xml @@ -0,0 +1,14 @@ + + + + + + + + + + + + + + \ No newline at end of file diff --git a/.idea/encodings.xml b/.idea/encodings.xml new file mode 100644 index 000000000..76bc0cb55 --- /dev/null +++ b/.idea/encodings.xml @@ -0,0 +1,7 @@ + + + + + + + \ No newline at end of file diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml new file mode 100644 index 000000000..105ce2da2 --- /dev/null +++ b/.idea/inspectionProfiles/profiles_settings.xml @@ -0,0 +1,6 @@ + + + + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml new file mode 100644 index 000000000..ea0e50d4b --- /dev/null +++ b/.idea/misc.xml @@ -0,0 +1,7 @@ + + + + + + \ No newline at end of file diff --git a/.idea/modules.xml b/.idea/modules.xml new file mode 100644 index 000000000..4bf57361e --- /dev/null +++ b/.idea/modules.xml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/project-Ethan.iml b/.idea/project-Ethan.iml new file mode 100644 index 000000000..d0876a78d --- /dev/null +++ b/.idea/project-Ethan.iml @@ -0,0 +1,8 @@ + + + + + + + + \ No newline at end of file diff --git a/.idea/vcs.xml b/.idea/vcs.xml new file mode 100644 index 000000000..35eb1ddfb --- /dev/null +++ b/.idea/vcs.xml @@ -0,0 +1,6 @@ + + + + + + \ No newline at end of file diff --git a/BNN_predictor.py b/BNN_predictor.py new file mode 100644 index 000000000..44e987022 --- /dev/null +++ b/BNN_predictor.py @@ -0,0 +1,250 @@ +import pandas as pd +import numpy as np +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from typing import Optional, Tuple +import logging +import os +from datetime import datetime +from tensorflow import keras +import tensorflow as tf +from keras.layers import Dense, Dropout, Lambda +from keras import backend as K + + +class BNNPredictor: + """ + 基于MC Dropout的贝叶斯神经网络时间序列预测器 + 主要用于预测电力负载，考虑预测的不确定性 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + # 初始化模型 + self.model = None + self.dropout_rate = 0.2 + self.num_monte_carlo = 100 + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + """ + try: + print("Starting data preprocessing for BNN...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 标准化数据 + features = ['hour_sin', 'hour_cos', 'temperature', 'load'] + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + sequence = scaled_data[i:(i + self.lookback_points)].flatten() + target = scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1] + + X.append(sequence) + y.append(target) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def _build_mc_dropout_model(self, input_shape: int): + """ + 构建带有MC Dropout的神经网络模型 + """ + model = keras.Sequential([ + Dense(128, input_shape=(input_shape,), activation='relu'), + Dropout(self.dropout_rate), + Dense(64, activation='relu'), + Dropout(self.dropout_rate), + Dense(32, activation='relu'), + Dropout(self.dropout_rate), + Dense(self.forecast_points, activation='linear') + ]) + + model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001), + loss='mse', + metrics=['mae']) + + return model + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Training MC Dropout Network with input shape: {X.shape}, output shape: {y.shape}") + + # 构建并训练模型 + if self.model is None: + self.model = self._build_mc_dropout_model(X.shape[1]) + print("Training MC Dropout model...") + history = self.model.fit(X, y, epochs=50, batch_size=32, validation_split=0.2, + verbose=0) + + # 只打印最终的损失值 + final_loss = history.history['loss'][-1] + final_val_loss = history.history['val_loss'][-1] + print(f"Training completed - Final loss: {final_loss:.4f}, Validation loss: {final_val_loss:.4f}") + + # 准备最后一个时间窗口用于预测 + last_window = scaled_data[-self.lookback_points:].flatten().reshape(1, -1) + + # 使用MC Dropout进行多次预测 + print("Generating predictions with MC Dropout sampling...") + predictions_list = [] + for _ in range(self.num_monte_carlo): + predictions_list.append(self.model(last_window, training=True)) + predictions_array = np.array(predictions_list) + + # 计算均值和标准差 + predictions_mean = np.mean(predictions_array, axis=0)[0] + predictions_std = np.std(predictions_array, axis=0)[0] + + # 反标准化预测结果 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + + # 处理均值 + dummy_features[:, -1] = predictions_mean + final_predictions_mean = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 处理置信区间 + dummy_features[:, -1] = predictions_mean + 2 * predictions_std + final_predictions_upper = self.scaler.inverse_transform(dummy_features)[:, -1] + + dummy_features[:, -1] = predictions_mean - 2 * predictions_std + final_predictions_lower = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions_mean, + 'prediction_lower': final_predictions_lower, + 'prediction_upper': final_predictions_upper + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(predictions_df) + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表，包括置信区间 + """ + plt.figure(figsize=(15, 6)) + + # 绘制历史数据 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据及置信区间 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='BNN Predicted Load', color='red', alpha=0.6) + plt.fill_between(predictions_df['timestamp'], + predictions_df['prediction_lower'], + predictions_df['prediction_upper'], + color='red', alpha=0.2, + label='95% Confidence Interval') + + plt.title(f'{self.forecast_hours}-hour BNN Load Forecast with Uncertainty') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'bnn_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"BNN prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions_df: pd.DataFrame) -> None: + """ + 打印预测结果的统计信息，包括不确定性估计 + """ + predictions = predictions_df['predicted_load'].values + uncertainty = (predictions_df['prediction_upper'].values - + predictions_df['prediction_lower'].values) / 2 + + print("\nBNN Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") + print(f"Average Uncertainty: ±{uncertainty.mean():.2f} MW") \ No newline at end of file diff --git a/CNN_predictor.py b/CNN_predictor.py new file mode 100644 index 000000000..2ce418108 --- /dev/null +++ b/CNN_predictor.py @@ -0,0 +1,252 @@ +import pandas as pd +import numpy as np +from tensorflow.keras.models import Sequential +from tensorflow.keras.layers import Conv1D, MaxPooling1D, Dense, Flatten, Dropout +from tensorflow.keras.optimizers import Adam +from tensorflow.keras.callbacks import EarlyStopping +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from typing import Optional, Tuple +import logging +from datetime import datetime +import os + + +class CNNPredictor: + """ + 基于Keras CNN的时间序列预测器 + 主要用于预测电力负载 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + # CNN模型参数 + self.filters = 64 + self.kernel_size = 3 + self.model = self._build_model() + + def _build_model(self) -> Sequential: + """ + 构建CNN模型 + """ + model = Sequential([ + # 第一个卷积层 + Conv1D(filters=self.filters, kernel_size=self.kernel_size, + activation='relu', input_shape=(self.lookback_points, 4)), + MaxPooling1D(pool_size=2), + + # 第二个卷积层 + Conv1D(filters=self.filters * 2, kernel_size=self.kernel_size, activation='relu'), + MaxPooling1D(pool_size=2), + + # 第三个卷积层 + Conv1D(filters=self.filters * 4, kernel_size=self.kernel_size, activation='relu'), + + # 展平层 + Flatten(), + + # 全连接层 + Dense(512, activation='relu'), + Dropout(0.3), + Dense(256, activation='relu'), + Dense(self.forecast_points, activation='linear') + ]) + + model.compile(optimizer=Adam(learning_rate=0.001), + loss='mse', + metrics=['mae']) + + return model + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + """ + try: + print("Starting data preprocessing...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour_sin'] = np.sin(2 * np.pi * df['timestamp'].dt.hour / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['timestamp'].dt.hour / 24) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 标准化数据 + features = ['hour_sin', 'hour_cos', 'temperature', 'load'] + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + # 使用所有特征作为输入 + sequence = scaled_data[i:(i + self.lookback_points)] + target = scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1] + + X.append(sequence) + y.append(target) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Training CNN with input shape: {X.shape}, output shape: {y.shape}") + + # 设置早停 + early_stopping = EarlyStopping( + monitor='val_loss', + patience=10, + restore_best_weights=True + ) + + # 训练模型 + print("Training CNN model...") + history = self.model.fit( + X, y, + epochs=100, + batch_size=32, + validation_split=0.2, + callbacks=[early_stopping], + verbose=0 + ) + print("Model training completed") + + # 准备最后一个时间窗口用于预测 + last_window = scaled_data[-self.lookback_points:].reshape(1, self.lookback_points, 4) + + # 生成预测 + print("Generating predictions...") + future_prediction = self.model.predict(last_window)[0] + + # 反标准化预测结果 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + dummy_features[:, -1] = future_prediction + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, history, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + history: object, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表和训练历史 + """ + # 创建一个包含两个子图的图表 + fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15, 12)) + + # 绘制预测结果 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + + ax1.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + ax1.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='CNN Predicted Load', color='red', alpha=0.6) + + ax1.set_title(f'{self.forecast_hours}-hour CNN Load Forecast') + ax1.set_xlabel('Time') + ax1.set_ylabel('Load (MW)') + ax1.legend() + ax1.grid(True) + ax1.tick_params(axis='x', rotation=45) + + # 绘制训练历史 + ax2.plot(history.history['loss'], label='Training Loss') + ax2.plot(history.history['val_loss'], label='Validation Loss') + ax2.set_title('Model Loss During Training') + ax2.set_xlabel('Epoch') + ax2.set_ylabel('Loss') + ax2.legend() + ax2.grid(True) + + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'cnn_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"CNN prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + """ + print("\nCNN Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") \ No newline at end of file diff --git a/LSTM_predictor.py b/LSTM_predictor.py new file mode 100644 index 000000000..efc8478dd --- /dev/null +++ b/LSTM_predictor.py @@ -0,0 +1,252 @@ +import pandas as pd +import numpy as np +from tensorflow.keras.models import Sequential +from tensorflow.keras.layers import LSTM, Dense, Dropout +from tensorflow.keras.optimizers import Adam +from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from typing import Optional, Tuple +import logging +from datetime import datetime +import os + + +class LSTMPredictor: + """ + 基于Keras LSTM的时间序列预测器 + 主要用于预测电力负载 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + self.model = None + + def _build_model(self, input_shape: Tuple[int, int]) -> None: + """ + 构建LSTM模型 + + 参数: + input_shape: Tuple[int, int] - 输入数据的形状 (时间步长, 特征数) + """ + self.model = Sequential([ + LSTM(units=64, activation='relu', return_sequences=True, + input_shape=input_shape), + Dropout(0.2), + LSTM(units=32, activation='relu'), + Dropout(0.2), + Dense(units=self.forecast_points) + ]) + + self.model.compile( + optimizer=Adam(learning_rate=0.001), + loss='mse', + metrics=['mae'] + ) + + print("LSTM model structure:") + self.model.summary() + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + """ + try: + print("Starting data preprocessing...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 标准化数据 + features = ['hour_sin', 'hour_cos', 'temperature', 'load'] + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + # 保持时间步维度 + sequence = scaled_data[i:(i + self.lookback_points)] + target = scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1] + + X.append(sequence) + y.append(target) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Training LSTM with input shape: {X.shape}, output shape: {y.shape}") + + # 构建模型 + if self.model is None: + self._build_model(input_shape=(X.shape[1], X.shape[2])) + + # 设置回调函数 + callbacks = [ + EarlyStopping( + monitor='val_loss', + patience=10, + restore_best_weights=True + ), + ReduceLROnPlateau( + monitor='val_loss', + factor=0.5, + patience=5, + min_lr=1e-6 + ) + ] + + # 训练模型 + print("Training LSTM model...") + history = self.model.fit( + X, y, + epochs=100, + batch_size=32, + validation_split=0.2, + callbacks=callbacks, + verbose=0 + ) + + # 准备最后一个时间窗口用于预测 + last_window = scaled_data[-self.lookback_points:].reshape(1, self.lookback_points, -1) + + # 生成预测 + print("Generating predictions...") + future_prediction = self.model.predict(last_window)[0] + + # 反标准化预测结果 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + dummy_features[:, -1] = future_prediction + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, history, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + history: any, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表和训练历史 + """ + # 创建一个2x1的子图布局 + fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(15, 12)) + + # 绘制预测结果 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + + ax1.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + ax1.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='LSTM Predicted Load', color='red', alpha=0.6) + ax1.set_title(f'{self.forecast_hours}-hour LSTM Load Forecast') + ax1.set_xlabel('Time') + ax1.set_ylabel('Load (MW)') + ax1.legend() + ax1.grid(True) + plt.setp(ax1.get_xticklabels(), rotation=45) + + # 绘制训练历史 + ax2.plot(history.history['loss'], label='Training Loss') + ax2.plot(history.history['val_loss'], label='Validation Loss') + ax2.set_title('Model Training History') + ax2.set_xlabel('Epoch') + ax2.set_ylabel('Loss') + ax2.legend() + ax2.grid(True) + + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'lstm_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"LSTM prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + """ + print("\nLSTM Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") \ No newline at end of file diff --git a/MLP_predictor.py b/MLP_predictor.py new file mode 100644 index 000000000..90b964537 --- /dev/null +++ b/MLP_predictor.py @@ -0,0 +1,200 @@ +import pandas as pd +import numpy as np +from sklearn.neural_network import MLPRegressor +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from typing import Optional, Tuple +import logging +from datetime import datetime +import os + + +class MLPPredictor: + """ + 基于sklearn MLPRegressor的时间序列预测器 + 主要用于预测电力负载 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + # 初始化MLPRegressor + self.model = MLPRegressor( + hidden_layer_sizes=(12, 6), # 两个隐藏层 + activation='relu', # ReLU激活函数 + solver='adam', # Adam优化器 + max_iter=500, # 最大迭代次数 + random_state=1, # 随机种子 + early_stopping=True, # 启用早停 + validation_fraction=0.1, # 验证集比例 + verbose=True # 显示训练进度 + ) + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + """ + try: + print("Starting data preprocessing...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 标准化数据 + features = ['hour_sin', 'hour_cos', 'temperature', 'load'] + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + # 将所有特征展平作为输入 + sequence = scaled_data[i:(i + self.lookback_points)].flatten() + target = scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1] + + X.append(sequence) + y.append(target) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Training MLP with input shape: {X.shape}, output shape: {y.shape}") + + # 训练模型 + print("Training MLP model...") + self.model.fit(X, y) + print("Model training completed") + + # 准备最后一个时间窗口用于预测 + last_window = scaled_data[-self.lookback_points:].flatten().reshape(1, -1) + + # 生成预测 + print("Generating predictions...") + future_prediction = self.model.predict(last_window)[0] + + # 反标准化预测结果 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + dummy_features[:, -1] = future_prediction + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表 + """ + plt.figure(figsize=(15, 6)) + + # 绘制历史数据 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='MLP Predicted Load', color='red', alpha=0.6) + + plt.title(f'{self.forecast_hours}-hour MLP Load Forecast') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'mlp_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"MLP prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + """ + print("\nMLP Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") \ No newline at end of file diff --git a/README.md b/README.md index a711aa635..e69de29bb 100644 --- a/README.md +++ b/README.md @@ -1,32 +0,0 @@ -# Welcome to ZZSC9020 GitHub repository for group [GROUP-NAME] - -This GitHub repository is the main point of access for students and lecturers of the ZZSC9020 capstone course. - -In this repository, you will find the data to start developing your project. Also, we will use the repository to share code, documentation, data, models and other resources between the group members and course lecturers. - -Complete the information below regarding your group. - -## Group and project information - -### Group members and zIDs -- Member 1 (zID1) - Group leader -- Member 2 (zID2) - role -- Member 3 (zID3) - role -- Member 4 (zID4) - role -- Member 5 (zID5) - role - -### Brief project description - -Describe your project in one paragraph. - -## Repository structure - -The repository has the following folder structure: - -- agendas: agendas for each weekly meeting with lecturers (left 24h before the next meeting) -- checklists: teamwork checklist or a link to an account in a project task management tool -- data: datasets for analysis -- gantt_chart: Gantt chart or a link to an account in a project task management tool -- minutes: minutes for each meeting (left not more than 24h after the corresponding meeting) -- report: RMarkdown or Jupyter notebook report in progress -- src: source code diff --git a/RandomForests_ensemble.py b/RandomForests_ensemble.py new file mode 100644 index 000000000..d0ecd9403 --- /dev/null +++ b/RandomForests_ensemble.py @@ -0,0 +1,245 @@ +import pandas as pd +import numpy as np +from sklearn.ensemble import RandomForestRegressor +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from typing import Optional, Dict, List, Tuple +import logging +from datetime import datetime +import os + + +class RandomForestsPredictor: + """ + 基于sklearn RandomForest的时间序列预测器 + 主要用于预测电力负载，支持温度作为额外的回归变量 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + # 初始化RandomForest模型 + self.model = RandomForestRegressor( + n_estimators=100, # 树的数量 + max_depth=None, # 树的最大深度，None表示不限制 + min_samples_split=2, + min_samples_leaf=1, + random_state=42, + n_jobs=-1, # 使用所有可用的CPU核心 + verbose=1 + ) + + # 存储最佳参数 + self.best_params = None + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + + 参数: + df: DataFrame - 包含 'timestamp', 'temperature', 'load' 列的数据框 + + 返回: + Tuple[pd.DataFrame, np.ndarray] - 处理后的数据框和标准化后的特征数据 + """ + try: + print("Starting data preprocessing...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['day'] = df['timestamp'].dt.day + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + df['dayofweek_sin'] = np.sin(2 * np.pi * df['dayofweek'] / 7) + df['dayofweek_cos'] = np.cos(2 * np.pi * df['dayofweek'] / 7) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 创建滚动特征 + df['load_lag_24h'] = df['load'].shift(48) # 24小时滞后 + df['load_lag_1w'] = df['load'].shift(336) # 一周滞后 + df['temp_lag_24h'] = df['temperature'].shift(48) # 24小时温度滞后 + + # 创建移动平均特征 + df['load_ma_24h'] = df['load'].rolling(window=48).mean() + df['temp_ma_24h'] = df['temperature'].rolling(window=48).mean() + + # 填充缺失值 + df = df.fillna(method='bfill') + + # 标准化特征 + features = ['hour_sin', 'hour_cos', 'dayofweek_sin', 'dayofweek_cos', + 'temperature', 'temp_lag_24h', 'temp_ma_24h', + 'load', 'load_lag_24h', 'load_lag_1w', 'load_ma_24h'] + + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + # 将所有特征展平作为输入 + sequence = scaled_data[i:(i + self.lookback_points)].flatten() + target = scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1] + + X.append(sequence) + y.append(target) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + + 参数: + df: DataFrame - 输入数据 + save_dir: Optional[str] - 保存预测结果的目录 + + 返回: + Optional[pd.DataFrame] - 预测结果数据框 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Training Random Forest with input shape: {X.shape}, output shape: {y.shape}") + + # 训练模型 + print("Training Random Forest model...") + self.model.fit(X, y) + print("Model training completed") + + # 准备最后一个时间窗口用于预测 + last_window = scaled_data[-self.lookback_points:].flatten().reshape(1, -1) + + # 生成预测 + print("Generating predictions...") + future_prediction = self.model.predict(last_window)[0] + + # 反标准化预测结果 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + dummy_features[:, -1] = future_prediction + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + # 输出特征重要性 + self._print_feature_importance() + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表 + """ + plt.figure(figsize=(15, 6)) + + # 绘制历史数据 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='Random Forest Predicted Load', color='red', alpha=0.6) + + plt.title(f'{self.forecast_hours}-hour Random Forest Load Forecast') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'random_forest_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"Random Forest prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + """ + print("\nRandom Forest Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") + + def _print_feature_importance(self) -> None: + """ + 打印特征重要性信息 + """ + feature_importance = self.model.feature_importances_ + print("\nFeature Importance:") + for importance in feature_importance: + print(f"Feature importance: {importance:.4f}") \ No newline at end of file diff --git a/XGBoost_ensemble.py b/XGBoost_ensemble.py new file mode 100644 index 000000000..d1a710894 --- /dev/null +++ b/XGBoost_ensemble.py @@ -0,0 +1,266 @@ +import pandas as pd +import numpy as np +from xgboost import XGBRegressor +from sklearn.preprocessing import MinMaxScaler +from sklearn.model_selection import TimeSeriesSplit +from sklearn.metrics import mean_squared_error, mean_absolute_error +import matplotlib.pyplot as plt +from typing import Optional, Tuple, List +import logging +from datetime import datetime +import os + + +class XGBoostEnsemblePredictor: + """ + 基于XGBoost的集成预测器 + 使用多个XGBoost模型进行不同时间尺度的预测 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T', n_estimators: int = 100): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + n_estimators: int - XGBoost模型中的树的数量 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + # 初始化XGBoost模型参数 + self.model_params = { + 'n_estimators': n_estimators, + 'learning_rate': 0.1, + 'max_depth': 6, + 'min_child_weight': 1, + 'subsample': 0.8, + 'colsample_bytree': 0.8, + 'random_state': 42, + 'n_jobs': -1 # 使用所有可用的CPU核心 + } + + # 创建多个预测模型用于不同的预测时间段 + self.models = [XGBRegressor(**self.model_params) for _ in range(3)] + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + """ + try: + print("Starting data preprocessing...") + + # 准备基础数据 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['day'] = df['timestamp'].dt.day + df['week'] = df['timestamp'].dt.isocalendar().week + + # 添加周期性特征 + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + df['day_sin'] = np.sin(2 * np.pi * df['dayofweek'] / 7) + df['day_cos'] = np.cos(2 * np.pi * df['dayofweek'] / 7) + + # 添加滞后特征 + df['load_lag_1h'] = df['load'].shift(2) # 1小时前 + df['load_lag_24h'] = df['load'].shift(48) # 24小时前 + df['load_lag_7d'] = df['load'].shift(336) # 7天前 + + # 添加滑动窗口特征 + df['load_rolling_mean_6h'] = df['load'].rolling(window=12).mean() + df['load_rolling_std_6h'] = df['load'].rolling(window=12).std() + df['temp_rolling_mean_6h'] = df['temperature'].rolling(window=12).mean() + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean() + # 使用前向填充和后向填充替代插值 + df = df.fillna(method='ffill').fillna(method='bfill') + df.reset_index(inplace=True) + + # 处理缺失值 + df = df.fillna(method='bfill') + + # 选择特征 + features = ['hour_sin', 'hour_cos', 'day_sin', 'day_cos', + 'temperature', 'temp_rolling_mean_6h', + 'load_lag_1h', 'load_lag_24h', 'load_lag_7d', + 'load_rolling_mean_6h', 'load_rolling_std_6h'] + + # 标准化数据 + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + """ + try: + X, y = [], [] + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + X.append(scaled_data[i:(i + self.lookback_points)]) + y.append(scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1]) + + return np.array(X), np.array(y) + + except Exception as e: + logging.error(f"Error in sequence creation: {str(e)}") + raise + + def _train_ensemble(self, X: np.ndarray, y: np.ndarray) -> None: + """ + 训练集成模型 + """ + try: + print("Training XGBoost ensemble models...") + + # 将预测时间段分为三段，每个模型负责一段 + segment_length = self.forecast_points // 3 + + for i, model in enumerate(self.models): + start_idx = i * segment_length + end_idx = (i + 1) * segment_length if i < 2 else self.forecast_points + + # 为每个模型准备训练数据 + X_flat = X.reshape(X.shape[0], -1) # 展平特征 + y_segment = y[:, start_idx:end_idx] + + # 使用时间序列交叉验证 + tscv = TimeSeriesSplit(n_splits=5) + for train_idx, val_idx in tscv.split(X_flat): + model.fit( + X_flat[train_idx], + y_segment[train_idx], + verbose=0 + ) + + print(f"Model {i + 1} training completed") + + except Exception as e: + logging.error(f"Error in ensemble training: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + print(f"Created sequences with shape: X={X.shape}, y={y.shape}") + + # 训练模型 + self._train_ensemble(X, y) + + # 准备预测数据 + last_window = scaled_data[-self.lookback_points:].reshape(1, -1) + + # 生成预测 + print("Generating predictions...") + predictions = [] + segment_length = self.forecast_points // 3 + + for i, model in enumerate(self.models): + start_idx = i * segment_length + end_idx = (i + 1) * segment_length if i < 2 else self.forecast_points + segment_pred = model.predict(last_window) + predictions.extend(segment_pred[0]) + + # 反标准化预测结果 + dummy_features = np.zeros((len(predictions), scaled_data.shape[1])) + dummy_features[:, -1] = predictions + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + return predictions_df + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表 + """ + plt.figure(figsize=(15, 6)) + + # 绘制历史数据 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='XGBoost Predicted Load', color='red', alpha=0.6) + + plt.title(f'{self.forecast_hours}-hour XGBoost Ensemble Load Forecast') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'xgboost_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"XGBoost prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + """ + print("\nXGBoost Ensemble Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") \ No newline at end of file diff --git a/agendas/README.md b/agendas/README.md deleted file mode 100644 index df122a30b..000000000 --- a/agendas/README.md +++ /dev/null @@ -1 +0,0 @@ -agendas: agendas for each weekly meeting with lecturers (left 24h before the next meeting) diff --git a/checklists/README.md b/checklists/README.md deleted file mode 100644 index 82819b296..000000000 --- a/checklists/README.md +++ /dev/null @@ -1 +0,0 @@ -checklists: teamwork checklist or a link to an account in a project task management tool diff --git a/config.py b/config.py new file mode 100644 index 000000000..c5be59c7d --- /dev/null +++ b/config.py @@ -0,0 +1,62 @@ +import os + + +class Config: + # 项目根目录 + ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) + + # 数据相关配置 + DATA_PATH = { + 'TEMPERATURE': os.path.join(ROOT_DIR, 'data', 'NSW', 'temperature_nsw.csv'), + 'DEMAND': os.path.join(ROOT_DIR, 'data', 'NSW', 'totaldemand_nsw.csv') + } + + # 时间窗口配置 + WINDOW_SIZE = 1440 # 24小时 * 60分钟 + FORECAST_HORIZON = 2880 # 48小时 * 60分钟 + TRAIN_TEST_SPLIT = 0.8 + + # 模型相关配置 + MODEL = { + 'type': 'transformer', # 可选: 'lstm', 'transformer', 'tcn' + 'hidden_size': 128, + 'num_layers': 4, + 'dropout': 0.1, + 'num_heads': 8, # 用于transformer + 'forward_expansion': 4 # 用于transformer的FFN + } + + # 训练相关配置 + TRAINING = { + 'batch_size': 32, + 'epochs': 100, + 'learning_rate': 0.001, + 'early_stopping_patience': 10, + 'scheduler_patience': 5, + 'scheduler_factor': 0.5 + } + + # 评估指标配置 + METRICS = ['mae', 'mse', 'rmse', 'mape'] + + # 系统配置 + RANDOM_SEED = 42 + DEVICE = 'cuda' # 或 'cpu' + NUM_WORKERS = 4 + + # 文件保存路径 + SAVE_PATH = { + 'models': os.path.join(ROOT_DIR, 'saved_models'), + 'logs': os.path.join(ROOT_DIR, 'logs'), + 'predictions': os.path.join(ROOT_DIR, 'predictions'), + 'figures': os.path.join(ROOT_DIR, 'figures') + } + + def __init__(self): + """初始化时创建必要的目录""" + for path in self.SAVE_PATH.values(): + os.makedirs(path, exist_ok=True) + + # 确保数据目录存在 + os.makedirs(os.path.dirname(self.DATA_PATH['TEMPERATURE']), exist_ok=True) + os.makedirs(os.path.dirname(self.DATA_PATH['DEMAND']), exist_ok=True) \ No newline at end of file diff --git a/data/totaldemand_nsw_hourly.csv b/data/totaldemand_nsw_hourly.csv new file mode 100644 index 000000000..8d736d034 --- /dev/null +++ b/data/totaldemand_nsw_hourly.csv @@ -0,0 +1,98258 @@ +,DATETIME,TOTALDEMAND,REGIONID +0,2010-01-01 00:00:00,15847.310000000001,NSW1NSW1 +1,2010-01-01 01:00:00,14600.919999999998,NSW1NSW1 +2,2010-01-01 02:00:00,13356.36,NSW1NSW1 +3,2010-01-01 03:00:00,12660.17,NSW1NSW1 +4,2010-01-01 04:00:00,12459.8,NSW1NSW1 +5,2010-01-01 05:00:00,12435.96,NSW1NSW1 +6,2010-01-01 06:00:00,12876.9,NSW1NSW1 +7,2010-01-01 07:00:00,13719.16,NSW1NSW1 +8,2010-01-01 08:00:00,14728.93,NSW1NSW1 +9,2010-01-01 09:00:00,15677.0,NSW1NSW1 +10,2010-01-01 10:00:00,16190.470000000001,NSW1NSW1 +11,2010-01-01 11:00:00,16416.870000000003,NSW1NSW1 +12,2010-01-01 12:00:00,16639.67,NSW1NSW1 +13,2010-01-01 13:00:00,16759.0,NSW1NSW1 +14,2010-01-01 14:00:00,16978.73,NSW1NSW1 +15,2010-01-01 15:00:00,17161.050000000003,NSW1NSW1 +16,2010-01-01 16:00:00,17507.300000000003,NSW1NSW1 +17,2010-01-01 17:00:00,17719.9,NSW1NSW1 +18,2010-01-01 18:00:00,17406.019999999997,NSW1NSW1 +19,2010-01-01 19:00:00,17106.67,NSW1NSW1 +20,2010-01-01 20:00:00,17208.83,NSW1NSW1 +21,2010-01-01 21:00:00,16677.34,NSW1NSW1 +22,2010-01-01 22:00:00,16506.13,NSW1NSW1 +23,2010-01-01 23:00:00,15824.45,NSW1NSW1 +24,2010-01-02 00:00:00,14918.150000000001,NSW1NSW1 +25,2010-01-02 01:00:00,13879.529999999999,NSW1NSW1 +26,2010-01-02 02:00:00,12845.16,NSW1NSW1 +27,2010-01-02 03:00:00,12405.71,NSW1NSW1 +28,2010-01-02 04:00:00,12365.3,NSW1NSW1 +29,2010-01-02 05:00:00,12596.2,NSW1NSW1 +30,2010-01-02 06:00:00,13150.49,NSW1NSW1 +31,2010-01-02 07:00:00,14427.32,NSW1NSW1 +32,2010-01-02 08:00:00,16007.66,NSW1NSW1 +33,2010-01-02 09:00:00,16916.83,NSW1NSW1 +34,2010-01-02 10:00:00,17622.589999999997,NSW1NSW1 +35,2010-01-02 11:00:00,18108.61,NSW1NSW1 +36,2010-01-02 12:00:00,17969.36,NSW1NSW1 +37,2010-01-02 13:00:00,17616.16,NSW1NSW1 +38,2010-01-02 14:00:00,17837.43,NSW1NSW1 +39,2010-01-02 15:00:00,18164.85,NSW1NSW1 +40,2010-01-02 16:00:00,18576.87,NSW1NSW1 +41,2010-01-02 17:00:00,18399.89,NSW1NSW1 +42,2010-01-02 18:00:00,17969.09,NSW1NSW1 +43,2010-01-02 19:00:00,17343.89,NSW1NSW1 +44,2010-01-02 20:00:00,17352.03,NSW1NSW1 +45,2010-01-02 21:00:00,16816.21,NSW1NSW1 +46,2010-01-02 22:00:00,16279.939999999999,NSW1NSW1 +47,2010-01-02 23:00:00,15268.8,NSW1NSW1 +48,2010-01-03 00:00:00,14338.03,NSW1NSW1 +49,2010-01-03 01:00:00,13357.54,NSW1NSW1 +50,2010-01-03 02:00:00,12541.24,NSW1NSW1 +51,2010-01-03 03:00:00,12166.09,NSW1NSW1 +52,2010-01-03 04:00:00,12161.21,NSW1NSW1 +53,2010-01-03 05:00:00,12285.05,NSW1NSW1 +54,2010-01-03 06:00:00,12776.84,NSW1NSW1 +55,2010-01-03 07:00:00,13808.619999999999,NSW1NSW1 +56,2010-01-03 08:00:00,15026.619999999999,NSW1NSW1 +57,2010-01-03 09:00:00,15953.66,NSW1NSW1 +58,2010-01-03 10:00:00,16389.95,NSW1NSW1 +59,2010-01-03 11:00:00,16457.72,NSW1NSW1 +60,2010-01-03 12:00:00,16358.79,NSW1NSW1 +61,2010-01-03 13:00:00,16092.06,NSW1NSW1 +62,2010-01-03 14:00:00,15913.39,NSW1NSW1 +63,2010-01-03 15:00:00,15878.970000000001,NSW1NSW1 +64,2010-01-03 16:00:00,15769.15,NSW1NSW1 +65,2010-01-03 17:00:00,15922.18,NSW1NSW1 +66,2010-01-03 18:00:00,15877.61,NSW1NSW1 +67,2010-01-03 19:00:00,15811.92,NSW1NSW1 +68,2010-01-03 20:00:00,15828.01,NSW1NSW1 +69,2010-01-03 21:00:00,15238.58,NSW1NSW1 +70,2010-01-03 22:00:00,14973.66,NSW1NSW1 +71,2010-01-03 23:00:00,14268.29,NSW1NSW1 +72,2010-01-04 00:00:00,13731.0,NSW1NSW1 +73,2010-01-04 01:00:00,13057.44,NSW1NSW1 +74,2010-01-04 02:00:00,12325.49,NSW1NSW1 +75,2010-01-04 03:00:00,12150.58,NSW1NSW1 +76,2010-01-04 04:00:00,12471.470000000001,NSW1NSW1 +77,2010-01-04 05:00:00,13377.380000000001,NSW1NSW1 +78,2010-01-04 06:00:00,14903.6,NSW1NSW1 +79,2010-01-04 07:00:00,16401.15,NSW1NSW1 +80,2010-01-04 08:00:00,17707.120000000003,NSW1NSW1 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02:00:00,13170.380000000001,NSW1NSW1 +147,2010-01-07 03:00:00,12868.29,NSW1NSW1 +148,2010-01-07 04:00:00,13115.35,NSW1NSW1 +149,2010-01-07 05:00:00,14049.43,NSW1NSW1 +150,2010-01-07 06:00:00,15541.130000000001,NSW1NSW1 +151,2010-01-07 07:00:00,17181.18,NSW1NSW1 +152,2010-01-07 08:00:00,18397.17,NSW1NSW1 +153,2010-01-07 09:00:00,19063.58,NSW1NSW1 +154,2010-01-07 10:00:00,19319.79,NSW1NSW1 +155,2010-01-07 11:00:00,19556.65,NSW1NSW1 +156,2010-01-07 12:00:00,19699.010000000002,NSW1NSW1 +157,2010-01-07 13:00:00,19559.03,NSW1NSW1 +158,2010-01-07 14:00:00,19417.85,NSW1NSW1 +159,2010-01-07 15:00:00,19456.9,NSW1NSW1 +160,2010-01-07 16:00:00,19292.69,NSW1NSW1 +161,2010-01-07 17:00:00,18833.65,NSW1NSW1 +162,2010-01-07 18:00:00,18222.379999999997,NSW1NSW1 +163,2010-01-07 19:00:00,17932.82,NSW1NSW1 +164,2010-01-07 20:00:00,17757.480000000003,NSW1NSW1 +165,2010-01-07 21:00:00,16969.84,NSW1NSW1 +166,2010-01-07 22:00:00,16565.6,NSW1NSW1 +167,2010-01-07 23:00:00,15972.68,NSW1NSW1 +168,2010-01-08 00:00:00,15186.89,NSW1NSW1 +169,2010-01-08 01:00:00,14214.76,NSW1NSW1 +170,2010-01-08 02:00:00,13231.93,NSW1NSW1 +171,2010-01-08 03:00:00,12921.74,NSW1NSW1 +172,2010-01-08 04:00:00,13213.26,NSW1NSW1 +173,2010-01-08 05:00:00,14131.07,NSW1NSW1 +174,2010-01-08 06:00:00,15545.2,NSW1NSW1 +175,2010-01-08 07:00:00,17331.4,NSW1NSW1 +176,2010-01-08 08:00:00,18662.08,NSW1NSW1 +177,2010-01-08 09:00:00,19428.11,NSW1NSW1 +178,2010-01-08 10:00:00,19803.18,NSW1NSW1 +179,2010-01-08 11:00:00,20007.6,NSW1NSW1 +180,2010-01-08 12:00:00,20316.7,NSW1NSW1 +181,2010-01-08 13:00:00,20621.92,NSW1NSW1 +182,2010-01-08 14:00:00,20868.75,NSW1NSW1 +183,2010-01-08 15:00:00,21136.510000000002,NSW1NSW1 +184,2010-01-08 16:00:00,21275.21,NSW1NSW1 +185,2010-01-08 17:00:00,20539.21,NSW1NSW1 +186,2010-01-08 18:00:00,19569.620000000003,NSW1NSW1 +187,2010-01-08 19:00:00,18902.73,NSW1NSW1 +188,2010-01-08 20:00:00,18786.72,NSW1NSW1 +189,2010-01-08 21:00:00,18162.17,NSW1NSW1 +190,2010-01-08 22:00:00,17717.379999999997,NSW1NSW1 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20:00:00,21074.739999999998,NSW1NSW1 +213,2010-01-09 21:00:00,20173.3,NSW1NSW1 +214,2010-01-09 22:00:00,19133.12,NSW1NSW1 +215,2010-01-09 23:00:00,17616.41,NSW1NSW1 +216,2010-01-10 00:00:00,16136.6,NSW1NSW1 +217,2010-01-10 01:00:00,14894.68,NSW1NSW1 +218,2010-01-10 02:00:00,13914.72,NSW1NSW1 +219,2010-01-10 03:00:00,13616.61,NSW1NSW1 +220,2010-01-10 04:00:00,13470.330000000002,NSW1NSW1 +221,2010-01-10 05:00:00,13572.810000000001,NSW1NSW1 +222,2010-01-10 06:00:00,14104.82,NSW1NSW1 +223,2010-01-10 07:00:00,15649.09,NSW1NSW1 +224,2010-01-10 08:00:00,17686.85,NSW1NSW1 +225,2010-01-10 09:00:00,19547.43,NSW1NSW1 +226,2010-01-10 10:00:00,20795.510000000002,NSW1NSW1 +227,2010-01-10 11:00:00,21544.66,NSW1NSW1 +228,2010-01-10 12:00:00,21816.199999999997,NSW1NSW1 +229,2010-01-10 13:00:00,21870.489999999998,NSW1NSW1 +230,2010-01-10 14:00:00,21918.010000000002,NSW1NSW1 +231,2010-01-10 15:00:00,21923.29,NSW1NSW1 +232,2010-01-10 16:00:00,21750.949999999997,NSW1NSW1 +233,2010-01-10 17:00:00,21346.239999999998,NSW1NSW1 +234,2010-01-10 18:00:00,20684.21,NSW1NSW1 +235,2010-01-10 19:00:00,19670.17,NSW1NSW1 +236,2010-01-10 20:00:00,19299.7,NSW1NSW1 +237,2010-01-10 21:00:00,18250.48,NSW1NSW1 +238,2010-01-10 22:00:00,17274.69,NSW1NSW1 +239,2010-01-10 23:00:00,16111.41,NSW1NSW1 +240,2010-01-11 00:00:00,15103.380000000001,NSW1NSW1 +241,2010-01-11 01:00:00,14258.61,NSW1NSW1 +242,2010-01-11 02:00:00,13472.55,NSW1NSW1 +243,2010-01-11 03:00:00,13259.59,NSW1NSW1 +244,2010-01-11 04:00:00,13581.34,NSW1NSW1 +245,2010-01-11 05:00:00,14775.04,NSW1NSW1 +246,2010-01-11 06:00:00,16703.14,NSW1NSW1 +247,2010-01-11 07:00:00,18786.58,NSW1NSW1 +248,2010-01-11 08:00:00,20359.21,NSW1NSW1 +249,2010-01-11 09:00:00,21220.83,NSW1NSW1 +250,2010-01-11 10:00:00,21624.120000000003,NSW1NSW1 +251,2010-01-11 11:00:00,21982.15,NSW1NSW1 +252,2010-01-11 12:00:00,22181.27,NSW1NSW1 +253,2010-01-11 13:00:00,22554.34,NSW1NSW1 +254,2010-01-11 14:00:00,22879.9,NSW1NSW1 +255,2010-01-11 15:00:00,23156.72,NSW1NSW1 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14:00:00,26688.2,NSW1NSW1 +279,2010-01-12 15:00:00,27122.75,NSW1NSW1 +280,2010-01-12 16:00:00,27337.489999999998,NSW1NSW1 +281,2010-01-12 17:00:00,26539.230000000003,NSW1NSW1 +282,2010-01-12 18:00:00,25235.23,NSW1NSW1 +283,2010-01-12 19:00:00,24350.67,NSW1NSW1 +284,2010-01-12 20:00:00,23943.82,NSW1NSW1 +285,2010-01-12 21:00:00,22546.33,NSW1NSW1 +286,2010-01-12 22:00:00,20723.769999999997,NSW1NSW1 +287,2010-01-12 23:00:00,19062.57,NSW1NSW1 +288,2010-01-13 00:00:00,17566.75,NSW1NSW1 +289,2010-01-13 01:00:00,16352.26,NSW1NSW1 +290,2010-01-13 02:00:00,15297.92,NSW1NSW1 +291,2010-01-13 03:00:00,14825.17,NSW1NSW1 +292,2010-01-13 04:00:00,14962.48,NSW1NSW1 +293,2010-01-13 05:00:00,15707.36,NSW1NSW1 +294,2010-01-13 06:00:00,17600.34,NSW1NSW1 +295,2010-01-13 07:00:00,20094.989999999998,NSW1NSW1 +296,2010-01-13 08:00:00,21920.88,NSW1NSW1 +297,2010-01-13 09:00:00,23114.3,NSW1NSW1 +298,2010-01-13 10:00:00,23711.53,NSW1NSW1 +299,2010-01-13 11:00:00,24219.07,NSW1NSW1 +300,2010-01-13 12:00:00,24376.739999999998,NSW1NSW1 +301,2010-01-13 13:00:00,24203.84,NSW1NSW1 +302,2010-01-13 14:00:00,23693.08,NSW1NSW1 +303,2010-01-13 15:00:00,23208.41,NSW1NSW1 +304,2010-01-13 16:00:00,22250.82,NSW1NSW1 +305,2010-01-13 17:00:00,20703.89,NSW1NSW1 +306,2010-01-13 18:00:00,19224.309999999998,NSW1NSW1 +307,2010-01-13 19:00:00,18329.78,NSW1NSW1 +308,2010-01-13 20:00:00,17900.34,NSW1NSW1 +309,2010-01-13 21:00:00,17191.35,NSW1NSW1 +310,2010-01-13 22:00:00,16641.52,NSW1NSW1 +311,2010-01-13 23:00:00,15938.23,NSW1NSW1 +312,2010-01-14 00:00:00,15184.64,NSW1NSW1 +313,2010-01-14 01:00:00,14113.380000000001,NSW1NSW1 +314,2010-01-14 02:00:00,13250.17,NSW1NSW1 +315,2010-01-14 03:00:00,13009.04,NSW1NSW1 +316,2010-01-14 04:00:00,13287.32,NSW1NSW1 +317,2010-01-14 05:00:00,14418.23,NSW1NSW1 +318,2010-01-14 06:00:00,16298.43,NSW1NSW1 +319,2010-01-14 07:00:00,18051.3,NSW1NSW1 +320,2010-01-14 08:00:00,19263.84,NSW1NSW1 +321,2010-01-14 09:00:00,19881.35,NSW1NSW1 +322,2010-01-14 10:00:00,20094.28,NSW1NSW1 +323,2010-01-14 11:00:00,20144.620000000003,NSW1NSW1 +324,2010-01-14 12:00:00,20155.4,NSW1NSW1 +325,2010-01-14 13:00:00,20141.77,NSW1NSW1 +326,2010-01-14 14:00:00,20074.760000000002,NSW1NSW1 +327,2010-01-14 15:00:00,20228.22,NSW1NSW1 +328,2010-01-14 16:00:00,20004.129999999997,NSW1NSW1 +329,2010-01-14 17:00:00,19634.019999999997,NSW1NSW1 +330,2010-01-14 18:00:00,18976.61,NSW1NSW1 +331,2010-01-14 19:00:00,18409.559999999998,NSW1NSW1 +332,2010-01-14 20:00:00,18074.21,NSW1NSW1 +333,2010-01-14 21:00:00,17217.190000000002,NSW1NSW1 +334,2010-01-14 22:00:00,16784.510000000002,NSW1NSW1 +335,2010-01-14 23:00:00,16205.35,NSW1NSW1 +336,2010-01-15 00:00:00,15433.91,NSW1NSW1 +337,2010-01-15 01:00:00,14437.85,NSW1NSW1 +338,2010-01-15 02:00:00,13487.02,NSW1NSW1 +339,2010-01-15 03:00:00,13032.45,NSW1NSW1 +340,2010-01-15 04:00:00,13453.1,NSW1NSW1 +341,2010-01-15 05:00:00,14606.69,NSW1NSW1 +342,2010-01-15 06:00:00,16351.91,NSW1NSW1 +343,2010-01-15 07:00:00,18087.46,NSW1NSW1 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05:00:00,13519.96,NSW1NSW1 +366,2010-01-16 06:00:00,14357.19,NSW1NSW1 +367,2010-01-16 07:00:00,15887.630000000001,NSW1NSW1 +368,2010-01-16 08:00:00,17555.54,NSW1NSW1 +369,2010-01-16 09:00:00,18580.370000000003,NSW1NSW1 +370,2010-01-16 10:00:00,18999.64,NSW1NSW1 +371,2010-01-16 11:00:00,19119.14,NSW1NSW1 +372,2010-01-16 12:00:00,19176.980000000003,NSW1NSW1 +373,2010-01-16 13:00:00,19169.84,NSW1NSW1 +374,2010-01-16 14:00:00,19056.28,NSW1NSW1 +375,2010-01-16 15:00:00,18920.230000000003,NSW1NSW1 +376,2010-01-16 16:00:00,18562.66,NSW1NSW1 +377,2010-01-16 17:00:00,18066.82,NSW1NSW1 +378,2010-01-16 18:00:00,17558.71,NSW1NSW1 +379,2010-01-16 19:00:00,17294.04,NSW1NSW1 +380,2010-01-16 20:00:00,17209.61,NSW1NSW1 +381,2010-01-16 21:00:00,16632.14,NSW1NSW1 +382,2010-01-16 22:00:00,16281.82,NSW1NSW1 +383,2010-01-16 23:00:00,15286.43,NSW1NSW1 +384,2010-01-17 00:00:00,14521.73,NSW1NSW1 +385,2010-01-17 01:00:00,13618.07,NSW1NSW1 +386,2010-01-17 02:00:00,12823.470000000001,NSW1NSW1 +387,2010-01-17 03:00:00,12573.57,NSW1NSW1 +388,2010-01-17 04:00:00,12541.96,NSW1NSW1 +389,2010-01-17 05:00:00,12629.13,NSW1NSW1 +390,2010-01-17 06:00:00,13089.529999999999,NSW1NSW1 +391,2010-01-17 07:00:00,14384.73,NSW1NSW1 +392,2010-01-17 08:00:00,15836.689999999999,NSW1NSW1 +393,2010-01-17 09:00:00,17046.84,NSW1NSW1 +394,2010-01-17 10:00:00,17732.57,NSW1NSW1 +395,2010-01-17 11:00:00,18016.67,NSW1NSW1 +396,2010-01-17 12:00:00,18281.629999999997,NSW1NSW1 +397,2010-01-17 13:00:00,18294.71,NSW1NSW1 +398,2010-01-17 14:00:00,18009.68,NSW1NSW1 +399,2010-01-17 15:00:00,17814.6,NSW1NSW1 +400,2010-01-17 16:00:00,17583.559999999998,NSW1NSW1 +401,2010-01-17 17:00:00,17491.370000000003,NSW1NSW1 +402,2010-01-17 18:00:00,17084.64,NSW1NSW1 +403,2010-01-17 19:00:00,16689.29,NSW1NSW1 +404,2010-01-17 20:00:00,16953.629999999997,NSW1NSW1 +405,2010-01-17 21:00:00,16270.45,NSW1NSW1 +406,2010-01-17 22:00:00,15741.75,NSW1NSW1 +407,2010-01-17 23:00:00,14910.69,NSW1NSW1 +408,2010-01-18 00:00:00,14262.39,NSW1NSW1 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22:00:00,16372.21,NSW1NSW1 +431,2010-01-18 23:00:00,15871.92,NSW1NSW1 +432,2010-01-19 00:00:00,15220.73,NSW1NSW1 +433,2010-01-19 01:00:00,14343.07,NSW1NSW1 +434,2010-01-19 02:00:00,13322.85,NSW1NSW1 +435,2010-01-19 03:00:00,12960.41,NSW1NSW1 +436,2010-01-19 04:00:00,13281.779999999999,NSW1NSW1 +437,2010-01-19 05:00:00,14426.33,NSW1NSW1 +438,2010-01-19 06:00:00,15995.42,NSW1NSW1 +439,2010-01-19 07:00:00,17443.34,NSW1NSW1 +440,2010-01-19 08:00:00,18596.21,NSW1NSW1 +441,2010-01-19 09:00:00,19179.59,NSW1NSW1 +442,2010-01-19 10:00:00,19326.83,NSW1NSW1 +443,2010-01-19 11:00:00,19390.050000000003,NSW1NSW1 +444,2010-01-19 12:00:00,19301.53,NSW1NSW1 +445,2010-01-19 13:00:00,19314.629999999997,NSW1NSW1 +446,2010-01-19 14:00:00,19344.260000000002,NSW1NSW1 +447,2010-01-19 15:00:00,19272.05,NSW1NSW1 +448,2010-01-19 16:00:00,19146.28,NSW1NSW1 +449,2010-01-19 17:00:00,18546.800000000003,NSW1NSW1 +450,2010-01-19 18:00:00,17777.78,NSW1NSW1 +451,2010-01-19 19:00:00,17319.7,NSW1NSW1 +452,2010-01-19 20:00:00,17314.5,NSW1NSW1 +453,2010-01-19 21:00:00,16673.739999999998,NSW1NSW1 +454,2010-01-19 22:00:00,16183.91,NSW1NSW1 +455,2010-01-19 23:00:00,15619.45,NSW1NSW1 +456,2010-01-20 00:00:00,14928.41,NSW1NSW1 +457,2010-01-20 01:00:00,14094.57,NSW1NSW1 +458,2010-01-20 02:00:00,13090.8,NSW1NSW1 +459,2010-01-20 03:00:00,12729.1,NSW1NSW1 +460,2010-01-20 04:00:00,12914.869999999999,NSW1NSW1 +461,2010-01-20 05:00:00,14061.64,NSW1NSW1 +462,2010-01-20 06:00:00,15758.220000000001,NSW1NSW1 +463,2010-01-20 07:00:00,17454.64,NSW1NSW1 +464,2010-01-20 08:00:00,18740.68,NSW1NSW1 +465,2010-01-20 09:00:00,19564.370000000003,NSW1NSW1 +466,2010-01-20 10:00:00,19872.14,NSW1NSW1 +467,2010-01-20 11:00:00,20210.2,NSW1NSW1 +468,2010-01-20 12:00:00,20445.309999999998,NSW1NSW1 +469,2010-01-20 13:00:00,20816.2,NSW1NSW1 +470,2010-01-20 14:00:00,21171.91,NSW1NSW1 +471,2010-01-20 15:00:00,21477.68,NSW1NSW1 +472,2010-01-20 16:00:00,21571.35,NSW1NSW1 +473,2010-01-20 17:00:00,21013.739999999998,NSW1NSW1 +474,2010-01-20 18:00:00,20119.21,NSW1NSW1 +475,2010-01-20 19:00:00,19382.98,NSW1NSW1 +476,2010-01-20 20:00:00,19108.79,NSW1NSW1 +477,2010-01-20 21:00:00,18207.28,NSW1NSW1 +478,2010-01-20 22:00:00,17392.65,NSW1NSW1 +479,2010-01-20 23:00:00,16546.71,NSW1NSW1 +480,2010-01-21 00:00:00,15660.1,NSW1NSW1 +481,2010-01-21 01:00:00,14630.41,NSW1NSW1 +482,2010-01-21 02:00:00,13683.26,NSW1NSW1 +483,2010-01-21 03:00:00,13271.61,NSW1NSW1 +484,2010-01-21 04:00:00,13596.619999999999,NSW1NSW1 +485,2010-01-21 05:00:00,14645.32,NSW1NSW1 +486,2010-01-21 06:00:00,16372.329999999998,NSW1NSW1 +487,2010-01-21 07:00:00,18248.22,NSW1NSW1 +488,2010-01-21 08:00:00,19902.61,NSW1NSW1 +489,2010-01-21 09:00:00,20875.23,NSW1NSW1 +490,2010-01-21 10:00:00,21600.43,NSW1NSW1 +491,2010-01-21 11:00:00,22322.08,NSW1NSW1 +492,2010-01-21 12:00:00,23045.010000000002,NSW1NSW1 +493,2010-01-21 13:00:00,24003.53,NSW1NSW1 +494,2010-01-21 14:00:00,24640.8,NSW1NSW1 +495,2010-01-21 15:00:00,25059.97,NSW1NSW1 +496,2010-01-21 16:00:00,25443.86,NSW1NSW1 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14:00:00,27145.63,NSW1NSW1 +519,2010-01-22 15:00:00,27509.870000000003,NSW1NSW1 +520,2010-01-22 16:00:00,27291.82,NSW1NSW1 +521,2010-01-22 17:00:00,26287.14,NSW1NSW1 +522,2010-01-22 18:00:00,25020.91,NSW1NSW1 +523,2010-01-22 19:00:00,23940.27,NSW1NSW1 +524,2010-01-22 20:00:00,23479.73,NSW1NSW1 +525,2010-01-22 21:00:00,22249.32,NSW1NSW1 +526,2010-01-22 22:00:00,20802.95,NSW1NSW1 +527,2010-01-22 23:00:00,19312.16,NSW1NSW1 +528,2010-01-23 00:00:00,17742.78,NSW1NSW1 +529,2010-01-23 01:00:00,16301.26,NSW1NSW1 +530,2010-01-23 02:00:00,15054.14,NSW1NSW1 +531,2010-01-23 03:00:00,14580.41,NSW1NSW1 +532,2010-01-23 04:00:00,14537.48,NSW1NSW1 +533,2010-01-23 05:00:00,14782.849999999999,NSW1NSW1 +534,2010-01-23 06:00:00,15577.7,NSW1NSW1 +535,2010-01-23 07:00:00,17486.54,NSW1NSW1 +536,2010-01-23 08:00:00,19714.75,NSW1NSW1 +537,2010-01-23 09:00:00,21344.14,NSW1NSW1 +538,2010-01-23 10:00:00,22430.11,NSW1NSW1 +539,2010-01-23 11:00:00,23326.18,NSW1NSW1 +540,2010-01-23 12:00:00,23996.59,NSW1NSW1 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06:00:00,14341.6,NSW1NSW1 +607,2010-01-26 07:00:00,15721.24,NSW1NSW1 +608,2010-01-26 08:00:00,17303.97,NSW1NSW1 +609,2010-01-26 09:00:00,18923.28,NSW1NSW1 +610,2010-01-26 10:00:00,20113.75,NSW1NSW1 +611,2010-01-26 11:00:00,20874.06,NSW1NSW1 +612,2010-01-26 12:00:00,21462.199999999997,NSW1NSW1 +613,2010-01-26 13:00:00,21974.75,NSW1NSW1 +614,2010-01-26 14:00:00,22420.73,NSW1NSW1 +615,2010-01-26 15:00:00,22825.95,NSW1NSW1 +616,2010-01-26 16:00:00,22934.92,NSW1NSW1 +617,2010-01-26 17:00:00,22495.03,NSW1NSW1 +618,2010-01-26 18:00:00,21771.44,NSW1NSW1 +619,2010-01-26 19:00:00,20997.25,NSW1NSW1 +620,2010-01-26 20:00:00,20812.86,NSW1NSW1 +621,2010-01-26 21:00:00,19805.47,NSW1NSW1 +622,2010-01-26 22:00:00,18585.42,NSW1NSW1 +623,2010-01-26 23:00:00,17221.35,NSW1NSW1 +624,2010-01-27 00:00:00,16221.75,NSW1NSW1 +625,2010-01-27 01:00:00,15171.78,NSW1NSW1 +626,2010-01-27 02:00:00,14230.55,NSW1NSW1 +627,2010-01-27 03:00:00,13862.83,NSW1NSW1 +628,2010-01-27 04:00:00,14088.36,NSW1NSW1 +629,2010-01-27 05:00:00,15316.39,NSW1NSW1 +630,2010-01-27 06:00:00,17354.269999999997,NSW1NSW1 +631,2010-01-27 07:00:00,19285.309999999998,NSW1NSW1 +632,2010-01-27 08:00:00,20724.17,NSW1NSW1 +633,2010-01-27 09:00:00,21721.82,NSW1NSW1 +634,2010-01-27 10:00:00,22402.9,NSW1NSW1 +635,2010-01-27 11:00:00,22800.699999999997,NSW1NSW1 +636,2010-01-27 12:00:00,23065.839999999997,NSW1NSW1 +637,2010-01-27 13:00:00,23306.46,NSW1NSW1 +638,2010-01-27 14:00:00,23163.59,NSW1NSW1 +639,2010-01-27 15:00:00,22614.96,NSW1NSW1 +640,2010-01-27 16:00:00,22186.41,NSW1NSW1 +641,2010-01-27 17:00:00,20839.96,NSW1NSW1 +642,2010-01-27 18:00:00,20223.42,NSW1NSW1 +643,2010-01-27 19:00:00,19578.489999999998,NSW1NSW1 +644,2010-01-27 20:00:00,19250.489999999998,NSW1NSW1 +645,2010-01-27 21:00:00,18176.440000000002,NSW1NSW1 +646,2010-01-27 22:00:00,17305.81,NSW1NSW1 +647,2010-01-27 23:00:00,16531.72,NSW1NSW1 +648,2010-01-28 00:00:00,15653.369999999999,NSW1NSW1 +649,2010-01-28 01:00:00,14649.94,NSW1NSW1 +650,2010-01-28 02:00:00,13776.06,NSW1NSW1 +651,2010-01-28 03:00:00,13502.89,NSW1NSW1 +652,2010-01-28 04:00:00,13886.14,NSW1NSW1 +653,2010-01-28 05:00:00,15208.7,NSW1NSW1 +654,2010-01-28 06:00:00,17552.47,NSW1NSW1 +655,2010-01-28 07:00:00,19397.809999999998,NSW1NSW1 +656,2010-01-28 08:00:00,20466.379999999997,NSW1NSW1 +657,2010-01-28 09:00:00,21374.199999999997,NSW1NSW1 +658,2010-01-28 10:00:00,21933.800000000003,NSW1NSW1 +659,2010-01-28 11:00:00,22307.67,NSW1NSW1 +660,2010-01-28 12:00:00,22563.91,NSW1NSW1 +661,2010-01-28 13:00:00,22903.15,NSW1NSW1 +662,2010-01-28 14:00:00,22649.58,NSW1NSW1 +663,2010-01-28 15:00:00,22258.309999999998,NSW1NSW1 +664,2010-01-28 16:00:00,21932.83,NSW1NSW1 +665,2010-01-28 17:00:00,21520.2,NSW1NSW1 +666,2010-01-28 18:00:00,20742.239999999998,NSW1NSW1 +667,2010-01-28 19:00:00,20005.52,NSW1NSW1 +668,2010-01-28 20:00:00,18796.370000000003,NSW1NSW1 +669,2010-01-28 21:00:00,17879.78,NSW1NSW1 +670,2010-01-28 22:00:00,17358.690000000002,NSW1NSW1 +671,2010-01-28 23:00:00,16457.77,NSW1NSW1 +672,2010-01-29 00:00:00,15485.19,NSW1NSW1 +673,2010-01-29 01:00:00,14482.08,NSW1NSW1 +674,2010-01-29 02:00:00,13533.04,NSW1NSW1 +675,2010-01-29 03:00:00,13296.76,NSW1NSW1 +676,2010-01-29 04:00:00,13660.91,NSW1NSW1 +677,2010-01-29 05:00:00,14972.099999999999,NSW1NSW1 +678,2010-01-29 06:00:00,17198.55,NSW1NSW1 +679,2010-01-29 07:00:00,19020.93,NSW1NSW1 +680,2010-01-29 08:00:00,20236.57,NSW1NSW1 +681,2010-01-29 09:00:00,21240.73,NSW1NSW1 +682,2010-01-29 10:00:00,21887.06,NSW1NSW1 +683,2010-01-29 11:00:00,22245.32,NSW1NSW1 +684,2010-01-29 12:00:00,22482.16,NSW1NSW1 +685,2010-01-29 13:00:00,22767.22,NSW1NSW1 +686,2010-01-29 14:00:00,22800.04,NSW1NSW1 +687,2010-01-29 15:00:00,22903.03,NSW1NSW1 +688,2010-01-29 16:00:00,22534.48,NSW1NSW1 +689,2010-01-29 17:00:00,21170.629999999997,NSW1NSW1 +690,2010-01-29 18:00:00,19853.18,NSW1NSW1 +691,2010-01-29 19:00:00,18983.61,NSW1NSW1 +692,2010-01-29 20:00:00,18761.5,NSW1NSW1 +693,2010-01-29 21:00:00,17838.98,NSW1NSW1 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10:00:00,21890.23,NSW1NSW1 +827,2010-02-04 11:00:00,21632.739999999998,NSW1NSW1 +828,2010-02-04 12:00:00,21892.41,NSW1NSW1 +829,2010-02-04 13:00:00,22194.2,NSW1NSW1 +830,2010-02-04 14:00:00,22159.44,NSW1NSW1 +831,2010-02-04 15:00:00,22072.510000000002,NSW1NSW1 +832,2010-02-04 16:00:00,21841.81,NSW1NSW1 +833,2010-02-04 17:00:00,21365.739999999998,NSW1NSW1 +834,2010-02-04 18:00:00,20515.760000000002,NSW1NSW1 +835,2010-02-04 19:00:00,19871.12,NSW1NSW1 +836,2010-02-04 20:00:00,19581.5,NSW1NSW1 +837,2010-02-04 21:00:00,18633.379999999997,NSW1NSW1 +838,2010-02-04 22:00:00,17821.13,NSW1NSW1 +839,2010-02-04 23:00:00,17051.12,NSW1NSW1 +840,2010-02-05 00:00:00,16033.76,NSW1NSW1 +841,2010-02-05 01:00:00,15018.27,NSW1NSW1 +842,2010-02-05 02:00:00,14123.71,NSW1NSW1 +843,2010-02-05 03:00:00,13883.130000000001,NSW1NSW1 +844,2010-02-05 04:00:00,14242.89,NSW1NSW1 +845,2010-02-05 05:00:00,15676.67,NSW1NSW1 +846,2010-02-05 06:00:00,18109.84,NSW1NSW1 +847,2010-02-05 07:00:00,20105.36,NSW1NSW1 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04:00:00,12573.01,NSW1NSW1 +893,2010-02-07 05:00:00,12791.810000000001,NSW1NSW1 +894,2010-02-07 06:00:00,13298.720000000001,NSW1NSW1 +895,2010-02-07 07:00:00,14536.74,NSW1NSW1 +896,2010-02-07 08:00:00,16083.38,NSW1NSW1 +897,2010-02-07 09:00:00,17230.17,NSW1NSW1 +898,2010-02-07 10:00:00,17659.16,NSW1NSW1 +899,2010-02-07 11:00:00,18017.940000000002,NSW1NSW1 +900,2010-02-07 12:00:00,18121.33,NSW1NSW1 +901,2010-02-07 13:00:00,17937.059999999998,NSW1NSW1 +902,2010-02-07 14:00:00,18046.97,NSW1NSW1 +903,2010-02-07 15:00:00,18215.57,NSW1NSW1 +904,2010-02-07 16:00:00,18348.1,NSW1NSW1 +905,2010-02-07 17:00:00,18557.879999999997,NSW1NSW1 +906,2010-02-07 18:00:00,18268.92,NSW1NSW1 +907,2010-02-07 19:00:00,18209.010000000002,NSW1NSW1 +908,2010-02-07 20:00:00,18136.36,NSW1NSW1 +909,2010-02-07 21:00:00,17164.61,NSW1NSW1 +910,2010-02-07 22:00:00,16526.440000000002,NSW1NSW1 +911,2010-02-07 23:00:00,15568.02,NSW1NSW1 +912,2010-02-08 00:00:00,14858.23,NSW1NSW1 +913,2010-02-08 01:00:00,14221.66,NSW1NSW1 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00:00:00,16158.49,NSW1NSW1 +937,2010-02-09 01:00:00,15111.04,NSW1NSW1 +938,2010-02-09 02:00:00,14117.42,NSW1NSW1 +939,2010-02-09 03:00:00,13834.99,NSW1NSW1 +940,2010-02-09 04:00:00,14175.43,NSW1NSW1 +941,2010-02-09 05:00:00,15539.18,NSW1NSW1 +942,2010-02-09 06:00:00,17892.11,NSW1NSW1 +943,2010-02-09 07:00:00,19675.37,NSW1NSW1 +944,2010-02-09 08:00:00,20861.67,NSW1NSW1 +945,2010-02-09 09:00:00,21831.58,NSW1NSW1 +946,2010-02-09 10:00:00,22274.03,NSW1NSW1 +947,2010-02-09 11:00:00,22626.87,NSW1NSW1 +948,2010-02-09 12:00:00,22741.800000000003,NSW1NSW1 +949,2010-02-09 13:00:00,22936.83,NSW1NSW1 +950,2010-02-09 14:00:00,23005.440000000002,NSW1NSW1 +951,2010-02-09 15:00:00,23631.27,NSW1NSW1 +952,2010-02-09 16:00:00,23612.129999999997,NSW1NSW1 +953,2010-02-09 17:00:00,22748.56,NSW1NSW1 +954,2010-02-09 18:00:00,21684.21,NSW1NSW1 +955,2010-02-09 19:00:00,21118.42,NSW1NSW1 +956,2010-02-09 20:00:00,20669.64,NSW1NSW1 +957,2010-02-09 21:00:00,19380.1,NSW1NSW1 +958,2010-02-09 22:00:00,18369.59,NSW1NSW1 +959,2010-02-09 23:00:00,17297.27,NSW1NSW1 +960,2010-02-10 00:00:00,16294.59,NSW1NSW1 +961,2010-02-10 01:00:00,15310.03,NSW1NSW1 +962,2010-02-10 02:00:00,14213.880000000001,NSW1NSW1 +963,2010-02-10 03:00:00,13891.48,NSW1NSW1 +964,2010-02-10 04:00:00,14159.86,NSW1NSW1 +965,2010-02-10 05:00:00,15618.009999999998,NSW1NSW1 +966,2010-02-10 06:00:00,17998.82,NSW1NSW1 +967,2010-02-10 07:00:00,19733.010000000002,NSW1NSW1 +968,2010-02-10 08:00:00,21060.96,NSW1NSW1 +969,2010-02-10 09:00:00,22129.300000000003,NSW1NSW1 +970,2010-02-10 10:00:00,22782.9,NSW1NSW1 +971,2010-02-10 11:00:00,23234.46,NSW1NSW1 +972,2010-02-10 12:00:00,23622.35,NSW1NSW1 +973,2010-02-10 13:00:00,24119.690000000002,NSW1NSW1 +974,2010-02-10 14:00:00,24265.02,NSW1NSW1 +975,2010-02-10 15:00:00,24691.5,NSW1NSW1 +976,2010-02-10 16:00:00,24676.29,NSW1NSW1 +977,2010-02-10 17:00:00,23565.46,NSW1NSW1 +978,2010-02-10 18:00:00,22307.989999999998,NSW1NSW1 +979,2010-02-10 19:00:00,21627.940000000002,NSW1NSW1 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15:00:00,26048.620000000003,NSW1NSW1 +1024,2010-02-12 16:00:00,26127.07,NSW1NSW1 +1025,2010-02-12 17:00:00,24296.14,NSW1NSW1 +1026,2010-02-12 18:00:00,22284.41,NSW1NSW1 +1027,2010-02-12 19:00:00,21283.6,NSW1NSW1 +1028,2010-02-12 20:00:00,20493.78,NSW1NSW1 +1029,2010-02-12 21:00:00,19309.120000000003,NSW1NSW1 +1030,2010-02-12 22:00:00,18509.11,NSW1NSW1 +1031,2010-02-12 23:00:00,17451.88,NSW1NSW1 +1032,2010-02-13 00:00:00,16208.72,NSW1NSW1 +1033,2010-02-13 01:00:00,14978.09,NSW1NSW1 +1034,2010-02-13 02:00:00,14008.93,NSW1NSW1 +1035,2010-02-13 03:00:00,13676.1,NSW1NSW1 +1036,2010-02-13 04:00:00,13630.3,NSW1NSW1 +1037,2010-02-13 05:00:00,14062.470000000001,NSW1NSW1 +1038,2010-02-13 06:00:00,15021.400000000001,NSW1NSW1 +1039,2010-02-13 07:00:00,16627.559999999998,NSW1NSW1 +1040,2010-02-13 08:00:00,18323.73,NSW1NSW1 +1041,2010-02-13 09:00:00,19115.809999999998,NSW1NSW1 +1042,2010-02-13 10:00:00,19248.58,NSW1NSW1 +1043,2010-02-13 11:00:00,19393.53,NSW1NSW1 +1044,2010-02-13 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17:00:00,20478.61,NSW1NSW1 +1626,2010-03-09 18:00:00,19733.43,NSW1NSW1 +1627,2010-03-09 19:00:00,19610.71,NSW1NSW1 +1628,2010-03-09 20:00:00,18675.96,NSW1NSW1 +1629,2010-03-09 21:00:00,17450.89,NSW1NSW1 +1630,2010-03-09 22:00:00,16835.9,NSW1NSW1 +1631,2010-03-09 23:00:00,16171.14,NSW1NSW1 +1632,2010-03-10 00:00:00,15360.68,NSW1NSW1 +1633,2010-03-10 01:00:00,14373.28,NSW1NSW1 +1634,2010-03-10 02:00:00,13404.689999999999,NSW1NSW1 +1635,2010-03-10 03:00:00,13101.119999999999,NSW1NSW1 +1636,2010-03-10 04:00:00,13462.279999999999,NSW1NSW1 +1637,2010-03-10 05:00:00,14937.22,NSW1NSW1 +1638,2010-03-10 06:00:00,17313.260000000002,NSW1NSW1 +1639,2010-03-10 07:00:00,18703.989999999998,NSW1NSW1 +1640,2010-03-10 08:00:00,19235.09,NSW1NSW1 +1641,2010-03-10 09:00:00,19719.550000000003,NSW1NSW1 +1642,2010-03-10 10:00:00,19771.12,NSW1NSW1 +1643,2010-03-10 11:00:00,19674.61,NSW1NSW1 +1644,2010-03-10 12:00:00,19539.08,NSW1NSW1 +1645,2010-03-10 13:00:00,19443.63,NSW1NSW1 +1646,2010-03-10 14:00:00,19263.82,NSW1NSW1 +1647,2010-03-10 15:00:00,19146.71,NSW1NSW1 +1648,2010-03-10 16:00:00,19097.11,NSW1NSW1 +1649,2010-03-10 17:00:00,18600.37,NSW1NSW1 +1650,2010-03-10 18:00:00,17577.18,NSW1NSW1 +1651,2010-03-10 19:00:00,18017.370000000003,NSW1NSW1 +1652,2010-03-10 20:00:00,17287.25,NSW1NSW1 +1653,2010-03-10 21:00:00,16375.01,NSW1NSW1 +1654,2010-03-10 22:00:00,16132.36,NSW1NSW1 +1655,2010-03-10 23:00:00,15607.099999999999,NSW1NSW1 +1656,2010-03-11 00:00:00,14941.01,NSW1NSW1 +1657,2010-03-11 01:00:00,14146.98,NSW1NSW1 +1658,2010-03-11 02:00:00,13212.560000000001,NSW1NSW1 +1659,2010-03-11 03:00:00,12753.61,NSW1NSW1 +1660,2010-03-11 04:00:00,13020.849999999999,NSW1NSW1 +1661,2010-03-11 05:00:00,14498.48,NSW1NSW1 +1662,2010-03-11 06:00:00,16834.41,NSW1NSW1 +1663,2010-03-11 07:00:00,18189.03,NSW1NSW1 +1664,2010-03-11 08:00:00,18613.91,NSW1NSW1 +1665,2010-03-11 09:00:00,19014.71,NSW1NSW1 +1666,2010-03-11 10:00:00,19169.050000000003,NSW1NSW1 +1667,2010-03-11 11:00:00,19188.67,NSW1NSW1 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09:00:00,19312.35,NSW1NSW1 +1690,2010-03-12 10:00:00,19453.120000000003,NSW1NSW1 +1691,2010-03-12 11:00:00,19222.1,NSW1NSW1 +1692,2010-03-12 12:00:00,19262.989999999998,NSW1NSW1 +1693,2010-03-12 13:00:00,19119.690000000002,NSW1NSW1 +1694,2010-03-12 14:00:00,18861.34,NSW1NSW1 +1695,2010-03-12 15:00:00,18724.809999999998,NSW1NSW1 +1696,2010-03-12 16:00:00,18609.03,NSW1NSW1 +1697,2010-03-12 17:00:00,17887.69,NSW1NSW1 +1698,2010-03-12 18:00:00,17314.98,NSW1NSW1 +1699,2010-03-12 19:00:00,17321.510000000002,NSW1NSW1 +1700,2010-03-12 20:00:00,16856.23,NSW1NSW1 +1701,2010-03-12 21:00:00,16215.09,NSW1NSW1 +1702,2010-03-12 22:00:00,16227.25,NSW1NSW1 +1703,2010-03-12 23:00:00,15803.939999999999,NSW1NSW1 +1704,2010-03-13 00:00:00,15063.400000000001,NSW1NSW1 +1705,2010-03-13 01:00:00,14159.029999999999,NSW1NSW1 +1706,2010-03-13 02:00:00,13110.880000000001,NSW1NSW1 +1707,2010-03-13 03:00:00,12591.27,NSW1NSW1 +1708,2010-03-13 04:00:00,12643.33,NSW1NSW1 +1709,2010-03-13 05:00:00,13104.619999999999,NSW1NSW1 +1710,2010-03-13 06:00:00,14019.93,NSW1NSW1 +1711,2010-03-13 07:00:00,15468.119999999999,NSW1NSW1 +1712,2010-03-13 08:00:00,16918.39,NSW1NSW1 +1713,2010-03-13 09:00:00,17532.83,NSW1NSW1 +1714,2010-03-13 10:00:00,17618.989999999998,NSW1NSW1 +1715,2010-03-13 11:00:00,17436.41,NSW1NSW1 +1716,2010-03-13 12:00:00,17191.86,NSW1NSW1 +1717,2010-03-13 13:00:00,16861.38,NSW1NSW1 +1718,2010-03-13 14:00:00,16652.36,NSW1NSW1 +1719,2010-03-13 15:00:00,16510.78,NSW1NSW1 +1720,2010-03-13 16:00:00,16533.17,NSW1NSW1 +1721,2010-03-13 17:00:00,16458.82,NSW1NSW1 +1722,2010-03-13 18:00:00,16375.990000000002,NSW1NSW1 +1723,2010-03-13 19:00:00,16475.59,NSW1NSW1 +1724,2010-03-13 20:00:00,15888.54,NSW1NSW1 +1725,2010-03-13 21:00:00,15490.98,NSW1NSW1 +1726,2010-03-13 22:00:00,15348.13,NSW1NSW1 +1727,2010-03-13 23:00:00,14667.35,NSW1NSW1 +1728,2010-03-14 00:00:00,14051.220000000001,NSW1NSW1 +1729,2010-03-14 01:00:00,13300.189999999999,NSW1NSW1 +1730,2010-03-14 02:00:00,12491.08,NSW1NSW1 +1731,2010-03-14 03:00:00,12167.02,NSW1NSW1 +1732,2010-03-14 04:00:00,12219.95,NSW1NSW1 +1733,2010-03-14 05:00:00,12501.82,NSW1NSW1 +1734,2010-03-14 06:00:00,13005.98,NSW1NSW1 +1735,2010-03-14 07:00:00,14171.67,NSW1NSW1 +1736,2010-03-14 08:00:00,15571.7,NSW1NSW1 +1737,2010-03-14 09:00:00,16450.58,NSW1NSW1 +1738,2010-03-14 10:00:00,16728.42,NSW1NSW1 +1739,2010-03-14 11:00:00,16725.53,NSW1NSW1 +1740,2010-03-14 12:00:00,16584.3,NSW1NSW1 +1741,2010-03-14 13:00:00,16366.29,NSW1NSW1 +1742,2010-03-14 14:00:00,16309.16,NSW1NSW1 +1743,2010-03-14 15:00:00,16560.32,NSW1NSW1 +1744,2010-03-14 16:00:00,16530.14,NSW1NSW1 +1745,2010-03-14 17:00:00,16663.51,NSW1NSW1 +1746,2010-03-14 18:00:00,16667.92,NSW1NSW1 +1747,2010-03-14 19:00:00,17028.739999999998,NSW1NSW1 +1748,2010-03-14 20:00:00,16537.07,NSW1NSW1 +1749,2010-03-14 21:00:00,15734.56,NSW1NSW1 +1750,2010-03-14 22:00:00,15257.2,NSW1NSW1 +1751,2010-03-14 23:00:00,14710.0,NSW1NSW1 +1752,2010-03-15 00:00:00,14179.23,NSW1NSW1 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13:00:00,20419.28,NSW1NSW1 +1838,2010-03-18 14:00:00,20520.06,NSW1NSW1 +1839,2010-03-18 15:00:00,20808.96,NSW1NSW1 +1840,2010-03-18 16:00:00,20783.18,NSW1NSW1 +1841,2010-03-18 17:00:00,20247.33,NSW1NSW1 +1842,2010-03-18 18:00:00,19518.07,NSW1NSW1 +1843,2010-03-18 19:00:00,19475.9,NSW1NSW1 +1844,2010-03-18 20:00:00,18495.61,NSW1NSW1 +1845,2010-03-18 21:00:00,17357.59,NSW1NSW1 +1846,2010-03-18 22:00:00,16828.73,NSW1NSW1 +1847,2010-03-18 23:00:00,16194.060000000001,NSW1NSW1 +1848,2010-03-19 00:00:00,15418.34,NSW1NSW1 +1849,2010-03-19 01:00:00,14489.0,NSW1NSW1 +1850,2010-03-19 02:00:00,13522.32,NSW1NSW1 +1851,2010-03-19 03:00:00,13131.07,NSW1NSW1 +1852,2010-03-19 04:00:00,13475.54,NSW1NSW1 +1853,2010-03-19 05:00:00,14897.14,NSW1NSW1 +1854,2010-03-19 06:00:00,17101.05,NSW1NSW1 +1855,2010-03-19 07:00:00,18363.13,NSW1NSW1 +1856,2010-03-19 08:00:00,19151.79,NSW1NSW1 +1857,2010-03-19 09:00:00,19804.02,NSW1NSW1 +1858,2010-03-19 10:00:00,20148.089999999997,NSW1NSW1 +1859,2010-03-19 11:00:00,20426.07,NSW1NSW1 +1860,2010-03-19 12:00:00,20763.53,NSW1NSW1 +1861,2010-03-19 13:00:00,21074.4,NSW1NSW1 +1862,2010-03-19 14:00:00,21189.3,NSW1NSW1 +1863,2010-03-19 15:00:00,21479.09,NSW1NSW1 +1864,2010-03-19 16:00:00,21533.21,NSW1NSW1 +1865,2010-03-19 17:00:00,20646.15,NSW1NSW1 +1866,2010-03-19 18:00:00,19619.28,NSW1NSW1 +1867,2010-03-19 19:00:00,19458.690000000002,NSW1NSW1 +1868,2010-03-19 20:00:00,18585.0,NSW1NSW1 +1869,2010-03-19 21:00:00,17660.48,NSW1NSW1 +1870,2010-03-19 22:00:00,17318.83,NSW1NSW1 +1871,2010-03-19 23:00:00,16636.08,NSW1NSW1 +1872,2010-03-20 00:00:00,15696.66,NSW1NSW1 +1873,2010-03-20 01:00:00,14563.0,NSW1NSW1 +1874,2010-03-20 02:00:00,13501.64,NSW1NSW1 +1875,2010-03-20 03:00:00,13080.5,NSW1NSW1 +1876,2010-03-20 04:00:00,13083.11,NSW1NSW1 +1877,2010-03-20 05:00:00,13564.27,NSW1NSW1 +1878,2010-03-20 06:00:00,14367.29,NSW1NSW1 +1879,2010-03-20 07:00:00,15786.33,NSW1NSW1 +1880,2010-03-20 08:00:00,17334.74,NSW1NSW1 +1881,2010-03-20 09:00:00,18076.06,NSW1NSW1 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06:00:00,13515.560000000001,NSW1NSW1 +1903,2010-03-21 07:00:00,14580.07,NSW1NSW1 +1904,2010-03-21 08:00:00,15914.83,NSW1NSW1 +1905,2010-03-21 09:00:00,17004.510000000002,NSW1NSW1 +1906,2010-03-21 10:00:00,17497.14,NSW1NSW1 +1907,2010-03-21 11:00:00,17800.879999999997,NSW1NSW1 +1908,2010-03-21 12:00:00,18234.51,NSW1NSW1 +1909,2010-03-21 13:00:00,18852.04,NSW1NSW1 +1910,2010-03-21 14:00:00,19252.690000000002,NSW1NSW1 +1911,2010-03-21 15:00:00,19654.83,NSW1NSW1 +1912,2010-03-21 16:00:00,19846.84,NSW1NSW1 +1913,2010-03-21 17:00:00,20007.81,NSW1NSW1 +1914,2010-03-21 18:00:00,19880.32,NSW1NSW1 +1915,2010-03-21 19:00:00,20039.7,NSW1NSW1 +1916,2010-03-21 20:00:00,19088.980000000003,NSW1NSW1 +1917,2010-03-21 21:00:00,17428.4,NSW1NSW1 +1918,2010-03-21 22:00:00,16366.02,NSW1NSW1 +1919,2010-03-21 23:00:00,15336.119999999999,NSW1NSW1 +1920,2010-03-22 00:00:00,14590.61,NSW1NSW1 +1921,2010-03-22 01:00:00,13935.990000000002,NSW1NSW1 +1922,2010-03-22 02:00:00,13267.619999999999,NSW1NSW1 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00:00:00,15269.35,NSW1NSW1 +1945,2010-03-23 01:00:00,14476.55,NSW1NSW1 +1946,2010-03-23 02:00:00,13445.43,NSW1NSW1 +1947,2010-03-23 03:00:00,13104.96,NSW1NSW1 +1948,2010-03-23 04:00:00,13509.58,NSW1NSW1 +1949,2010-03-23 05:00:00,14979.880000000001,NSW1NSW1 +1950,2010-03-23 06:00:00,17401.620000000003,NSW1NSW1 +1951,2010-03-23 07:00:00,18721.84,NSW1NSW1 +1952,2010-03-23 08:00:00,19389.29,NSW1NSW1 +1953,2010-03-23 09:00:00,20113.71,NSW1NSW1 +1954,2010-03-23 10:00:00,20455.949999999997,NSW1NSW1 +1955,2010-03-23 11:00:00,20589.61,NSW1NSW1 +1956,2010-03-23 12:00:00,20875.78,NSW1NSW1 +1957,2010-03-23 13:00:00,21221.07,NSW1NSW1 +1958,2010-03-23 14:00:00,21364.52,NSW1NSW1 +1959,2010-03-23 15:00:00,21568.449999999997,NSW1NSW1 +1960,2010-03-23 16:00:00,21564.96,NSW1NSW1 +1961,2010-03-23 17:00:00,20759.910000000003,NSW1NSW1 +1962,2010-03-23 18:00:00,19959.08,NSW1NSW1 +1963,2010-03-23 19:00:00,19912.050000000003,NSW1NSW1 +1964,2010-03-23 20:00:00,18794.190000000002,NSW1NSW1 +1965,2010-03-23 21:00:00,17539.510000000002,NSW1NSW1 +1966,2010-03-23 22:00:00,16966.47,NSW1NSW1 +1967,2010-03-23 23:00:00,16318.5,NSW1NSW1 +1968,2010-03-24 00:00:00,15492.54,NSW1NSW1 +1969,2010-03-24 01:00:00,14615.23,NSW1NSW1 +1970,2010-03-24 02:00:00,13647.39,NSW1NSW1 +1971,2010-03-24 03:00:00,13215.78,NSW1NSW1 +1972,2010-03-24 04:00:00,13545.57,NSW1NSW1 +1973,2010-03-24 05:00:00,15012.93,NSW1NSW1 +1974,2010-03-24 06:00:00,17380.449999999997,NSW1NSW1 +1975,2010-03-24 07:00:00,18654.86,NSW1NSW1 +1976,2010-03-24 08:00:00,19302.510000000002,NSW1NSW1 +1977,2010-03-24 09:00:00,19982.21,NSW1NSW1 +1978,2010-03-24 10:00:00,20410.68,NSW1NSW1 +1979,2010-03-24 11:00:00,20595.25,NSW1NSW1 +1980,2010-03-24 12:00:00,20600.55,NSW1NSW1 +1981,2010-03-24 13:00:00,20697.93,NSW1NSW1 +1982,2010-03-24 14:00:00,20624.04,NSW1NSW1 +1983,2010-03-24 15:00:00,20402.43,NSW1NSW1 +1984,2010-03-24 16:00:00,20276.53,NSW1NSW1 +1985,2010-03-24 17:00:00,19577.82,NSW1NSW1 +1986,2010-03-24 18:00:00,19126.79,NSW1NSW1 +1987,2010-03-24 19:00:00,18918.11,NSW1NSW1 +1988,2010-03-24 20:00:00,18100.9,NSW1NSW1 +1989,2010-03-24 21:00:00,17222.47,NSW1NSW1 +1990,2010-03-24 22:00:00,16690.019999999997,NSW1NSW1 +1991,2010-03-24 23:00:00,16121.93,NSW1NSW1 +1992,2010-03-25 00:00:00,15401.529999999999,NSW1NSW1 +1993,2010-03-25 01:00:00,14553.8,NSW1NSW1 +1994,2010-03-25 02:00:00,13580.07,NSW1NSW1 +1995,2010-03-25 03:00:00,13246.01,NSW1NSW1 +1996,2010-03-25 04:00:00,13589.54,NSW1NSW1 +1997,2010-03-25 05:00:00,15051.2,NSW1NSW1 +1998,2010-03-25 06:00:00,17416.62,NSW1NSW1 +1999,2010-03-25 07:00:00,18685.18,NSW1NSW1 +2000,2010-03-25 08:00:00,19202.66,NSW1NSW1 +2001,2010-03-25 09:00:00,19864.5,NSW1NSW1 +2002,2010-03-25 10:00:00,19740.06,NSW1NSW1 +2003,2010-03-25 11:00:00,20533.010000000002,NSW1NSW1 +2004,2010-03-25 12:00:00,20637.3,NSW1NSW1 +2005,2010-03-25 13:00:00,20847.379999999997,NSW1NSW1 +2006,2010-03-25 14:00:00,20976.89,NSW1NSW1 +2007,2010-03-25 15:00:00,21165.3,NSW1NSW1 +2008,2010-03-25 16:00:00,21077.559999999998,NSW1NSW1 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14:00:00,22747.11,NSW1NSW1 +2031,2010-03-26 15:00:00,23064.98,NSW1NSW1 +2032,2010-03-26 16:00:00,23008.66,NSW1NSW1 +2033,2010-03-26 17:00:00,21732.3,NSW1NSW1 +2034,2010-03-26 18:00:00,20780.120000000003,NSW1NSW1 +2035,2010-03-26 19:00:00,20467.510000000002,NSW1NSW1 +2036,2010-03-26 20:00:00,19382.7,NSW1NSW1 +2037,2010-03-26 21:00:00,18404.9,NSW1NSW1 +2038,2010-03-26 22:00:00,17857.75,NSW1NSW1 +2039,2010-03-26 23:00:00,16934.71,NSW1NSW1 +2040,2010-03-27 00:00:00,15871.75,NSW1NSW1 +2041,2010-03-27 01:00:00,14651.279999999999,NSW1NSW1 +2042,2010-03-27 02:00:00,13717.48,NSW1NSW1 +2043,2010-03-27 03:00:00,13228.74,NSW1NSW1 +2044,2010-03-27 04:00:00,13285.68,NSW1NSW1 +2045,2010-03-27 05:00:00,13918.36,NSW1NSW1 +2046,2010-03-27 06:00:00,14822.880000000001,NSW1NSW1 +2047,2010-03-27 07:00:00,16300.25,NSW1NSW1 +2048,2010-03-27 08:00:00,17823.15,NSW1NSW1 +2049,2010-03-27 09:00:00,18628.08,NSW1NSW1 +2050,2010-03-27 10:00:00,18832.510000000002,NSW1NSW1 +2051,2010-03-27 11:00:00,19048.84,NSW1NSW1 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09:00:00,17242.79,NSW1NSW1 +2074,2010-03-28 10:00:00,17826.43,NSW1NSW1 +2075,2010-03-28 11:00:00,18372.15,NSW1NSW1 +2076,2010-03-28 12:00:00,18865.17,NSW1NSW1 +2077,2010-03-28 13:00:00,19198.940000000002,NSW1NSW1 +2078,2010-03-28 14:00:00,19394.91,NSW1NSW1 +2079,2010-03-28 15:00:00,19598.93,NSW1NSW1 +2080,2010-03-28 16:00:00,19530.97,NSW1NSW1 +2081,2010-03-28 17:00:00,19328.35,NSW1NSW1 +2082,2010-03-28 18:00:00,19254.33,NSW1NSW1 +2083,2010-03-28 19:00:00,19137.57,NSW1NSW1 +2084,2010-03-28 20:00:00,18256.53,NSW1NSW1 +2085,2010-03-28 21:00:00,17092.75,NSW1NSW1 +2086,2010-03-28 22:00:00,16350.11,NSW1NSW1 +2087,2010-03-28 23:00:00,15324.66,NSW1NSW1 +2088,2010-03-29 00:00:00,14695.74,NSW1NSW1 +2089,2010-03-29 01:00:00,14001.23,NSW1NSW1 +2090,2010-03-29 02:00:00,13427.99,NSW1NSW1 +2091,2010-03-29 03:00:00,13169.56,NSW1NSW1 +2092,2010-03-29 04:00:00,13623.23,NSW1NSW1 +2093,2010-03-29 05:00:00,15240.6,NSW1NSW1 +2094,2010-03-29 06:00:00,17763.58,NSW1NSW1 +2095,2010-03-29 07:00:00,19413.17,NSW1NSW1 +2096,2010-03-29 08:00:00,20264.82,NSW1NSW1 +2097,2010-03-29 09:00:00,20887.24,NSW1NSW1 +2098,2010-03-29 10:00:00,21130.050000000003,NSW1NSW1 +2099,2010-03-29 11:00:00,21295.48,NSW1NSW1 +2100,2010-03-29 12:00:00,21172.93,NSW1NSW1 +2101,2010-03-29 13:00:00,21096.63,NSW1NSW1 +2102,2010-03-29 14:00:00,20851.489999999998,NSW1NSW1 +2103,2010-03-29 15:00:00,20705.129999999997,NSW1NSW1 +2104,2010-03-29 16:00:00,20718.379999999997,NSW1NSW1 +2105,2010-03-29 17:00:00,20447.440000000002,NSW1NSW1 +2106,2010-03-29 18:00:00,20175.72,NSW1NSW1 +2107,2010-03-29 19:00:00,19637.08,NSW1NSW1 +2108,2010-03-29 20:00:00,18734.45,NSW1NSW1 +2109,2010-03-29 21:00:00,17706.8,NSW1NSW1 +2110,2010-03-29 22:00:00,17186.559999999998,NSW1NSW1 +2111,2010-03-29 23:00:00,16623.68,NSW1NSW1 +2112,2010-03-30 00:00:00,15883.130000000001,NSW1NSW1 +2113,2010-03-30 01:00:00,14906.83,NSW1NSW1 +2114,2010-03-30 02:00:00,13984.380000000001,NSW1NSW1 +2115,2010-03-30 03:00:00,13628.05,NSW1NSW1 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23:00:00,15629.22,NSW1NSW1 +2928,2010-05-03 00:00:00,15022.27,NSW1NSW1 +2929,2010-05-03 01:00:00,14235.689999999999,NSW1NSW1 +2930,2010-05-03 02:00:00,13503.68,NSW1NSW1 +2931,2010-05-03 03:00:00,12771.16,NSW1NSW1 +2932,2010-05-03 04:00:00,12701.21,NSW1NSW1 +2933,2010-05-03 05:00:00,13170.04,NSW1NSW1 +2934,2010-05-03 06:00:00,15010.14,NSW1NSW1 +2935,2010-05-03 07:00:00,17301.980000000003,NSW1NSW1 +2936,2010-05-03 08:00:00,18529.660000000003,NSW1NSW1 +2937,2010-05-03 09:00:00,18909.82,NSW1NSW1 +2938,2010-05-03 10:00:00,19261.32,NSW1NSW1 +2939,2010-05-03 11:00:00,19318.05,NSW1NSW1 +2940,2010-05-03 12:00:00,19407.39,NSW1NSW1 +2941,2010-05-03 13:00:00,19253.79,NSW1NSW1 +2942,2010-05-03 14:00:00,19267.1,NSW1NSW1 +2943,2010-05-03 15:00:00,19066.64,NSW1NSW1 +2944,2010-05-03 16:00:00,18978.28,NSW1NSW1 +2945,2010-05-03 17:00:00,19307.47,NSW1NSW1 +2946,2010-05-03 18:00:00,20383.18,NSW1NSW1 +2947,2010-05-03 19:00:00,19442.17,NSW1NSW1 +2948,2010-05-03 20:00:00,18486.91,NSW1NSW1 +2949,2010-05-03 21:00:00,17697.32,NSW1NSW1 +2950,2010-05-03 22:00:00,17130.43,NSW1NSW1 +2951,2010-05-03 23:00:00,16958.16,NSW1NSW1 +2952,2010-05-04 00:00:00,16425.57,NSW1NSW1 +2953,2010-05-04 01:00:00,15682.470000000001,NSW1NSW1 +2954,2010-05-04 02:00:00,14606.630000000001,NSW1NSW1 +2955,2010-05-04 03:00:00,13460.369999999999,NSW1NSW1 +2956,2010-05-04 04:00:00,13044.64,NSW1NSW1 +2957,2010-05-04 05:00:00,13456.2,NSW1NSW1 +2958,2010-05-04 06:00:00,15180.189999999999,NSW1NSW1 +2959,2010-05-04 07:00:00,17579.32,NSW1NSW1 +2960,2010-05-04 08:00:00,18680.59,NSW1NSW1 +2961,2010-05-04 09:00:00,18935.91,NSW1NSW1 +2962,2010-05-04 10:00:00,19003.34,NSW1NSW1 +2963,2010-05-04 11:00:00,19150.02,NSW1NSW1 +2964,2010-05-04 12:00:00,19119.07,NSW1NSW1 +2965,2010-05-04 13:00:00,19015.46,NSW1NSW1 +2966,2010-05-04 14:00:00,18935.83,NSW1NSW1 +2967,2010-05-04 15:00:00,18698.45,NSW1NSW1 +2968,2010-05-04 16:00:00,18820.98,NSW1NSW1 +2969,2010-05-04 17:00:00,19208.45,NSW1NSW1 +2970,2010-05-04 18:00:00,20227.96,NSW1NSW1 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14:00:00,18290.45,NSW1NSW1 +3015,2010-05-06 15:00:00,18097.73,NSW1NSW1 +3016,2010-05-06 16:00:00,18218.14,NSW1NSW1 +3017,2010-05-06 17:00:00,18652.29,NSW1NSW1 +3018,2010-05-06 18:00:00,20249.9,NSW1NSW1 +3019,2010-05-06 19:00:00,20284.7,NSW1NSW1 +3020,2010-05-06 20:00:00,19491.22,NSW1NSW1 +3021,2010-05-06 21:00:00,18874.440000000002,NSW1NSW1 +3022,2010-05-06 22:00:00,18105.53,NSW1NSW1 +3023,2010-05-06 23:00:00,17663.7,NSW1NSW1 +3024,2010-05-07 00:00:00,17031.61,NSW1NSW1 +3025,2010-05-07 01:00:00,16216.619999999999,NSW1NSW1 +3026,2010-05-07 02:00:00,15180.88,NSW1NSW1 +3027,2010-05-07 03:00:00,13917.0,NSW1NSW1 +3028,2010-05-07 04:00:00,13439.14,NSW1NSW1 +3029,2010-05-07 05:00:00,13853.490000000002,NSW1NSW1 +3030,2010-05-07 06:00:00,15661.150000000001,NSW1NSW1 +3031,2010-05-07 07:00:00,18294.9,NSW1NSW1 +3032,2010-05-07 08:00:00,19506.67,NSW1NSW1 +3033,2010-05-07 09:00:00,19461.690000000002,NSW1NSW1 +3034,2010-05-07 10:00:00,19378.65,NSW1NSW1 +3035,2010-05-07 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23:00:00,17039.0,NSW1NSW1 +3120,2010-05-11 00:00:00,16517.55,NSW1NSW1 +3121,2010-05-11 01:00:00,15711.990000000002,NSW1NSW1 +3122,2010-05-11 02:00:00,14691.72,NSW1NSW1 +3123,2010-05-11 03:00:00,13480.189999999999,NSW1NSW1 +3124,2010-05-11 04:00:00,13131.56,NSW1NSW1 +3125,2010-05-11 05:00:00,13433.560000000001,NSW1NSW1 +3126,2010-05-11 06:00:00,15296.16,NSW1NSW1 +3127,2010-05-11 07:00:00,17719.46,NSW1NSW1 +3128,2010-05-11 08:00:00,18769.31,NSW1NSW1 +3129,2010-05-11 09:00:00,18817.78,NSW1NSW1 +3130,2010-05-11 10:00:00,18898.9,NSW1NSW1 +3131,2010-05-11 11:00:00,18868.84,NSW1NSW1 +3132,2010-05-11 12:00:00,18773.05,NSW1NSW1 +3133,2010-05-11 13:00:00,18633.41,NSW1NSW1 +3134,2010-05-11 14:00:00,18670.57,NSW1NSW1 +3135,2010-05-11 15:00:00,18406.75,NSW1NSW1 +3136,2010-05-11 16:00:00,18454.0,NSW1NSW1 +3137,2010-05-11 17:00:00,19175.4,NSW1NSW1 +3138,2010-05-11 18:00:00,20537.79,NSW1NSW1 +3139,2010-05-11 19:00:00,19729.309999999998,NSW1NSW1 +3140,2010-05-11 20:00:00,18949.5,NSW1NSW1 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18:00:00,21481.239999999998,NSW1NSW1 +3163,2010-05-12 19:00:00,20935.9,NSW1NSW1 +3164,2010-05-12 20:00:00,20144.65,NSW1NSW1 +3165,2010-05-12 21:00:00,19364.12,NSW1NSW1 +3166,2010-05-12 22:00:00,18484.55,NSW1NSW1 +3167,2010-05-12 23:00:00,18091.940000000002,NSW1NSW1 +3168,2010-05-13 00:00:00,17427.33,NSW1NSW1 +3169,2010-05-13 01:00:00,16643.16,NSW1NSW1 +3170,2010-05-13 02:00:00,15558.439999999999,NSW1NSW1 +3171,2010-05-13 03:00:00,14302.72,NSW1NSW1 +3172,2010-05-13 04:00:00,13797.220000000001,NSW1NSW1 +3173,2010-05-13 05:00:00,14268.34,NSW1NSW1 +3174,2010-05-13 06:00:00,16442.22,NSW1NSW1 +3175,2010-05-13 07:00:00,19254.190000000002,NSW1NSW1 +3176,2010-05-13 08:00:00,20382.88,NSW1NSW1 +3177,2010-05-13 09:00:00,20091.73,NSW1NSW1 +3178,2010-05-13 10:00:00,19843.800000000003,NSW1NSW1 +3179,2010-05-13 11:00:00,19391.4,NSW1NSW1 +3180,2010-05-13 12:00:00,18791.4,NSW1NSW1 +3181,2010-05-13 13:00:00,18614.730000000003,NSW1NSW1 +3182,2010-05-13 14:00:00,18527.9,NSW1NSW1 +3183,2010-05-13 15:00:00,18322.559999999998,NSW1NSW1 +3184,2010-05-13 16:00:00,18455.08,NSW1NSW1 +3185,2010-05-13 17:00:00,19570.34,NSW1NSW1 +3186,2010-05-13 18:00:00,21427.940000000002,NSW1NSW1 +3187,2010-05-13 19:00:00,20912.059999999998,NSW1NSW1 +3188,2010-05-13 20:00:00,20230.49,NSW1NSW1 +3189,2010-05-13 21:00:00,19383.52,NSW1NSW1 +3190,2010-05-13 22:00:00,18503.41,NSW1NSW1 +3191,2010-05-13 23:00:00,18108.72,NSW1NSW1 +3192,2010-05-14 00:00:00,17412.45,NSW1NSW1 +3193,2010-05-14 01:00:00,16678.51,NSW1NSW1 +3194,2010-05-14 02:00:00,15599.27,NSW1NSW1 +3195,2010-05-14 03:00:00,14400.84,NSW1NSW1 +3196,2010-05-14 04:00:00,13995.7,NSW1NSW1 +3197,2010-05-14 05:00:00,14459.560000000001,NSW1NSW1 +3198,2010-05-14 06:00:00,16343.830000000002,NSW1NSW1 +3199,2010-05-14 07:00:00,19134.35,NSW1NSW1 +3200,2010-05-14 08:00:00,20326.800000000003,NSW1NSW1 +3201,2010-05-14 09:00:00,20130.1,NSW1NSW1 +3202,2010-05-14 10:00:00,19999.97,NSW1NSW1 +3203,2010-05-14 11:00:00,19502.11,NSW1NSW1 +3204,2010-05-14 12:00:00,18955.67,NSW1NSW1 +3205,2010-05-14 13:00:00,18781.83,NSW1NSW1 +3206,2010-05-14 14:00:00,18463.21,NSW1NSW1 +3207,2010-05-14 15:00:00,18296.97,NSW1NSW1 +3208,2010-05-14 16:00:00,18483.42,NSW1NSW1 +3209,2010-05-14 17:00:00,19479.14,NSW1NSW1 +3210,2010-05-14 18:00:00,20819.93,NSW1NSW1 +3211,2010-05-14 19:00:00,20198.52,NSW1NSW1 +3212,2010-05-14 20:00:00,19309.07,NSW1NSW1 +3213,2010-05-14 21:00:00,18744.85,NSW1NSW1 +3214,2010-05-14 22:00:00,18263.059999999998,NSW1NSW1 +3215,2010-05-14 23:00:00,18079.39,NSW1NSW1 +3216,2010-05-15 00:00:00,17526.39,NSW1NSW1 +3217,2010-05-15 01:00:00,16703.72,NSW1NSW1 +3218,2010-05-15 02:00:00,15603.07,NSW1NSW1 +3219,2010-05-15 03:00:00,14347.21,NSW1NSW1 +3220,2010-05-15 04:00:00,13692.7,NSW1NSW1 +3221,2010-05-15 05:00:00,13747.88,NSW1NSW1 +3222,2010-05-15 06:00:00,14691.17,NSW1NSW1 +3223,2010-05-15 07:00:00,16048.44,NSW1NSW1 +3224,2010-05-15 08:00:00,17710.93,NSW1NSW1 +3225,2010-05-15 09:00:00,18583.11,NSW1NSW1 +3226,2010-05-15 10:00:00,18395.510000000002,NSW1NSW1 +3227,2010-05-15 11:00:00,17930.239999999998,NSW1NSW1 +3228,2010-05-15 12:00:00,17440.879999999997,NSW1NSW1 +3229,2010-05-15 13:00:00,17143.2,NSW1NSW1 +3230,2010-05-15 14:00:00,16623.35,NSW1NSW1 +3231,2010-05-15 15:00:00,16581.230000000003,NSW1NSW1 +3232,2010-05-15 16:00:00,16882.769999999997,NSW1NSW1 +3233,2010-05-15 17:00:00,18002.910000000003,NSW1NSW1 +3234,2010-05-15 18:00:00,19446.239999999998,NSW1NSW1 +3235,2010-05-15 19:00:00,18895.52,NSW1NSW1 +3236,2010-05-15 20:00:00,18220.14,NSW1NSW1 +3237,2010-05-15 21:00:00,17741.510000000002,NSW1NSW1 +3238,2010-05-15 22:00:00,17268.489999999998,NSW1NSW1 +3239,2010-05-15 23:00:00,17090.64,NSW1NSW1 +3240,2010-05-16 00:00:00,16422.8,NSW1NSW1 +3241,2010-05-16 01:00:00,15553.71,NSW1NSW1 +3242,2010-05-16 02:00:00,14675.57,NSW1NSW1 +3243,2010-05-16 03:00:00,13597.41,NSW1NSW1 +3244,2010-05-16 04:00:00,13262.27,NSW1NSW1 +3245,2010-05-16 05:00:00,13338.11,NSW1NSW1 +3246,2010-05-16 06:00:00,13812.77,NSW1NSW1 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04:00:00,13494.970000000001,NSW1NSW1 +3269,2010-05-17 05:00:00,14065.91,NSW1NSW1 +3270,2010-05-17 06:00:00,15931.25,NSW1NSW1 +3271,2010-05-17 07:00:00,18526.39,NSW1NSW1 +3272,2010-05-17 08:00:00,19919.22,NSW1NSW1 +3273,2010-05-17 09:00:00,20171.559999999998,NSW1NSW1 +3274,2010-05-17 10:00:00,20265.91,NSW1NSW1 +3275,2010-05-17 11:00:00,20044.64,NSW1NSW1 +3276,2010-05-17 12:00:00,19652.73,NSW1NSW1 +3277,2010-05-17 13:00:00,19816.27,NSW1NSW1 +3278,2010-05-17 14:00:00,19666.489999999998,NSW1NSW1 +3279,2010-05-17 15:00:00,19482.72,NSW1NSW1 +3280,2010-05-17 16:00:00,19962.23,NSW1NSW1 +3281,2010-05-17 17:00:00,21395.23,NSW1NSW1 +3282,2010-05-17 18:00:00,22487.120000000003,NSW1NSW1 +3283,2010-05-17 19:00:00,21524.04,NSW1NSW1 +3284,2010-05-17 20:00:00,20388.300000000003,NSW1NSW1 +3285,2010-05-17 21:00:00,19375.23,NSW1NSW1 +3286,2010-05-17 22:00:00,18474.269999999997,NSW1NSW1 +3287,2010-05-17 23:00:00,17897.14,NSW1NSW1 +3288,2010-05-18 00:00:00,17279.33,NSW1NSW1 +3289,2010-05-18 01:00:00,16567.96,NSW1NSW1 +3290,2010-05-18 02:00:00,15542.509999999998,NSW1NSW1 +3291,2010-05-18 03:00:00,14333.619999999999,NSW1NSW1 +3292,2010-05-18 04:00:00,13896.49,NSW1NSW1 +3293,2010-05-18 05:00:00,14300.61,NSW1NSW1 +3294,2010-05-18 06:00:00,16229.57,NSW1NSW1 +3295,2010-05-18 07:00:00,18862.739999999998,NSW1NSW1 +3296,2010-05-18 08:00:00,20203.26,NSW1NSW1 +3297,2010-05-18 09:00:00,20336.71,NSW1NSW1 +3298,2010-05-18 10:00:00,20578.370000000003,NSW1NSW1 +3299,2010-05-18 11:00:00,20311.96,NSW1NSW1 +3300,2010-05-18 12:00:00,20059.71,NSW1NSW1 +3301,2010-05-18 13:00:00,19800.5,NSW1NSW1 +3302,2010-05-18 14:00:00,19707.16,NSW1NSW1 +3303,2010-05-18 15:00:00,19452.15,NSW1NSW1 +3304,2010-05-18 16:00:00,19915.75,NSW1NSW1 +3305,2010-05-18 17:00:00,21168.96,NSW1NSW1 +3306,2010-05-18 18:00:00,22517.9,NSW1NSW1 +3307,2010-05-18 19:00:00,21704.78,NSW1NSW1 +3308,2010-05-18 20:00:00,20833.1,NSW1NSW1 +3309,2010-05-18 21:00:00,19968.08,NSW1NSW1 +3310,2010-05-18 22:00:00,19058.1,NSW1NSW1 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18:00:00,21773.65,NSW1NSW1 +3355,2010-05-20 19:00:00,21248.620000000003,NSW1NSW1 +3356,2010-05-20 20:00:00,20590.92,NSW1NSW1 +3357,2010-05-20 21:00:00,19744.08,NSW1NSW1 +3358,2010-05-20 22:00:00,18804.18,NSW1NSW1 +3359,2010-05-20 23:00:00,18301.41,NSW1NSW1 +3360,2010-05-21 00:00:00,17580.38,NSW1NSW1 +3361,2010-05-21 01:00:00,16854.18,NSW1NSW1 +3362,2010-05-21 02:00:00,15741.21,NSW1NSW1 +3363,2010-05-21 03:00:00,14480.43,NSW1NSW1 +3364,2010-05-21 04:00:00,14032.73,NSW1NSW1 +3365,2010-05-21 05:00:00,14507.08,NSW1NSW1 +3366,2010-05-21 06:00:00,16420.75,NSW1NSW1 +3367,2010-05-21 07:00:00,19052.85,NSW1NSW1 +3368,2010-05-21 08:00:00,20089.75,NSW1NSW1 +3369,2010-05-21 09:00:00,20062.300000000003,NSW1NSW1 +3370,2010-05-21 10:00:00,19943.67,NSW1NSW1 +3371,2010-05-21 11:00:00,19632.0,NSW1NSW1 +3372,2010-05-21 12:00:00,19472.77,NSW1NSW1 +3373,2010-05-21 13:00:00,19177.620000000003,NSW1NSW1 +3374,2010-05-21 14:00:00,19051.61,NSW1NSW1 +3375,2010-05-21 15:00:00,18775.02,NSW1NSW1 +3376,2010-05-21 16:00:00,19094.68,NSW1NSW1 +3377,2010-05-21 17:00:00,20175.39,NSW1NSW1 +3378,2010-05-21 18:00:00,21216.28,NSW1NSW1 +3379,2010-05-21 19:00:00,20367.95,NSW1NSW1 +3380,2010-05-21 20:00:00,19683.54,NSW1NSW1 +3381,2010-05-21 21:00:00,18976.739999999998,NSW1NSW1 +3382,2010-05-21 22:00:00,18313.23,NSW1NSW1 +3383,2010-05-21 23:00:00,18213.82,NSW1NSW1 +3384,2010-05-22 00:00:00,17657.28,NSW1NSW1 +3385,2010-05-22 01:00:00,16787.6,NSW1NSW1 +3386,2010-05-22 02:00:00,15625.61,NSW1NSW1 +3387,2010-05-22 03:00:00,14279.43,NSW1NSW1 +3388,2010-05-22 04:00:00,13626.98,NSW1NSW1 +3389,2010-05-22 05:00:00,13695.42,NSW1NSW1 +3390,2010-05-22 06:00:00,14396.560000000001,NSW1NSW1 +3391,2010-05-22 07:00:00,15822.099999999999,NSW1NSW1 +3392,2010-05-22 08:00:00,17800.21,NSW1NSW1 +3393,2010-05-22 09:00:00,18952.54,NSW1NSW1 +3394,2010-05-22 10:00:00,19177.09,NSW1NSW1 +3395,2010-05-22 11:00:00,18649.29,NSW1NSW1 +3396,2010-05-22 12:00:00,18216.6,NSW1NSW1 +3397,2010-05-22 13:00:00,17781.239999999998,NSW1NSW1 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11:00:00,18602.940000000002,NSW1NSW1 +3420,2010-05-23 12:00:00,18295.260000000002,NSW1NSW1 +3421,2010-05-23 13:00:00,17960.54,NSW1NSW1 +3422,2010-05-23 14:00:00,17634.02,NSW1NSW1 +3423,2010-05-23 15:00:00,17596.07,NSW1NSW1 +3424,2010-05-23 16:00:00,18134.5,NSW1NSW1 +3425,2010-05-23 17:00:00,19676.91,NSW1NSW1 +3426,2010-05-23 18:00:00,21055.809999999998,NSW1NSW1 +3427,2010-05-23 19:00:00,20513.55,NSW1NSW1 +3428,2010-05-23 20:00:00,19850.29,NSW1NSW1 +3429,2010-05-23 21:00:00,19231.6,NSW1NSW1 +3430,2010-05-23 22:00:00,18288.23,NSW1NSW1 +3431,2010-05-23 23:00:00,17262.6,NSW1NSW1 +3432,2010-05-24 00:00:00,16331.67,NSW1NSW1 +3433,2010-05-24 01:00:00,15527.26,NSW1NSW1 +3434,2010-05-24 02:00:00,14696.05,NSW1NSW1 +3435,2010-05-24 03:00:00,13838.970000000001,NSW1NSW1 +3436,2010-05-24 04:00:00,13614.93,NSW1NSW1 +3437,2010-05-24 05:00:00,14190.9,NSW1NSW1 +3438,2010-05-24 06:00:00,16341.0,NSW1NSW1 +3439,2010-05-24 07:00:00,19310.57,NSW1NSW1 +3440,2010-05-24 08:00:00,20812.28,NSW1NSW1 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06:00:00,16199.73,NSW1NSW1 +3463,2010-05-25 07:00:00,18940.25,NSW1NSW1 +3464,2010-05-25 08:00:00,20045.86,NSW1NSW1 +3465,2010-05-25 09:00:00,20218.190000000002,NSW1NSW1 +3466,2010-05-25 10:00:00,20141.72,NSW1NSW1 +3467,2010-05-25 11:00:00,20228.489999999998,NSW1NSW1 +3468,2010-05-25 12:00:00,20110.23,NSW1NSW1 +3469,2010-05-25 13:00:00,20002.29,NSW1NSW1 +3470,2010-05-25 14:00:00,19675.01,NSW1NSW1 +3471,2010-05-25 15:00:00,19579.86,NSW1NSW1 +3472,2010-05-25 16:00:00,19836.41,NSW1NSW1 +3473,2010-05-25 17:00:00,21022.89,NSW1NSW1 +3474,2010-05-25 18:00:00,22321.190000000002,NSW1NSW1 +3475,2010-05-25 19:00:00,21519.39,NSW1NSW1 +3476,2010-05-25 20:00:00,20634.15,NSW1NSW1 +3477,2010-05-25 21:00:00,19703.13,NSW1NSW1 +3478,2010-05-25 22:00:00,18872.690000000002,NSW1NSW1 +3479,2010-05-25 23:00:00,18308.940000000002,NSW1NSW1 +3480,2010-05-26 00:00:00,17637.39,NSW1NSW1 +3481,2010-05-26 01:00:00,16786.379999999997,NSW1NSW1 +3482,2010-05-26 02:00:00,15591.75,NSW1NSW1 +3483,2010-05-26 03:00:00,14127.3,NSW1NSW1 +3484,2010-05-26 04:00:00,13654.27,NSW1NSW1 +3485,2010-05-26 05:00:00,14076.119999999999,NSW1NSW1 +3486,2010-05-26 06:00:00,15869.369999999999,NSW1NSW1 +3487,2010-05-26 07:00:00,18670.31,NSW1NSW1 +3488,2010-05-26 08:00:00,20043.68,NSW1NSW1 +3489,2010-05-26 09:00:00,20273.28,NSW1NSW1 +3490,2010-05-26 10:00:00,20449.58,NSW1NSW1 +3491,2010-05-26 11:00:00,20316.35,NSW1NSW1 +3492,2010-05-26 12:00:00,20230.53,NSW1NSW1 +3493,2010-05-26 13:00:00,20091.9,NSW1NSW1 +3494,2010-05-26 14:00:00,19993.04,NSW1NSW1 +3495,2010-05-26 15:00:00,20033.980000000003,NSW1NSW1 +3496,2010-05-26 16:00:00,20717.87,NSW1NSW1 +3497,2010-05-26 17:00:00,21877.510000000002,NSW1NSW1 +3498,2010-05-26 18:00:00,22794.12,NSW1NSW1 +3499,2010-05-26 19:00:00,21935.050000000003,NSW1NSW1 +3500,2010-05-26 20:00:00,20869.17,NSW1NSW1 +3501,2010-05-26 21:00:00,19871.16,NSW1NSW1 +3502,2010-05-26 22:00:00,18983.1,NSW1NSW1 +3503,2010-05-26 23:00:00,18332.9,NSW1NSW1 +3504,2010-05-27 00:00:00,17592.57,NSW1NSW1 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22:00:00,18898.54,NSW1NSW1 +3527,2010-05-27 23:00:00,18496.64,NSW1NSW1 +3528,2010-05-28 00:00:00,17705.9,NSW1NSW1 +3529,2010-05-28 01:00:00,16783.59,NSW1NSW1 +3530,2010-05-28 02:00:00,15673.82,NSW1NSW1 +3531,2010-05-28 03:00:00,14277.66,NSW1NSW1 +3532,2010-05-28 04:00:00,13749.919999999998,NSW1NSW1 +3533,2010-05-28 05:00:00,14195.55,NSW1NSW1 +3534,2010-05-28 06:00:00,16099.890000000001,NSW1NSW1 +3535,2010-05-28 07:00:00,18824.12,NSW1NSW1 +3536,2010-05-28 08:00:00,20175.77,NSW1NSW1 +3537,2010-05-28 09:00:00,20322.16,NSW1NSW1 +3538,2010-05-28 10:00:00,20179.9,NSW1NSW1 +3539,2010-05-28 11:00:00,19849.309999999998,NSW1NSW1 +3540,2010-05-28 12:00:00,19478.239999999998,NSW1NSW1 +3541,2010-05-28 13:00:00,19230.04,NSW1NSW1 +3542,2010-05-28 14:00:00,18984.83,NSW1NSW1 +3543,2010-05-28 15:00:00,18784.699999999997,NSW1NSW1 +3544,2010-05-28 16:00:00,18954.7,NSW1NSW1 +3545,2010-05-28 17:00:00,20058.3,NSW1NSW1 +3546,2010-05-28 18:00:00,21067.29,NSW1NSW1 +3547,2010-05-28 19:00:00,20237.15,NSW1NSW1 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11:00:00,20136.07,NSW1NSW1 +3612,2010-05-31 12:00:00,19989.04,NSW1NSW1 +3613,2010-05-31 13:00:00,19784.47,NSW1NSW1 +3614,2010-05-31 14:00:00,19562.15,NSW1NSW1 +3615,2010-05-31 15:00:00,19434.949999999997,NSW1NSW1 +3616,2010-05-31 16:00:00,19947.78,NSW1NSW1 +3617,2010-05-31 17:00:00,21518.65,NSW1NSW1 +3618,2010-05-31 18:00:00,22673.02,NSW1NSW1 +3619,2010-05-31 19:00:00,21875.47,NSW1NSW1 +3620,2010-05-31 20:00:00,20955.96,NSW1NSW1 +3621,2010-05-31 21:00:00,20110.58,NSW1NSW1 +3622,2010-05-31 22:00:00,18977.31,NSW1NSW1 +3623,2010-05-31 23:00:00,18392.839999999997,NSW1NSW1 +3624,2010-06-01 00:00:00,17632.239999999998,NSW1NSW1 +3625,2010-06-01 01:00:00,16823.440000000002,NSW1NSW1 +3626,2010-06-01 02:00:00,15757.32,NSW1NSW1 +3627,2010-06-01 03:00:00,14448.869999999999,NSW1NSW1 +3628,2010-06-01 04:00:00,14033.93,NSW1NSW1 +3629,2010-06-01 05:00:00,14418.43,NSW1NSW1 +3630,2010-06-01 06:00:00,16436.22,NSW1NSW1 +3631,2010-06-01 07:00:00,19306.11,NSW1NSW1 +3632,2010-06-01 08:00:00,20402.53,NSW1NSW1 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02:00:00,15756.67,NSW1NSW1 +3699,2010-06-04 03:00:00,14458.27,NSW1NSW1 +3700,2010-06-04 04:00:00,13911.7,NSW1NSW1 +3701,2010-06-04 05:00:00,14284.46,NSW1NSW1 +3702,2010-06-04 06:00:00,16098.060000000001,NSW1NSW1 +3703,2010-06-04 07:00:00,18656.17,NSW1NSW1 +3704,2010-06-04 08:00:00,20095.52,NSW1NSW1 +3705,2010-06-04 09:00:00,20211.57,NSW1NSW1 +3706,2010-06-04 10:00:00,20283.489999999998,NSW1NSW1 +3707,2010-06-04 11:00:00,20071.85,NSW1NSW1 +3708,2010-06-04 12:00:00,19712.65,NSW1NSW1 +3709,2010-06-04 13:00:00,19757.730000000003,NSW1NSW1 +3710,2010-06-04 14:00:00,19298.04,NSW1NSW1 +3711,2010-06-04 15:00:00,19731.17,NSW1NSW1 +3712,2010-06-04 16:00:00,20167.980000000003,NSW1NSW1 +3713,2010-06-04 17:00:00,21478.739999999998,NSW1NSW1 +3714,2010-06-04 18:00:00,22174.940000000002,NSW1NSW1 +3715,2010-06-04 19:00:00,21332.39,NSW1NSW1 +3716,2010-06-04 20:00:00,20402.7,NSW1NSW1 +3717,2010-06-04 21:00:00,19612.22,NSW1NSW1 +3718,2010-06-04 22:00:00,18908.300000000003,NSW1NSW1 +3719,2010-06-04 23:00:00,18741.38,NSW1NSW1 +3720,2010-06-05 00:00:00,18129.91,NSW1NSW1 +3721,2010-06-05 01:00:00,17133.809999999998,NSW1NSW1 +3722,2010-06-05 02:00:00,15905.86,NSW1NSW1 +3723,2010-06-05 03:00:00,14537.11,NSW1NSW1 +3724,2010-06-05 04:00:00,13877.279999999999,NSW1NSW1 +3725,2010-06-05 05:00:00,13867.61,NSW1NSW1 +3726,2010-06-05 06:00:00,14500.869999999999,NSW1NSW1 +3727,2010-06-05 07:00:00,15805.0,NSW1NSW1 +3728,2010-06-05 08:00:00,17712.64,NSW1NSW1 +3729,2010-06-05 09:00:00,18919.17,NSW1NSW1 +3730,2010-06-05 10:00:00,19158.82,NSW1NSW1 +3731,2010-06-05 11:00:00,18758.25,NSW1NSW1 +3732,2010-06-05 12:00:00,18046.57,NSW1NSW1 +3733,2010-06-05 13:00:00,17759.84,NSW1NSW1 +3734,2010-06-05 14:00:00,17360.31,NSW1NSW1 +3735,2010-06-05 15:00:00,17334.43,NSW1NSW1 +3736,2010-06-05 16:00:00,17750.16,NSW1NSW1 +3737,2010-06-05 17:00:00,19186.239999999998,NSW1NSW1 +3738,2010-06-05 18:00:00,20321.36,NSW1NSW1 +3739,2010-06-05 19:00:00,19541.68,NSW1NSW1 +3740,2010-06-05 20:00:00,18814.809999999998,NSW1NSW1 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17:00:00,20272.7,NSW1NSW1 +3762,2010-06-06 18:00:00,21672.96,NSW1NSW1 +3763,2010-06-06 19:00:00,21059.04,NSW1NSW1 +3764,2010-06-06 20:00:00,20277.89,NSW1NSW1 +3765,2010-06-06 21:00:00,19391.15,NSW1NSW1 +3766,2010-06-06 22:00:00,18279.79,NSW1NSW1 +3767,2010-06-06 23:00:00,17287.91,NSW1NSW1 +3768,2010-06-07 00:00:00,16398.29,NSW1NSW1 +3769,2010-06-07 01:00:00,15655.17,NSW1NSW1 +3770,2010-06-07 02:00:00,14888.849999999999,NSW1NSW1 +3771,2010-06-07 03:00:00,13999.22,NSW1NSW1 +3772,2010-06-07 04:00:00,13752.279999999999,NSW1NSW1 +3773,2010-06-07 05:00:00,14358.14,NSW1NSW1 +3774,2010-06-07 06:00:00,16534.34,NSW1NSW1 +3775,2010-06-07 07:00:00,19718.489999999998,NSW1NSW1 +3776,2010-06-07 08:00:00,21313.8,NSW1NSW1 +3777,2010-06-07 09:00:00,21139.879999999997,NSW1NSW1 +3778,2010-06-07 10:00:00,20836.6,NSW1NSW1 +3779,2010-06-07 11:00:00,20351.050000000003,NSW1NSW1 +3780,2010-06-07 12:00:00,19929.3,NSW1NSW1 +3781,2010-06-07 13:00:00,19988.07,NSW1NSW1 +3782,2010-06-07 14:00:00,19918.47,NSW1NSW1 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09:00:00,21362.46,NSW1NSW1 +3826,2010-06-09 10:00:00,21064.34,NSW1NSW1 +3827,2010-06-09 11:00:00,20653.14,NSW1NSW1 +3828,2010-06-09 12:00:00,20249.47,NSW1NSW1 +3829,2010-06-09 13:00:00,19929.28,NSW1NSW1 +3830,2010-06-09 14:00:00,19729.71,NSW1NSW1 +3831,2010-06-09 15:00:00,19721.629999999997,NSW1NSW1 +3832,2010-06-09 16:00:00,20665.85,NSW1NSW1 +3833,2010-06-09 17:00:00,22559.61,NSW1NSW1 +3834,2010-06-09 18:00:00,24117.35,NSW1NSW1 +3835,2010-06-09 19:00:00,23535.87,NSW1NSW1 +3836,2010-06-09 20:00:00,22734.66,NSW1NSW1 +3837,2010-06-09 21:00:00,21821.89,NSW1NSW1 +3838,2010-06-09 22:00:00,20470.550000000003,NSW1NSW1 +3839,2010-06-09 23:00:00,19311.449999999997,NSW1NSW1 +3840,2010-06-10 00:00:00,18353.239999999998,NSW1NSW1 +3841,2010-06-10 01:00:00,17384.64,NSW1NSW1 +3842,2010-06-10 02:00:00,16270.599999999999,NSW1NSW1 +3843,2010-06-10 03:00:00,14956.52,NSW1NSW1 +3844,2010-06-10 04:00:00,14419.6,NSW1NSW1 +3845,2010-06-10 05:00:00,14905.29,NSW1NSW1 +3846,2010-06-10 06:00:00,17185.89,NSW1NSW1 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02:00:00,17108.12,NSW1NSW1 +3891,2010-06-12 03:00:00,15535.72,NSW1NSW1 +3892,2010-06-12 04:00:00,14736.720000000001,NSW1NSW1 +3893,2010-06-12 05:00:00,14755.720000000001,NSW1NSW1 +3894,2010-06-12 06:00:00,15436.45,NSW1NSW1 +3895,2010-06-12 07:00:00,16988.010000000002,NSW1NSW1 +3896,2010-06-12 08:00:00,19415.47,NSW1NSW1 +3897,2010-06-12 09:00:00,20632.15,NSW1NSW1 +3898,2010-06-12 10:00:00,20307.8,NSW1NSW1 +3899,2010-06-12 11:00:00,19460.59,NSW1NSW1 +3900,2010-06-12 12:00:00,18702.769999999997,NSW1NSW1 +3901,2010-06-12 13:00:00,18131.809999999998,NSW1NSW1 +3902,2010-06-12 14:00:00,17832.82,NSW1NSW1 +3903,2010-06-12 15:00:00,17801.96,NSW1NSW1 +3904,2010-06-12 16:00:00,18591.88,NSW1NSW1 +3905,2010-06-12 17:00:00,20744.05,NSW1NSW1 +3906,2010-06-12 18:00:00,22560.82,NSW1NSW1 +3907,2010-06-12 19:00:00,21874.16,NSW1NSW1 +3908,2010-06-12 20:00:00,21108.519999999997,NSW1NSW1 +3909,2010-06-12 21:00:00,20565.0,NSW1NSW1 +3910,2010-06-12 22:00:00,19835.440000000002,NSW1NSW1 +3911,2010-06-12 23:00:00,19295.37,NSW1NSW1 +3912,2010-06-13 00:00:00,18309.989999999998,NSW1NSW1 +3913,2010-06-13 01:00:00,17307.89,NSW1NSW1 +3914,2010-06-13 02:00:00,16083.599999999999,NSW1NSW1 +3915,2010-06-13 03:00:00,14878.82,NSW1NSW1 +3916,2010-06-13 04:00:00,14338.400000000001,NSW1NSW1 +3917,2010-06-13 05:00:00,14449.25,NSW1NSW1 +3918,2010-06-13 06:00:00,14984.03,NSW1NSW1 +3919,2010-06-13 07:00:00,16069.02,NSW1NSW1 +3920,2010-06-13 08:00:00,18122.58,NSW1NSW1 +3921,2010-06-13 09:00:00,19722.84,NSW1NSW1 +3922,2010-06-13 10:00:00,19866.03,NSW1NSW1 +3923,2010-06-13 11:00:00,19162.809999999998,NSW1NSW1 +3924,2010-06-13 12:00:00,18335.85,NSW1NSW1 +3925,2010-06-13 13:00:00,17830.59,NSW1NSW1 +3926,2010-06-13 14:00:00,17417.44,NSW1NSW1 +3927,2010-06-13 15:00:00,17330.11,NSW1NSW1 +3928,2010-06-13 16:00:00,18009.16,NSW1NSW1 +3929,2010-06-13 17:00:00,20113.85,NSW1NSW1 +3930,2010-06-13 18:00:00,21920.43,NSW1NSW1 +3931,2010-06-13 19:00:00,21486.21,NSW1NSW1 +3932,2010-06-13 20:00:00,20881.63,NSW1NSW1 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15:00:00,19524.46,NSW1NSW1 +3976,2010-06-15 16:00:00,20003.43,NSW1NSW1 +3977,2010-06-15 17:00:00,22108.440000000002,NSW1NSW1 +3978,2010-06-15 18:00:00,24139.48,NSW1NSW1 +3979,2010-06-15 19:00:00,23770.82,NSW1NSW1 +3980,2010-06-15 20:00:00,22956.77,NSW1NSW1 +3981,2010-06-15 21:00:00,21944.989999999998,NSW1NSW1 +3982,2010-06-15 22:00:00,20807.370000000003,NSW1NSW1 +3983,2010-06-15 23:00:00,19690.59,NSW1NSW1 +3984,2010-06-16 00:00:00,18835.41,NSW1NSW1 +3985,2010-06-16 01:00:00,17903.3,NSW1NSW1 +3986,2010-06-16 02:00:00,16760.73,NSW1NSW1 +3987,2010-06-16 03:00:00,15354.07,NSW1NSW1 +3988,2010-06-16 04:00:00,14636.26,NSW1NSW1 +3989,2010-06-16 05:00:00,15061.12,NSW1NSW1 +3990,2010-06-16 06:00:00,17307.88,NSW1NSW1 +3991,2010-06-16 07:00:00,20713.18,NSW1NSW1 +3992,2010-06-16 08:00:00,22075.54,NSW1NSW1 +3993,2010-06-16 09:00:00,21567.940000000002,NSW1NSW1 +3994,2010-06-16 10:00:00,21176.54,NSW1NSW1 +3995,2010-06-16 11:00:00,20507.489999999998,NSW1NSW1 +3996,2010-06-16 12:00:00,19903.42,NSW1NSW1 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09:00:00,21397.800000000003,NSW1NSW1 +4018,2010-06-17 10:00:00,21474.690000000002,NSW1NSW1 +4019,2010-06-17 11:00:00,21187.379999999997,NSW1NSW1 +4020,2010-06-17 12:00:00,20940.42,NSW1NSW1 +4021,2010-06-17 13:00:00,20768.739999999998,NSW1NSW1 +4022,2010-06-17 14:00:00,20575.309999999998,NSW1NSW1 +4023,2010-06-17 15:00:00,20161.010000000002,NSW1NSW1 +4024,2010-06-17 16:00:00,20467.06,NSW1NSW1 +4025,2010-06-17 17:00:00,22020.4,NSW1NSW1 +4026,2010-06-17 18:00:00,23651.02,NSW1NSW1 +4027,2010-06-17 19:00:00,23413.58,NSW1NSW1 +4028,2010-06-17 20:00:00,22566.53,NSW1NSW1 +4029,2010-06-17 21:00:00,21555.47,NSW1NSW1 +4030,2010-06-17 22:00:00,20303.120000000003,NSW1NSW1 +4031,2010-06-17 23:00:00,19401.75,NSW1NSW1 +4032,2010-06-18 00:00:00,18436.75,NSW1NSW1 +4033,2010-06-18 01:00:00,17488.41,NSW1NSW1 +4034,2010-06-18 02:00:00,16368.59,NSW1NSW1 +4035,2010-06-18 03:00:00,14966.82,NSW1NSW1 +4036,2010-06-18 04:00:00,14419.42,NSW1NSW1 +4037,2010-06-18 05:00:00,14950.52,NSW1NSW1 +4038,2010-06-18 06:00:00,17086.8,NSW1NSW1 +4039,2010-06-18 07:00:00,20344.68,NSW1NSW1 +4040,2010-06-18 08:00:00,21775.86,NSW1NSW1 +4041,2010-06-18 09:00:00,21331.97,NSW1NSW1 +4042,2010-06-18 10:00:00,20925.059999999998,NSW1NSW1 +4043,2010-06-18 11:00:00,20292.809999999998,NSW1NSW1 +4044,2010-06-18 12:00:00,19688.54,NSW1NSW1 +4045,2010-06-18 13:00:00,19332.949999999997,NSW1NSW1 +4046,2010-06-18 14:00:00,19079.41,NSW1NSW1 +4047,2010-06-18 15:00:00,18616.54,NSW1NSW1 +4048,2010-06-18 16:00:00,19265.269999999997,NSW1NSW1 +4049,2010-06-18 17:00:00,21226.66,NSW1NSW1 +4050,2010-06-18 18:00:00,22995.67,NSW1NSW1 +4051,2010-06-18 19:00:00,22559.769999999997,NSW1NSW1 +4052,2010-06-18 20:00:00,21892.269999999997,NSW1NSW1 +4053,2010-06-18 21:00:00,21197.019999999997,NSW1NSW1 +4054,2010-06-18 22:00:00,20340.940000000002,NSW1NSW1 +4055,2010-06-18 23:00:00,19955.940000000002,NSW1NSW1 +4056,2010-06-19 00:00:00,18925.190000000002,NSW1NSW1 +4057,2010-06-19 01:00:00,17884.05,NSW1NSW1 +4058,2010-06-19 02:00:00,16514.670000000002,NSW1NSW1 +4059,2010-06-19 03:00:00,15058.76,NSW1NSW1 +4060,2010-06-19 04:00:00,14245.619999999999,NSW1NSW1 +4061,2010-06-19 05:00:00,14239.369999999999,NSW1NSW1 +4062,2010-06-19 06:00:00,15064.14,NSW1NSW1 +4063,2010-06-19 07:00:00,16565.46,NSW1NSW1 +4064,2010-06-19 08:00:00,18881.75,NSW1NSW1 +4065,2010-06-19 09:00:00,20140.989999999998,NSW1NSW1 +4066,2010-06-19 10:00:00,20016.440000000002,NSW1NSW1 +4067,2010-06-19 11:00:00,19253.02,NSW1NSW1 +4068,2010-06-19 12:00:00,18425.63,NSW1NSW1 +4069,2010-06-19 13:00:00,17853.71,NSW1NSW1 +4070,2010-06-19 14:00:00,17454.72,NSW1NSW1 +4071,2010-06-19 15:00:00,17349.64,NSW1NSW1 +4072,2010-06-19 16:00:00,18026.84,NSW1NSW1 +4073,2010-06-19 17:00:00,19948.95,NSW1NSW1 +4074,2010-06-19 18:00:00,21695.66,NSW1NSW1 +4075,2010-06-19 19:00:00,21074.2,NSW1NSW1 +4076,2010-06-19 20:00:00,20346.98,NSW1NSW1 +4077,2010-06-19 21:00:00,19607.559999999998,NSW1NSW1 +4078,2010-06-19 22:00:00,18949.22,NSW1NSW1 +4079,2010-06-19 23:00:00,18636.2,NSW1NSW1 +4080,2010-06-20 00:00:00,17910.690000000002,NSW1NSW1 +4081,2010-06-20 01:00:00,16965.96,NSW1NSW1 +4082,2010-06-20 02:00:00,15702.919999999998,NSW1NSW1 +4083,2010-06-20 03:00:00,14306.59,NSW1NSW1 +4084,2010-06-20 04:00:00,13684.5,NSW1NSW1 +4085,2010-06-20 05:00:00,13693.83,NSW1NSW1 +4086,2010-06-20 06:00:00,14262.2,NSW1NSW1 +4087,2010-06-20 07:00:00,15357.599999999999,NSW1NSW1 +4088,2010-06-20 08:00:00,17307.53,NSW1NSW1 +4089,2010-06-20 09:00:00,18678.309999999998,NSW1NSW1 +4090,2010-06-20 10:00:00,18942.440000000002,NSW1NSW1 +4091,2010-06-20 11:00:00,18389.519999999997,NSW1NSW1 +4092,2010-06-20 12:00:00,17827.28,NSW1NSW1 +4093,2010-06-20 13:00:00,17281.370000000003,NSW1NSW1 +4094,2010-06-20 14:00:00,16912.18,NSW1NSW1 +4095,2010-06-20 15:00:00,16757.95,NSW1NSW1 +4096,2010-06-20 16:00:00,17359.86,NSW1NSW1 +4097,2010-06-20 17:00:00,19529.39,NSW1NSW1 +4098,2010-06-20 18:00:00,21632.79,NSW1NSW1 +4099,2010-06-20 19:00:00,21446.68,NSW1NSW1 +4100,2010-06-20 20:00:00,20907.14,NSW1NSW1 +4101,2010-06-20 21:00:00,20180.08,NSW1NSW1 +4102,2010-06-20 22:00:00,19124.39,NSW1NSW1 +4103,2010-06-20 23:00:00,17996.58,NSW1NSW1 +4104,2010-06-21 00:00:00,16991.41,NSW1NSW1 +4105,2010-06-21 01:00:00,16155.45,NSW1NSW1 +4106,2010-06-21 02:00:00,15327.43,NSW1NSW1 +4107,2010-06-21 03:00:00,14460.66,NSW1NSW1 +4108,2010-06-21 04:00:00,14170.36,NSW1NSW1 +4109,2010-06-21 05:00:00,14785.3,NSW1NSW1 +4110,2010-06-21 06:00:00,17060.04,NSW1NSW1 +4111,2010-06-21 07:00:00,20344.33,NSW1NSW1 +4112,2010-06-21 08:00:00,21877.41,NSW1NSW1 +4113,2010-06-21 09:00:00,21674.519999999997,NSW1NSW1 +4114,2010-06-21 10:00:00,21453.739999999998,NSW1NSW1 +4115,2010-06-21 11:00:00,21042.66,NSW1NSW1 +4116,2010-06-21 12:00:00,20677.089999999997,NSW1NSW1 +4117,2010-06-21 13:00:00,20460.41,NSW1NSW1 +4118,2010-06-21 14:00:00,20274.410000000003,NSW1NSW1 +4119,2010-06-21 15:00:00,19991.02,NSW1NSW1 +4120,2010-06-21 16:00:00,20405.83,NSW1NSW1 +4121,2010-06-21 17:00:00,22363.9,NSW1NSW1 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15:00:00,19904.09,NSW1NSW1 +4144,2010-06-22 16:00:00,20492.440000000002,NSW1NSW1 +4145,2010-06-22 17:00:00,22414.54,NSW1NSW1 +4146,2010-06-22 18:00:00,23856.42,NSW1NSW1 +4147,2010-06-22 19:00:00,23081.57,NSW1NSW1 +4148,2010-06-22 20:00:00,22137.6,NSW1NSW1 +4149,2010-06-22 21:00:00,21173.010000000002,NSW1NSW1 +4150,2010-06-22 22:00:00,19973.21,NSW1NSW1 +4151,2010-06-22 23:00:00,19311.36,NSW1NSW1 +4152,2010-06-23 00:00:00,18374.03,NSW1NSW1 +4153,2010-06-23 01:00:00,17573.66,NSW1NSW1 +4154,2010-06-23 02:00:00,16390.64,NSW1NSW1 +4155,2010-06-23 03:00:00,14956.36,NSW1NSW1 +4156,2010-06-23 04:00:00,14280.220000000001,NSW1NSW1 +4157,2010-06-23 05:00:00,14701.46,NSW1NSW1 +4158,2010-06-23 06:00:00,16796.239999999998,NSW1NSW1 +4159,2010-06-23 07:00:00,19875.47,NSW1NSW1 +4160,2010-06-23 08:00:00,21165.61,NSW1NSW1 +4161,2010-06-23 09:00:00,21058.67,NSW1NSW1 +4162,2010-06-23 10:00:00,20838.9,NSW1NSW1 +4163,2010-06-23 11:00:00,20621.620000000003,NSW1NSW1 +4164,2010-06-23 12:00:00,20315.08,NSW1NSW1 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11:00:00,20094.36,NSW1NSW1 +4188,2010-06-24 12:00:00,19443.16,NSW1NSW1 +4189,2010-06-24 13:00:00,19461.39,NSW1NSW1 +4190,2010-06-24 14:00:00,19235.3,NSW1NSW1 +4191,2010-06-24 15:00:00,19047.17,NSW1NSW1 +4192,2010-06-24 16:00:00,19370.120000000003,NSW1NSW1 +4193,2010-06-24 17:00:00,20906.730000000003,NSW1NSW1 +4194,2010-06-24 18:00:00,22708.2,NSW1NSW1 +4195,2010-06-24 19:00:00,22350.269999999997,NSW1NSW1 +4196,2010-06-24 20:00:00,21751.87,NSW1NSW1 +4197,2010-06-24 21:00:00,20935.59,NSW1NSW1 +4198,2010-06-24 22:00:00,19796.34,NSW1NSW1 +4199,2010-06-24 23:00:00,18980.39,NSW1NSW1 +4200,2010-06-25 00:00:00,18246.809999999998,NSW1NSW1 +4201,2010-06-25 01:00:00,17315.29,NSW1NSW1 +4202,2010-06-25 02:00:00,16204.3,NSW1NSW1 +4203,2010-06-25 03:00:00,14800.14,NSW1NSW1 +4204,2010-06-25 04:00:00,14258.41,NSW1NSW1 +4205,2010-06-25 05:00:00,14738.17,NSW1NSW1 +4206,2010-06-25 06:00:00,16635.55,NSW1NSW1 +4207,2010-06-25 07:00:00,19435.57,NSW1NSW1 +4208,2010-06-25 08:00:00,20953.690000000002,NSW1NSW1 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06:00:00,14323.18,NSW1NSW1 +4231,2010-06-26 07:00:00,15558.939999999999,NSW1NSW1 +4232,2010-06-26 08:00:00,17438.18,NSW1NSW1 +4233,2010-06-26 09:00:00,18978.68,NSW1NSW1 +4234,2010-06-26 10:00:00,19294.4,NSW1NSW1 +4235,2010-06-26 11:00:00,19127.31,NSW1NSW1 +4236,2010-06-26 12:00:00,18751.29,NSW1NSW1 +4237,2010-06-26 13:00:00,18172.53,NSW1NSW1 +4238,2010-06-26 14:00:00,17627.36,NSW1NSW1 +4239,2010-06-26 15:00:00,17406.92,NSW1NSW1 +4240,2010-06-26 16:00:00,17851.75,NSW1NSW1 +4241,2010-06-26 17:00:00,19434.83,NSW1NSW1 +4242,2010-06-26 18:00:00,21153.0,NSW1NSW1 +4243,2010-06-26 19:00:00,20547.550000000003,NSW1NSW1 +4244,2010-06-26 20:00:00,19789.41,NSW1NSW1 +4245,2010-06-26 21:00:00,19319.82,NSW1NSW1 +4246,2010-06-26 22:00:00,18889.28,NSW1NSW1 +4247,2010-06-26 23:00:00,18553.42,NSW1NSW1 +4248,2010-06-27 00:00:00,17635.690000000002,NSW1NSW1 +4249,2010-06-27 01:00:00,16395.17,NSW1NSW1 +4250,2010-06-27 02:00:00,15523.52,NSW1NSW1 +4251,2010-06-27 03:00:00,14507.07,NSW1NSW1 +4252,2010-06-27 04:00:00,14027.880000000001,NSW1NSW1 +4253,2010-06-27 05:00:00,14098.32,NSW1NSW1 +4254,2010-06-27 06:00:00,14621.96,NSW1NSW1 +4255,2010-06-27 07:00:00,15725.02,NSW1NSW1 +4256,2010-06-27 08:00:00,17866.78,NSW1NSW1 +4257,2010-06-27 09:00:00,19487.7,NSW1NSW1 +4258,2010-06-27 10:00:00,19714.17,NSW1NSW1 +4259,2010-06-27 11:00:00,19101.989999999998,NSW1NSW1 +4260,2010-06-27 12:00:00,18440.53,NSW1NSW1 +4261,2010-06-27 13:00:00,18099.64,NSW1NSW1 +4262,2010-06-27 14:00:00,17883.010000000002,NSW1NSW1 +4263,2010-06-27 15:00:00,18012.08,NSW1NSW1 +4264,2010-06-27 16:00:00,18810.88,NSW1NSW1 +4265,2010-06-27 17:00:00,20989.57,NSW1NSW1 +4266,2010-06-27 18:00:00,23063.010000000002,NSW1NSW1 +4267,2010-06-27 19:00:00,22791.16,NSW1NSW1 +4268,2010-06-27 20:00:00,21987.46,NSW1NSW1 +4269,2010-06-27 21:00:00,21178.480000000003,NSW1NSW1 +4270,2010-06-27 22:00:00,19969.37,NSW1NSW1 +4271,2010-06-27 23:00:00,18876.699999999997,NSW1NSW1 +4272,2010-06-28 00:00:00,17675.97,NSW1NSW1 +4273,2010-06-28 01:00:00,16716.61,NSW1NSW1 +4274,2010-06-28 02:00:00,15831.63,NSW1NSW1 +4275,2010-06-28 03:00:00,14743.76,NSW1NSW1 +4276,2010-06-28 04:00:00,14476.29,NSW1NSW1 +4277,2010-06-28 05:00:00,15237.509999999998,NSW1NSW1 +4278,2010-06-28 06:00:00,17662.53,NSW1NSW1 +4279,2010-06-28 07:00:00,20983.22,NSW1NSW1 +4280,2010-06-28 08:00:00,22951.82,NSW1NSW1 +4281,2010-06-28 09:00:00,22980.5,NSW1NSW1 +4282,2010-06-28 10:00:00,22543.67,NSW1NSW1 +4283,2010-06-28 11:00:00,21881.15,NSW1NSW1 +4284,2010-06-28 12:00:00,21221.42,NSW1NSW1 +4285,2010-06-28 13:00:00,20650.760000000002,NSW1NSW1 +4286,2010-06-28 14:00:00,20277.23,NSW1NSW1 +4287,2010-06-28 15:00:00,20006.93,NSW1NSW1 +4288,2010-06-28 16:00:00,20586.96,NSW1NSW1 +4289,2010-06-28 17:00:00,23128.35,NSW1NSW1 +4290,2010-06-28 18:00:00,25623.34,NSW1NSW1 +4291,2010-06-28 19:00:00,25156.89,NSW1NSW1 +4292,2010-06-28 20:00:00,24196.82,NSW1NSW1 +4293,2010-06-28 21:00:00,23074.76,NSW1NSW1 +4294,2010-06-28 22:00:00,21628.33,NSW1NSW1 +4295,2010-06-28 23:00:00,20372.4,NSW1NSW1 +4296,2010-06-29 00:00:00,19287.27,NSW1NSW1 +4297,2010-06-29 01:00:00,18427.02,NSW1NSW1 +4298,2010-06-29 02:00:00,17288.25,NSW1NSW1 +4299,2010-06-29 03:00:00,15890.63,NSW1NSW1 +4300,2010-06-29 04:00:00,15268.349999999999,NSW1NSW1 +4301,2010-06-29 05:00:00,15835.119999999999,NSW1NSW1 +4302,2010-06-29 06:00:00,18274.4,NSW1NSW1 +4303,2010-06-29 07:00:00,21788.83,NSW1NSW1 +4304,2010-06-29 08:00:00,23717.89,NSW1NSW1 +4305,2010-06-29 09:00:00,23421.67,NSW1NSW1 +4306,2010-06-29 10:00:00,22965.05,NSW1NSW1 +4307,2010-06-29 11:00:00,22369.82,NSW1NSW1 +4308,2010-06-29 12:00:00,21612.870000000003,NSW1NSW1 +4309,2010-06-29 13:00:00,21125.68,NSW1NSW1 +4310,2010-06-29 14:00:00,20678.06,NSW1NSW1 +4311,2010-06-29 15:00:00,20360.27,NSW1NSW1 +4312,2010-06-29 16:00:00,21079.61,NSW1NSW1 +4313,2010-06-29 17:00:00,23616.43,NSW1NSW1 +4314,2010-06-29 18:00:00,26199.17,NSW1NSW1 +4315,2010-06-29 19:00:00,26027.190000000002,NSW1NSW1 +4316,2010-06-29 20:00:00,25073.8,NSW1NSW1 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18:00:00,25927.45,NSW1NSW1 +4339,2010-06-30 19:00:00,25565.4,NSW1NSW1 +4340,2010-06-30 20:00:00,24606.33,NSW1NSW1 +4341,2010-06-30 21:00:00,23684.23,NSW1NSW1 +4342,2010-06-30 22:00:00,22185.07,NSW1NSW1 +4343,2010-06-30 23:00:00,20796.5,NSW1NSW1 +4344,2010-07-01 00:00:00,19701.96,NSW1NSW1 +4345,2010-07-01 01:00:00,18755.18,NSW1NSW1 +4346,2010-07-01 02:00:00,17637.68,NSW1NSW1 +4347,2010-07-01 03:00:00,16174.84,NSW1NSW1 +4348,2010-07-01 04:00:00,15599.130000000001,NSW1NSW1 +4349,2010-07-01 05:00:00,16083.669999999998,NSW1NSW1 +4350,2010-07-01 06:00:00,18421.980000000003,NSW1NSW1 +4351,2010-07-01 07:00:00,21969.98,NSW1NSW1 +4352,2010-07-01 08:00:00,23700.739999999998,NSW1NSW1 +4353,2010-07-01 09:00:00,23427.9,NSW1NSW1 +4354,2010-07-01 10:00:00,22924.72,NSW1NSW1 +4355,2010-07-01 11:00:00,22091.29,NSW1NSW1 +4356,2010-07-01 12:00:00,21069.379999999997,NSW1NSW1 +4357,2010-07-01 13:00:00,20480.6,NSW1NSW1 +4358,2010-07-01 14:00:00,20129.75,NSW1NSW1 +4359,2010-07-01 15:00:00,20058.739999999998,NSW1NSW1 +4360,2010-07-01 16:00:00,20803.11,NSW1NSW1 +4361,2010-07-01 17:00:00,22995.14,NSW1NSW1 +4362,2010-07-01 18:00:00,25419.02,NSW1NSW1 +4363,2010-07-01 19:00:00,25117.84,NSW1NSW1 +4364,2010-07-01 20:00:00,24418.989999999998,NSW1NSW1 +4365,2010-07-01 21:00:00,23541.34,NSW1NSW1 +4366,2010-07-01 22:00:00,22140.15,NSW1NSW1 +4367,2010-07-01 23:00:00,20900.34,NSW1NSW1 +4368,2010-07-02 00:00:00,19721.8,NSW1NSW1 +4369,2010-07-02 01:00:00,18769.010000000002,NSW1NSW1 +4370,2010-07-02 02:00:00,17577.79,NSW1NSW1 +4371,2010-07-02 03:00:00,16104.51,NSW1NSW1 +4372,2010-07-02 04:00:00,15487.970000000001,NSW1NSW1 +4373,2010-07-02 05:00:00,15870.56,NSW1NSW1 +4374,2010-07-02 06:00:00,18141.449999999997,NSW1NSW1 +4375,2010-07-02 07:00:00,21497.65,NSW1NSW1 +4376,2010-07-02 08:00:00,23536.75,NSW1NSW1 +4377,2010-07-02 09:00:00,23690.15,NSW1NSW1 +4378,2010-07-02 10:00:00,23605.09,NSW1NSW1 +4379,2010-07-02 11:00:00,23216.84,NSW1NSW1 +4380,2010-07-02 12:00:00,22686.61,NSW1NSW1 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08:00:00,18465.760000000002,NSW1NSW1 +4425,2010-07-04 09:00:00,20125.16,NSW1NSW1 +4426,2010-07-04 10:00:00,20222.66,NSW1NSW1 +4427,2010-07-04 11:00:00,19593.22,NSW1NSW1 +4428,2010-07-04 12:00:00,18848.86,NSW1NSW1 +4429,2010-07-04 13:00:00,18271.93,NSW1NSW1 +4430,2010-07-04 14:00:00,17742.43,NSW1NSW1 +4431,2010-07-04 15:00:00,17531.2,NSW1NSW1 +4432,2010-07-04 16:00:00,18232.88,NSW1NSW1 +4433,2010-07-04 17:00:00,20465.67,NSW1NSW1 +4434,2010-07-04 18:00:00,22683.09,NSW1NSW1 +4435,2010-07-04 19:00:00,22398.519999999997,NSW1NSW1 +4436,2010-07-04 20:00:00,21779.78,NSW1NSW1 +4437,2010-07-04 21:00:00,20957.79,NSW1NSW1 +4438,2010-07-04 22:00:00,19770.5,NSW1NSW1 +4439,2010-07-04 23:00:00,18680.77,NSW1NSW1 +4440,2010-07-05 00:00:00,17557.0,NSW1NSW1 +4441,2010-07-05 01:00:00,16643.21,NSW1NSW1 +4442,2010-07-05 02:00:00,15621.279999999999,NSW1NSW1 +4443,2010-07-05 03:00:00,14780.54,NSW1NSW1 +4444,2010-07-05 04:00:00,14467.73,NSW1NSW1 +4445,2010-07-05 05:00:00,15060.599999999999,NSW1NSW1 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04:00:00,14845.55,NSW1NSW1 +4469,2010-07-06 05:00:00,15235.67,NSW1NSW1 +4470,2010-07-06 06:00:00,17139.8,NSW1NSW1 +4471,2010-07-06 07:00:00,19702.940000000002,NSW1NSW1 +4472,2010-07-06 08:00:00,21331.81,NSW1NSW1 +4473,2010-07-06 09:00:00,21945.989999999998,NSW1NSW1 +4474,2010-07-06 10:00:00,22033.29,NSW1NSW1 +4475,2010-07-06 11:00:00,21548.42,NSW1NSW1 +4476,2010-07-06 12:00:00,20914.55,NSW1NSW1 +4477,2010-07-06 13:00:00,20432.5,NSW1NSW1 +4478,2010-07-06 14:00:00,20156.03,NSW1NSW1 +4479,2010-07-06 15:00:00,20332.39,NSW1NSW1 +4480,2010-07-06 16:00:00,21029.91,NSW1NSW1 +4481,2010-07-06 17:00:00,22757.32,NSW1NSW1 +4482,2010-07-06 18:00:00,24353.3,NSW1NSW1 +4483,2010-07-06 19:00:00,23741.92,NSW1NSW1 +4484,2010-07-06 20:00:00,23011.17,NSW1NSW1 +4485,2010-07-06 21:00:00,22017.760000000002,NSW1NSW1 +4486,2010-07-06 22:00:00,20817.57,NSW1NSW1 +4487,2010-07-06 23:00:00,19806.989999999998,NSW1NSW1 +4488,2010-07-07 00:00:00,18805.64,NSW1NSW1 +4489,2010-07-07 01:00:00,18019.36,NSW1NSW1 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23:00:00,20324.239999999998,NSW1NSW1 +4512,2010-07-08 00:00:00,19386.4,NSW1NSW1 +4513,2010-07-08 01:00:00,18422.17,NSW1NSW1 +4514,2010-07-08 02:00:00,17274.71,NSW1NSW1 +4515,2010-07-08 03:00:00,15788.01,NSW1NSW1 +4516,2010-07-08 04:00:00,15143.4,NSW1NSW1 +4517,2010-07-08 05:00:00,15725.25,NSW1NSW1 +4518,2010-07-08 06:00:00,17724.59,NSW1NSW1 +4519,2010-07-08 07:00:00,20282.58,NSW1NSW1 +4520,2010-07-08 08:00:00,21770.62,NSW1NSW1 +4521,2010-07-08 09:00:00,22066.0,NSW1NSW1 +4522,2010-07-08 10:00:00,21821.0,NSW1NSW1 +4523,2010-07-08 11:00:00,21460.12,NSW1NSW1 +4524,2010-07-08 12:00:00,20976.8,NSW1NSW1 +4525,2010-07-08 13:00:00,20719.510000000002,NSW1NSW1 +4526,2010-07-08 14:00:00,20506.44,NSW1NSW1 +4527,2010-07-08 15:00:00,20535.09,NSW1NSW1 +4528,2010-07-08 16:00:00,20969.88,NSW1NSW1 +4529,2010-07-08 17:00:00,22472.510000000002,NSW1NSW1 +4530,2010-07-08 18:00:00,24282.04,NSW1NSW1 +4531,2010-07-08 19:00:00,23848.29,NSW1NSW1 +4532,2010-07-08 20:00:00,23094.64,NSW1NSW1 +4533,2010-07-08 21:00:00,22105.239999999998,NSW1NSW1 +4534,2010-07-08 22:00:00,20876.37,NSW1NSW1 +4535,2010-07-08 23:00:00,20035.949999999997,NSW1NSW1 +4536,2010-07-09 00:00:00,19058.21,NSW1NSW1 +4537,2010-07-09 01:00:00,18059.33,NSW1NSW1 +4538,2010-07-09 02:00:00,16945.05,NSW1NSW1 +4539,2010-07-09 03:00:00,15520.52,NSW1NSW1 +4540,2010-07-09 04:00:00,14950.86,NSW1NSW1 +4541,2010-07-09 05:00:00,15357.04,NSW1NSW1 +4542,2010-07-09 06:00:00,17263.239999999998,NSW1NSW1 +4543,2010-07-09 07:00:00,19779.1,NSW1NSW1 +4544,2010-07-09 08:00:00,21509.08,NSW1NSW1 +4545,2010-07-09 09:00:00,22149.35,NSW1NSW1 +4546,2010-07-09 10:00:00,21987.23,NSW1NSW1 +4547,2010-07-09 11:00:00,21307.1,NSW1NSW1 +4548,2010-07-09 12:00:00,20646.800000000003,NSW1NSW1 +4549,2010-07-09 13:00:00,20335.57,NSW1NSW1 +4550,2010-07-09 14:00:00,19937.95,NSW1NSW1 +4551,2010-07-09 15:00:00,19926.68,NSW1NSW1 +4552,2010-07-09 16:00:00,20197.510000000002,NSW1NSW1 +4553,2010-07-09 17:00:00,21654.879999999997,NSW1NSW1 +4554,2010-07-09 18:00:00,23084.0,NSW1NSW1 +4555,2010-07-09 19:00:00,22426.47,NSW1NSW1 +4556,2010-07-09 20:00:00,21549.16,NSW1NSW1 +4557,2010-07-09 21:00:00,20868.09,NSW1NSW1 +4558,2010-07-09 22:00:00,20077.559999999998,NSW1NSW1 +4559,2010-07-09 23:00:00,19699.510000000002,NSW1NSW1 +4560,2010-07-10 00:00:00,18884.28,NSW1NSW1 +4561,2010-07-10 01:00:00,17799.370000000003,NSW1NSW1 +4562,2010-07-10 02:00:00,16595.98,NSW1NSW1 +4563,2010-07-10 03:00:00,15135.240000000002,NSW1NSW1 +4564,2010-07-10 04:00:00,14332.73,NSW1NSW1 +4565,2010-07-10 05:00:00,14276.720000000001,NSW1NSW1 +4566,2010-07-10 06:00:00,15004.79,NSW1NSW1 +4567,2010-07-10 07:00:00,16393.54,NSW1NSW1 +4568,2010-07-10 08:00:00,18442.699999999997,NSW1NSW1 +4569,2010-07-10 09:00:00,19952.800000000003,NSW1NSW1 +4570,2010-07-10 10:00:00,20226.46,NSW1NSW1 +4571,2010-07-10 11:00:00,19606.14,NSW1NSW1 +4572,2010-07-10 12:00:00,19064.0,NSW1NSW1 +4573,2010-07-10 13:00:00,18510.870000000003,NSW1NSW1 +4574,2010-07-10 14:00:00,17966.78,NSW1NSW1 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09:00:00,21489.35,NSW1NSW1 +4618,2010-07-12 10:00:00,21316.63,NSW1NSW1 +4619,2010-07-12 11:00:00,20785.559999999998,NSW1NSW1 +4620,2010-07-12 12:00:00,20307.96,NSW1NSW1 +4621,2010-07-12 13:00:00,20090.11,NSW1NSW1 +4622,2010-07-12 14:00:00,19782.22,NSW1NSW1 +4623,2010-07-12 15:00:00,19581.760000000002,NSW1NSW1 +4624,2010-07-12 16:00:00,19808.239999999998,NSW1NSW1 +4625,2010-07-12 17:00:00,21290.940000000002,NSW1NSW1 +4626,2010-07-12 18:00:00,23143.54,NSW1NSW1 +4627,2010-07-12 19:00:00,22518.940000000002,NSW1NSW1 +4628,2010-07-12 20:00:00,21597.35,NSW1NSW1 +4629,2010-07-12 21:00:00,20776.41,NSW1NSW1 +4630,2010-07-12 22:00:00,19699.91,NSW1NSW1 +4631,2010-07-12 23:00:00,19036.95,NSW1NSW1 +4632,2010-07-13 00:00:00,18160.739999999998,NSW1NSW1 +4633,2010-07-13 01:00:00,17339.66,NSW1NSW1 +4634,2010-07-13 02:00:00,16146.22,NSW1NSW1 +4635,2010-07-13 03:00:00,14819.560000000001,NSW1NSW1 +4636,2010-07-13 04:00:00,14258.21,NSW1NSW1 +4637,2010-07-13 05:00:00,14533.94,NSW1NSW1 +4638,2010-07-13 06:00:00,16296.02,NSW1NSW1 +4639,2010-07-13 07:00:00,18633.269999999997,NSW1NSW1 +4640,2010-07-13 08:00:00,20105.21,NSW1NSW1 +4641,2010-07-13 09:00:00,20662.18,NSW1NSW1 +4642,2010-07-13 10:00:00,20653.59,NSW1NSW1 +4643,2010-07-13 11:00:00,20240.23,NSW1NSW1 +4644,2010-07-13 12:00:00,20246.08,NSW1NSW1 +4645,2010-07-13 13:00:00,20122.82,NSW1NSW1 +4646,2010-07-13 14:00:00,19883.71,NSW1NSW1 +4647,2010-07-13 15:00:00,19661.120000000003,NSW1NSW1 +4648,2010-07-13 16:00:00,20052.29,NSW1NSW1 +4649,2010-07-13 17:00:00,21660.370000000003,NSW1NSW1 +4650,2010-07-13 18:00:00,22827.84,NSW1NSW1 +4651,2010-07-13 19:00:00,21988.489999999998,NSW1NSW1 +4652,2010-07-13 20:00:00,20893.96,NSW1NSW1 +4653,2010-07-13 21:00:00,19888.559999999998,NSW1NSW1 +4654,2010-07-13 22:00:00,18935.43,NSW1NSW1 +4655,2010-07-13 23:00:00,18233.56,NSW1NSW1 +4656,2010-07-14 00:00:00,17523.4,NSW1NSW1 +4657,2010-07-14 01:00:00,16699.89,NSW1NSW1 +4658,2010-07-14 02:00:00,15617.0,NSW1NSW1 +4659,2010-07-14 03:00:00,14384.970000000001,NSW1NSW1 +4660,2010-07-14 04:00:00,13758.31,NSW1NSW1 +4661,2010-07-14 05:00:00,14073.46,NSW1NSW1 +4662,2010-07-14 06:00:00,15754.880000000001,NSW1NSW1 +4663,2010-07-14 07:00:00,18002.09,NSW1NSW1 +4664,2010-07-14 08:00:00,19642.04,NSW1NSW1 +4665,2010-07-14 09:00:00,20234.57,NSW1NSW1 +4666,2010-07-14 10:00:00,20067.04,NSW1NSW1 +4667,2010-07-14 11:00:00,19757.28,NSW1NSW1 +4668,2010-07-14 12:00:00,19199.7,NSW1NSW1 +4669,2010-07-14 13:00:00,18758.04,NSW1NSW1 +4670,2010-07-14 14:00:00,18761.85,NSW1NSW1 +4671,2010-07-14 15:00:00,18736.21,NSW1NSW1 +4672,2010-07-14 16:00:00,18928.03,NSW1NSW1 +4673,2010-07-14 17:00:00,20489.120000000003,NSW1NSW1 +4674,2010-07-14 18:00:00,22660.25,NSW1NSW1 +4675,2010-07-14 19:00:00,22251.17,NSW1NSW1 +4676,2010-07-14 20:00:00,21459.42,NSW1NSW1 +4677,2010-07-14 21:00:00,20680.989999999998,NSW1NSW1 +4678,2010-07-14 22:00:00,19648.7,NSW1NSW1 +4679,2010-07-14 23:00:00,18883.52,NSW1NSW1 +4680,2010-07-15 00:00:00,18052.0,NSW1NSW1 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22:00:00,20940.129999999997,NSW1NSW1 +4703,2010-07-15 23:00:00,20109.21,NSW1NSW1 +4704,2010-07-16 00:00:00,19064.760000000002,NSW1NSW1 +4705,2010-07-16 01:00:00,18065.629999999997,NSW1NSW1 +4706,2010-07-16 02:00:00,16990.510000000002,NSW1NSW1 +4707,2010-07-16 03:00:00,15574.58,NSW1NSW1 +4708,2010-07-16 04:00:00,14990.55,NSW1NSW1 +4709,2010-07-16 05:00:00,15450.439999999999,NSW1NSW1 +4710,2010-07-16 06:00:00,17400.78,NSW1NSW1 +4711,2010-07-16 07:00:00,20025.6,NSW1NSW1 +4712,2010-07-16 08:00:00,21980.379999999997,NSW1NSW1 +4713,2010-07-16 09:00:00,22417.940000000002,NSW1NSW1 +4714,2010-07-16 10:00:00,21903.21,NSW1NSW1 +4715,2010-07-16 11:00:00,21170.07,NSW1NSW1 +4716,2010-07-16 12:00:00,20368.84,NSW1NSW1 +4717,2010-07-16 13:00:00,19758.18,NSW1NSW1 +4718,2010-07-16 14:00:00,19293.63,NSW1NSW1 +4719,2010-07-16 15:00:00,19084.58,NSW1NSW1 +4720,2010-07-16 16:00:00,19423.42,NSW1NSW1 +4721,2010-07-16 17:00:00,21005.36,NSW1NSW1 +4722,2010-07-16 18:00:00,22954.75,NSW1NSW1 +4723,2010-07-16 19:00:00,22728.2,NSW1NSW1 +4724,2010-07-16 20:00:00,22022.72,NSW1NSW1 +4725,2010-07-16 21:00:00,21491.81,NSW1NSW1 +4726,2010-07-16 22:00:00,20751.0,NSW1NSW1 +4727,2010-07-16 23:00:00,20197.14,NSW1NSW1 +4728,2010-07-17 00:00:00,19231.309999999998,NSW1NSW1 +4729,2010-07-17 01:00:00,18200.230000000003,NSW1NSW1 +4730,2010-07-17 02:00:00,16866.16,NSW1NSW1 +4731,2010-07-17 03:00:00,15380.759999999998,NSW1NSW1 +4732,2010-07-17 04:00:00,14731.53,NSW1NSW1 +4733,2010-07-17 05:00:00,14683.990000000002,NSW1NSW1 +4734,2010-07-17 06:00:00,15449.66,NSW1NSW1 +4735,2010-07-17 07:00:00,16896.489999999998,NSW1NSW1 +4736,2010-07-17 08:00:00,19196.980000000003,NSW1NSW1 +4737,2010-07-17 09:00:00,20479.21,NSW1NSW1 +4738,2010-07-17 10:00:00,20354.27,NSW1NSW1 +4739,2010-07-17 11:00:00,19459.33,NSW1NSW1 +4740,2010-07-17 12:00:00,18436.73,NSW1NSW1 +4741,2010-07-17 13:00:00,17687.559999999998,NSW1NSW1 +4742,2010-07-17 14:00:00,17217.41,NSW1NSW1 +4743,2010-07-17 15:00:00,16943.63,NSW1NSW1 +4744,2010-07-17 16:00:00,17486.16,NSW1NSW1 +4745,2010-07-17 17:00:00,19357.59,NSW1NSW1 +4746,2010-07-17 18:00:00,21741.11,NSW1NSW1 +4747,2010-07-17 19:00:00,21417.9,NSW1NSW1 +4748,2010-07-17 20:00:00,20637.260000000002,NSW1NSW1 +4749,2010-07-17 21:00:00,20158.29,NSW1NSW1 +4750,2010-07-17 22:00:00,19508.08,NSW1NSW1 +4751,2010-07-17 23:00:00,18961.18,NSW1NSW1 +4752,2010-07-18 00:00:00,17812.79,NSW1NSW1 +4753,2010-07-18 01:00:00,16640.6,NSW1NSW1 +4754,2010-07-18 02:00:00,15490.83,NSW1NSW1 +4755,2010-07-18 03:00:00,14356.13,NSW1NSW1 +4756,2010-07-18 04:00:00,13864.8,NSW1NSW1 +4757,2010-07-18 05:00:00,13919.26,NSW1NSW1 +4758,2010-07-18 06:00:00,14531.59,NSW1NSW1 +4759,2010-07-18 07:00:00,15547.61,NSW1NSW1 +4760,2010-07-18 08:00:00,17534.86,NSW1NSW1 +4761,2010-07-18 09:00:00,18982.36,NSW1NSW1 +4762,2010-07-18 10:00:00,19344.36,NSW1NSW1 +4763,2010-07-18 11:00:00,18649.59,NSW1NSW1 +4764,2010-07-18 12:00:00,17780.010000000002,NSW1NSW1 +4765,2010-07-18 13:00:00,17130.440000000002,NSW1NSW1 +4766,2010-07-18 14:00:00,16673.7,NSW1NSW1 +4767,2010-07-18 15:00:00,16596.98,NSW1NSW1 +4768,2010-07-18 16:00:00,17224.98,NSW1NSW1 +4769,2010-07-18 17:00:00,19038.21,NSW1NSW1 +4770,2010-07-18 18:00:00,21626.46,NSW1NSW1 +4771,2010-07-18 19:00:00,21642.64,NSW1NSW1 +4772,2010-07-18 20:00:00,21156.7,NSW1NSW1 +4773,2010-07-18 21:00:00,20534.96,NSW1NSW1 +4774,2010-07-18 22:00:00,19374.510000000002,NSW1NSW1 +4775,2010-07-18 23:00:00,18226.38,NSW1NSW1 +4776,2010-07-19 00:00:00,17005.42,NSW1NSW1 +4777,2010-07-19 01:00:00,16128.18,NSW1NSW1 +4778,2010-07-19 02:00:00,15295.64,NSW1NSW1 +4779,2010-07-19 03:00:00,14328.45,NSW1NSW1 +4780,2010-07-19 04:00:00,14182.08,NSW1NSW1 +4781,2010-07-19 05:00:00,14774.66,NSW1NSW1 +4782,2010-07-19 06:00:00,16891.01,NSW1NSW1 +4783,2010-07-19 07:00:00,19988.1,NSW1NSW1 +4784,2010-07-19 08:00:00,21776.739999999998,NSW1NSW1 +4785,2010-07-19 09:00:00,22262.28,NSW1NSW1 +4786,2010-07-19 10:00:00,22140.629999999997,NSW1NSW1 +4787,2010-07-19 11:00:00,21874.36,NSW1NSW1 +4788,2010-07-19 12:00:00,21303.5,NSW1NSW1 +4789,2010-07-19 13:00:00,20891.97,NSW1NSW1 +4790,2010-07-19 14:00:00,20567.1,NSW1NSW1 +4791,2010-07-19 15:00:00,20679.32,NSW1NSW1 +4792,2010-07-19 16:00:00,21463.910000000003,NSW1NSW1 +4793,2010-07-19 17:00:00,23092.010000000002,NSW1NSW1 +4794,2010-07-19 18:00:00,24923.190000000002,NSW1NSW1 +4795,2010-07-19 19:00:00,24442.010000000002,NSW1NSW1 +4796,2010-07-19 20:00:00,23433.260000000002,NSW1NSW1 +4797,2010-07-19 21:00:00,22332.52,NSW1NSW1 +4798,2010-07-19 22:00:00,21035.190000000002,NSW1NSW1 +4799,2010-07-19 23:00:00,19978.48,NSW1NSW1 +4800,2010-07-20 00:00:00,19012.16,NSW1NSW1 +4801,2010-07-20 01:00:00,18159.53,NSW1NSW1 +4802,2010-07-20 02:00:00,17076.53,NSW1NSW1 +4803,2010-07-20 03:00:00,15751.97,NSW1NSW1 +4804,2010-07-20 04:00:00,15212.68,NSW1NSW1 +4805,2010-07-20 05:00:00,15546.380000000001,NSW1NSW1 +4806,2010-07-20 06:00:00,17736.239999999998,NSW1NSW1 +4807,2010-07-20 07:00:00,21188.83,NSW1NSW1 +4808,2010-07-20 08:00:00,22625.57,NSW1NSW1 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05:00:00,15620.279999999999,NSW1NSW1 +4830,2010-07-21 06:00:00,17906.73,NSW1NSW1 +4831,2010-07-21 07:00:00,21262.37,NSW1NSW1 +4832,2010-07-21 08:00:00,22955.15,NSW1NSW1 +4833,2010-07-21 09:00:00,22800.82,NSW1NSW1 +4834,2010-07-21 10:00:00,22533.300000000003,NSW1NSW1 +4835,2010-07-21 11:00:00,21932.760000000002,NSW1NSW1 +4836,2010-07-21 12:00:00,21268.739999999998,NSW1NSW1 +4837,2010-07-21 13:00:00,20704.03,NSW1NSW1 +4838,2010-07-21 14:00:00,20293.0,NSW1NSW1 +4839,2010-07-21 15:00:00,19993.03,NSW1NSW1 +4840,2010-07-21 16:00:00,20431.239999999998,NSW1NSW1 +4841,2010-07-21 17:00:00,22460.410000000003,NSW1NSW1 +4842,2010-07-21 18:00:00,25081.66,NSW1NSW1 +4843,2010-07-21 19:00:00,24915.129999999997,NSW1NSW1 +4844,2010-07-21 20:00:00,24037.0,NSW1NSW1 +4845,2010-07-21 21:00:00,23104.17,NSW1NSW1 +4846,2010-07-21 22:00:00,21734.690000000002,NSW1NSW1 +4847,2010-07-21 23:00:00,20472.68,NSW1NSW1 +4848,2010-07-22 00:00:00,19373.9,NSW1NSW1 +4849,2010-07-22 01:00:00,18426.65,NSW1NSW1 +4850,2010-07-22 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22:00:00,20534.78,NSW1NSW1 +4895,2010-07-23 23:00:00,20044.64,NSW1NSW1 +4896,2010-07-24 00:00:00,19215.14,NSW1NSW1 +4897,2010-07-24 01:00:00,18169.489999999998,NSW1NSW1 +4898,2010-07-24 02:00:00,16841.449999999997,NSW1NSW1 +4899,2010-07-24 03:00:00,15382.83,NSW1NSW1 +4900,2010-07-24 04:00:00,14651.91,NSW1NSW1 +4901,2010-07-24 05:00:00,14593.36,NSW1NSW1 +4902,2010-07-24 06:00:00,15300.13,NSW1NSW1 +4903,2010-07-24 07:00:00,16880.07,NSW1NSW1 +4904,2010-07-24 08:00:00,19046.7,NSW1NSW1 +4905,2010-07-24 09:00:00,20399.85,NSW1NSW1 +4906,2010-07-24 10:00:00,20352.78,NSW1NSW1 +4907,2010-07-24 11:00:00,19609.82,NSW1NSW1 +4908,2010-07-24 12:00:00,18839.59,NSW1NSW1 +4909,2010-07-24 13:00:00,18185.31,NSW1NSW1 +4910,2010-07-24 14:00:00,17713.39,NSW1NSW1 +4911,2010-07-24 15:00:00,17453.239999999998,NSW1NSW1 +4912,2010-07-24 16:00:00,17986.690000000002,NSW1NSW1 +4913,2010-07-24 17:00:00,19695.760000000002,NSW1NSW1 +4914,2010-07-24 18:00:00,21649.18,NSW1NSW1 +4915,2010-07-24 19:00:00,21195.65,NSW1NSW1 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17:00:00,20099.36,NSW1NSW1 +4938,2010-07-25 18:00:00,22204.14,NSW1NSW1 +4939,2010-07-25 19:00:00,21854.77,NSW1NSW1 +4940,2010-07-25 20:00:00,21177.190000000002,NSW1NSW1 +4941,2010-07-25 21:00:00,20430.949999999997,NSW1NSW1 +4942,2010-07-25 22:00:00,19493.18,NSW1NSW1 +4943,2010-07-25 23:00:00,18435.34,NSW1NSW1 +4944,2010-07-26 00:00:00,17123.04,NSW1NSW1 +4945,2010-07-26 01:00:00,16208.400000000001,NSW1NSW1 +4946,2010-07-26 02:00:00,15297.75,NSW1NSW1 +4947,2010-07-26 03:00:00,14402.46,NSW1NSW1 +4948,2010-07-26 04:00:00,14175.79,NSW1NSW1 +4949,2010-07-26 05:00:00,14918.119999999999,NSW1NSW1 +4950,2010-07-26 06:00:00,17111.88,NSW1NSW1 +4951,2010-07-26 07:00:00,20400.17,NSW1NSW1 +4952,2010-07-26 08:00:00,21979.45,NSW1NSW1 +4953,2010-07-26 09:00:00,21667.16,NSW1NSW1 +4954,2010-07-26 10:00:00,21147.67,NSW1NSW1 +4955,2010-07-26 11:00:00,20850.239999999998,NSW1NSW1 +4956,2010-07-26 12:00:00,20278.75,NSW1NSW1 +4957,2010-07-26 13:00:00,20119.67,NSW1NSW1 +4958,2010-07-26 14:00:00,19979.47,NSW1NSW1 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12:00:00,20083.41,NSW1NSW1 +4981,2010-07-27 13:00:00,19854.760000000002,NSW1NSW1 +4982,2010-07-27 14:00:00,19652.09,NSW1NSW1 +4983,2010-07-27 15:00:00,19608.02,NSW1NSW1 +4984,2010-07-27 16:00:00,20096.05,NSW1NSW1 +4985,2010-07-27 17:00:00,21773.32,NSW1NSW1 +4986,2010-07-27 18:00:00,23804.83,NSW1NSW1 +4987,2010-07-27 19:00:00,23388.27,NSW1NSW1 +4988,2010-07-27 20:00:00,22592.47,NSW1NSW1 +4989,2010-07-27 21:00:00,21564.78,NSW1NSW1 +4990,2010-07-27 22:00:00,20371.71,NSW1NSW1 +4991,2010-07-27 23:00:00,19333.82,NSW1NSW1 +4992,2010-07-28 00:00:00,18519.03,NSW1NSW1 +4993,2010-07-28 01:00:00,17687.699999999997,NSW1NSW1 +4994,2010-07-28 02:00:00,16537.65,NSW1NSW1 +4995,2010-07-28 03:00:00,15082.86,NSW1NSW1 +4996,2010-07-28 04:00:00,14558.29,NSW1NSW1 +4997,2010-07-28 05:00:00,14932.82,NSW1NSW1 +4998,2010-07-28 06:00:00,17043.62,NSW1NSW1 +4999,2010-07-28 07:00:00,20167.6,NSW1NSW1 +5000,2010-07-28 08:00:00,21639.94,NSW1NSW1 +5001,2010-07-28 09:00:00,21621.95,NSW1NSW1 +5002,2010-07-28 10:00:00,21596.41,NSW1NSW1 +5003,2010-07-28 11:00:00,21373.04,NSW1NSW1 +5004,2010-07-28 12:00:00,21182.72,NSW1NSW1 +5005,2010-07-28 13:00:00,21071.23,NSW1NSW1 +5006,2010-07-28 14:00:00,21011.89,NSW1NSW1 +5007,2010-07-28 15:00:00,20949.19,NSW1NSW1 +5008,2010-07-28 16:00:00,21683.28,NSW1NSW1 +5009,2010-07-28 17:00:00,23042.440000000002,NSW1NSW1 +5010,2010-07-28 18:00:00,24231.62,NSW1NSW1 +5011,2010-07-28 19:00:00,23549.800000000003,NSW1NSW1 +5012,2010-07-28 20:00:00,22560.29,NSW1NSW1 +5013,2010-07-28 21:00:00,21481.96,NSW1NSW1 +5014,2010-07-28 22:00:00,20092.78,NSW1NSW1 +5015,2010-07-28 23:00:00,19088.93,NSW1NSW1 +5016,2010-07-29 00:00:00,18333.94,NSW1NSW1 +5017,2010-07-29 01:00:00,17493.260000000002,NSW1NSW1 +5018,2010-07-29 02:00:00,16340.7,NSW1NSW1 +5019,2010-07-29 03:00:00,14931.07,NSW1NSW1 +5020,2010-07-29 04:00:00,14327.23,NSW1NSW1 +5021,2010-07-29 05:00:00,14707.69,NSW1NSW1 +5022,2010-07-29 06:00:00,16668.25,NSW1NSW1 +5023,2010-07-29 07:00:00,19612.35,NSW1NSW1 +5024,2010-07-29 08:00:00,20973.11,NSW1NSW1 +5025,2010-07-29 09:00:00,20763.129999999997,NSW1NSW1 +5026,2010-07-29 10:00:00,20695.059999999998,NSW1NSW1 +5027,2010-07-29 11:00:00,20498.71,NSW1NSW1 +5028,2010-07-29 12:00:00,20383.71,NSW1NSW1 +5029,2010-07-29 13:00:00,20127.010000000002,NSW1NSW1 +5030,2010-07-29 14:00:00,19918.769999999997,NSW1NSW1 +5031,2010-07-29 15:00:00,19999.5,NSW1NSW1 +5032,2010-07-29 16:00:00,20606.68,NSW1NSW1 +5033,2010-07-29 17:00:00,22068.92,NSW1NSW1 +5034,2010-07-29 18:00:00,23667.05,NSW1NSW1 +5035,2010-07-29 19:00:00,23134.129999999997,NSW1NSW1 +5036,2010-07-29 20:00:00,22207.95,NSW1NSW1 +5037,2010-07-29 21:00:00,21257.309999999998,NSW1NSW1 +5038,2010-07-29 22:00:00,19978.97,NSW1NSW1 +5039,2010-07-29 23:00:00,19282.739999999998,NSW1NSW1 +5040,2010-07-30 00:00:00,18397.67,NSW1NSW1 +5041,2010-07-30 01:00:00,17487.04,NSW1NSW1 +5042,2010-07-30 02:00:00,16334.14,NSW1NSW1 +5043,2010-07-30 03:00:00,14946.7,NSW1NSW1 +5044,2010-07-30 04:00:00,14414.98,NSW1NSW1 +5045,2010-07-30 05:00:00,14764.23,NSW1NSW1 +5046,2010-07-30 06:00:00,16795.699999999997,NSW1NSW1 +5047,2010-07-30 07:00:00,19760.2,NSW1NSW1 +5048,2010-07-30 08:00:00,21009.559999999998,NSW1NSW1 +5049,2010-07-30 09:00:00,20749.61,NSW1NSW1 +5050,2010-07-30 10:00:00,20402.59,NSW1NSW1 +5051,2010-07-30 11:00:00,19953.83,NSW1NSW1 +5052,2010-07-30 12:00:00,19584.69,NSW1NSW1 +5053,2010-07-30 13:00:00,19233.69,NSW1NSW1 +5054,2010-07-30 14:00:00,19091.589999999997,NSW1NSW1 +5055,2010-07-30 15:00:00,18759.82,NSW1NSW1 +5056,2010-07-30 16:00:00,18992.1,NSW1NSW1 +5057,2010-07-30 17:00:00,20190.510000000002,NSW1NSW1 +5058,2010-07-30 18:00:00,21276.35,NSW1NSW1 +5059,2010-07-30 19:00:00,20548.79,NSW1NSW1 +5060,2010-07-30 20:00:00,19595.35,NSW1NSW1 +5061,2010-07-30 21:00:00,19027.57,NSW1NSW1 +5062,2010-07-30 22:00:00,18426.61,NSW1NSW1 +5063,2010-07-30 23:00:00,18325.21,NSW1NSW1 +5064,2010-07-31 00:00:00,17775.13,NSW1NSW1 +5065,2010-07-31 01:00:00,16796.45,NSW1NSW1 +5066,2010-07-31 02:00:00,15565.22,NSW1NSW1 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00:00:00,16762.85,NSW1NSW1 +5089,2010-08-01 01:00:00,15752.48,NSW1NSW1 +5090,2010-08-01 02:00:00,14756.96,NSW1NSW1 +5091,2010-08-01 03:00:00,13672.21,NSW1NSW1 +5092,2010-08-01 04:00:00,13286.900000000001,NSW1NSW1 +5093,2010-08-01 05:00:00,13362.45,NSW1NSW1 +5094,2010-08-01 06:00:00,13853.61,NSW1NSW1 +5095,2010-08-01 07:00:00,14856.130000000001,NSW1NSW1 +5096,2010-08-01 08:00:00,16593.91,NSW1NSW1 +5097,2010-08-01 09:00:00,17798.03,NSW1NSW1 +5098,2010-08-01 10:00:00,18000.78,NSW1NSW1 +5099,2010-08-01 11:00:00,17601.36,NSW1NSW1 +5100,2010-08-01 12:00:00,17130.18,NSW1NSW1 +5101,2010-08-01 13:00:00,16803.940000000002,NSW1NSW1 +5102,2010-08-01 14:00:00,16511.11,NSW1NSW1 +5103,2010-08-01 15:00:00,16491.940000000002,NSW1NSW1 +5104,2010-08-01 16:00:00,16949.379999999997,NSW1NSW1 +5105,2010-08-01 17:00:00,18275.96,NSW1NSW1 +5106,2010-08-01 18:00:00,20588.54,NSW1NSW1 +5107,2010-08-01 19:00:00,20732.81,NSW1NSW1 +5108,2010-08-01 20:00:00,20170.6,NSW1NSW1 +5109,2010-08-01 21:00:00,19428.67,NSW1NSW1 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19:00:00,24451.129999999997,NSW1NSW1 +5132,2010-08-02 20:00:00,23461.27,NSW1NSW1 +5133,2010-08-02 21:00:00,22437.61,NSW1NSW1 +5134,2010-08-02 22:00:00,20970.53,NSW1NSW1 +5135,2010-08-02 23:00:00,19777.309999999998,NSW1NSW1 +5136,2010-08-03 00:00:00,18645.559999999998,NSW1NSW1 +5137,2010-08-03 01:00:00,17857.72,NSW1NSW1 +5138,2010-08-03 02:00:00,16735.21,NSW1NSW1 +5139,2010-08-03 03:00:00,15378.14,NSW1NSW1 +5140,2010-08-03 04:00:00,14834.380000000001,NSW1NSW1 +5141,2010-08-03 05:00:00,15254.07,NSW1NSW1 +5142,2010-08-03 06:00:00,17366.5,NSW1NSW1 +5143,2010-08-03 07:00:00,20532.239999999998,NSW1NSW1 +5144,2010-08-03 08:00:00,22027.260000000002,NSW1NSW1 +5145,2010-08-03 09:00:00,21827.17,NSW1NSW1 +5146,2010-08-03 10:00:00,21618.04,NSW1NSW1 +5147,2010-08-03 11:00:00,21172.559999999998,NSW1NSW1 +5148,2010-08-03 12:00:00,20721.78,NSW1NSW1 +5149,2010-08-03 13:00:00,20341.1,NSW1NSW1 +5150,2010-08-03 14:00:00,19969.1,NSW1NSW1 +5151,2010-08-03 15:00:00,19687.010000000002,NSW1NSW1 +5152,2010-08-03 16:00:00,20160.11,NSW1NSW1 +5153,2010-08-03 17:00:00,21412.9,NSW1NSW1 +5154,2010-08-03 18:00:00,23728.3,NSW1NSW1 +5155,2010-08-03 19:00:00,23515.85,NSW1NSW1 +5156,2010-08-03 20:00:00,22689.53,NSW1NSW1 +5157,2010-08-03 21:00:00,21879.52,NSW1NSW1 +5158,2010-08-03 22:00:00,20643.489999999998,NSW1NSW1 +5159,2010-08-03 23:00:00,19646.15,NSW1NSW1 +5160,2010-08-04 00:00:00,18698.57,NSW1NSW1 +5161,2010-08-04 01:00:00,17800.08,NSW1NSW1 +5162,2010-08-04 02:00:00,16690.15,NSW1NSW1 +5163,2010-08-04 03:00:00,15393.61,NSW1NSW1 +5164,2010-08-04 04:00:00,14798.029999999999,NSW1NSW1 +5165,2010-08-04 05:00:00,15224.279999999999,NSW1NSW1 +5166,2010-08-04 06:00:00,17365.7,NSW1NSW1 +5167,2010-08-04 07:00:00,20686.8,NSW1NSW1 +5168,2010-08-04 08:00:00,21836.36,NSW1NSW1 +5169,2010-08-04 09:00:00,21281.260000000002,NSW1NSW1 +5170,2010-08-04 10:00:00,20807.809999999998,NSW1NSW1 +5171,2010-08-04 11:00:00,20077.989999999998,NSW1NSW1 +5172,2010-08-04 12:00:00,19412.67,NSW1NSW1 +5173,2010-08-04 13:00:00,19172.68,NSW1NSW1 +5174,2010-08-04 14:00:00,18883.23,NSW1NSW1 +5175,2010-08-04 15:00:00,18604.309999999998,NSW1NSW1 +5176,2010-08-04 16:00:00,18900.67,NSW1NSW1 +5177,2010-08-04 17:00:00,19988.16,NSW1NSW1 +5178,2010-08-04 18:00:00,22545.089999999997,NSW1NSW1 +5179,2010-08-04 19:00:00,22632.019999999997,NSW1NSW1 +5180,2010-08-04 20:00:00,22079.769999999997,NSW1NSW1 +5181,2010-08-04 21:00:00,21311.239999999998,NSW1NSW1 +5182,2010-08-04 22:00:00,20321.87,NSW1NSW1 +5183,2010-08-04 23:00:00,19406.269999999997,NSW1NSW1 +5184,2010-08-05 00:00:00,18519.47,NSW1NSW1 +5185,2010-08-05 01:00:00,17710.44,NSW1NSW1 +5186,2010-08-05 02:00:00,16586.239999999998,NSW1NSW1 +5187,2010-08-05 03:00:00,15198.64,NSW1NSW1 +5188,2010-08-05 04:00:00,14687.51,NSW1NSW1 +5189,2010-08-05 05:00:00,15175.24,NSW1NSW1 +5190,2010-08-05 06:00:00,17433.1,NSW1NSW1 +5191,2010-08-05 07:00:00,20773.92,NSW1NSW1 +5192,2010-08-05 08:00:00,22257.690000000002,NSW1NSW1 +5193,2010-08-05 09:00:00,21586.48,NSW1NSW1 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07:00:00,21052.95,NSW1NSW1 +5216,2010-08-06 08:00:00,22305.23,NSW1NSW1 +5217,2010-08-06 09:00:00,22075.61,NSW1NSW1 +5218,2010-08-06 10:00:00,21637.97,NSW1NSW1 +5219,2010-08-06 11:00:00,20911.05,NSW1NSW1 +5220,2010-08-06 12:00:00,20269.32,NSW1NSW1 +5221,2010-08-06 13:00:00,19626.1,NSW1NSW1 +5222,2010-08-06 14:00:00,19412.52,NSW1NSW1 +5223,2010-08-06 15:00:00,19017.57,NSW1NSW1 +5224,2010-08-06 16:00:00,19516.16,NSW1NSW1 +5225,2010-08-06 17:00:00,20841.47,NSW1NSW1 +5226,2010-08-06 18:00:00,23241.35,NSW1NSW1 +5227,2010-08-06 19:00:00,23229.96,NSW1NSW1 +5228,2010-08-06 20:00:00,22515.510000000002,NSW1NSW1 +5229,2010-08-06 21:00:00,21810.120000000003,NSW1NSW1 +5230,2010-08-06 22:00:00,21023.25,NSW1NSW1 +5231,2010-08-06 23:00:00,20333.379999999997,NSW1NSW1 +5232,2010-08-07 00:00:00,19318.629999999997,NSW1NSW1 +5233,2010-08-07 01:00:00,18269.989999999998,NSW1NSW1 +5234,2010-08-07 02:00:00,17003.44,NSW1NSW1 +5235,2010-08-07 03:00:00,15593.47,NSW1NSW1 +5236,2010-08-07 04:00:00,14942.17,NSW1NSW1 +5237,2010-08-07 05:00:00,14832.98,NSW1NSW1 +5238,2010-08-07 06:00:00,15691.48,NSW1NSW1 +5239,2010-08-07 07:00:00,17223.82,NSW1NSW1 +5240,2010-08-07 08:00:00,19617.949999999997,NSW1NSW1 +5241,2010-08-07 09:00:00,20859.52,NSW1NSW1 +5242,2010-08-07 10:00:00,20420.61,NSW1NSW1 +5243,2010-08-07 11:00:00,19478.66,NSW1NSW1 +5244,2010-08-07 12:00:00,18529.010000000002,NSW1NSW1 +5245,2010-08-07 13:00:00,17852.98,NSW1NSW1 +5246,2010-08-07 14:00:00,17433.24,NSW1NSW1 +5247,2010-08-07 15:00:00,17426.73,NSW1NSW1 +5248,2010-08-07 16:00:00,17902.95,NSW1NSW1 +5249,2010-08-07 17:00:00,19561.37,NSW1NSW1 +5250,2010-08-07 18:00:00,22059.059999999998,NSW1NSW1 +5251,2010-08-07 19:00:00,21851.510000000002,NSW1NSW1 +5252,2010-08-07 20:00:00,21037.86,NSW1NSW1 +5253,2010-08-07 21:00:00,20364.690000000002,NSW1NSW1 +5254,2010-08-07 22:00:00,19707.690000000002,NSW1NSW1 +5255,2010-08-07 23:00:00,18986.05,NSW1NSW1 +5256,2010-08-08 00:00:00,17946.64,NSW1NSW1 +5257,2010-08-08 01:00:00,16919.9,NSW1NSW1 +5258,2010-08-08 02:00:00,15739.95,NSW1NSW1 +5259,2010-08-08 03:00:00,14742.939999999999,NSW1NSW1 +5260,2010-08-08 04:00:00,14272.04,NSW1NSW1 +5261,2010-08-08 05:00:00,14364.29,NSW1NSW1 +5262,2010-08-08 06:00:00,15061.97,NSW1NSW1 +5263,2010-08-08 07:00:00,16217.2,NSW1NSW1 +5264,2010-08-08 08:00:00,18230.58,NSW1NSW1 +5265,2010-08-08 09:00:00,19537.28,NSW1NSW1 +5266,2010-08-08 10:00:00,19494.09,NSW1NSW1 +5267,2010-08-08 11:00:00,18623.34,NSW1NSW1 +5268,2010-08-08 12:00:00,17824.23,NSW1NSW1 +5269,2010-08-08 13:00:00,17175.04,NSW1NSW1 +5270,2010-08-08 14:00:00,16766.879999999997,NSW1NSW1 +5271,2010-08-08 15:00:00,16726.1,NSW1NSW1 +5272,2010-08-08 16:00:00,17329.79,NSW1NSW1 +5273,2010-08-08 17:00:00,18974.87,NSW1NSW1 +5274,2010-08-08 18:00:00,22100.81,NSW1NSW1 +5275,2010-08-08 19:00:00,22329.41,NSW1NSW1 +5276,2010-08-08 20:00:00,21652.769999999997,NSW1NSW1 +5277,2010-08-08 21:00:00,20844.23,NSW1NSW1 +5278,2010-08-08 22:00:00,19383.18,NSW1NSW1 +5279,2010-08-08 23:00:00,18294.14,NSW1NSW1 +5280,2010-08-09 00:00:00,17281.230000000003,NSW1NSW1 +5281,2010-08-09 01:00:00,16480.9,NSW1NSW1 +5282,2010-08-09 02:00:00,15738.98,NSW1NSW1 +5283,2010-08-09 03:00:00,14828.89,NSW1NSW1 +5284,2010-08-09 04:00:00,14573.880000000001,NSW1NSW1 +5285,2010-08-09 05:00:00,15240.48,NSW1NSW1 +5286,2010-08-09 06:00:00,17599.0,NSW1NSW1 +5287,2010-08-09 07:00:00,21042.23,NSW1NSW1 +5288,2010-08-09 08:00:00,22564.09,NSW1NSW1 +5289,2010-08-09 09:00:00,22157.5,NSW1NSW1 +5290,2010-08-09 10:00:00,21561.93,NSW1NSW1 +5291,2010-08-09 11:00:00,20775.11,NSW1NSW1 +5292,2010-08-09 12:00:00,20068.16,NSW1NSW1 +5293,2010-08-09 13:00:00,19603.879999999997,NSW1NSW1 +5294,2010-08-09 14:00:00,19309.309999999998,NSW1NSW1 +5295,2010-08-09 15:00:00,19004.96,NSW1NSW1 +5296,2010-08-09 16:00:00,19265.510000000002,NSW1NSW1 +5297,2010-08-09 17:00:00,20510.38,NSW1NSW1 +5298,2010-08-09 18:00:00,23128.28,NSW1NSW1 +5299,2010-08-09 19:00:00,23065.129999999997,NSW1NSW1 +5300,2010-08-09 20:00:00,22245.3,NSW1NSW1 +5301,2010-08-09 21:00:00,21459.58,NSW1NSW1 +5302,2010-08-09 22:00:00,20289.339999999997,NSW1NSW1 +5303,2010-08-09 23:00:00,19166.57,NSW1NSW1 +5304,2010-08-10 00:00:00,18266.59,NSW1NSW1 +5305,2010-08-10 01:00:00,17530.65,NSW1NSW1 +5306,2010-08-10 02:00:00,16451.52,NSW1NSW1 +5307,2010-08-10 03:00:00,14949.86,NSW1NSW1 +5308,2010-08-10 04:00:00,14254.79,NSW1NSW1 +5309,2010-08-10 05:00:00,14711.25,NSW1NSW1 +5310,2010-08-10 06:00:00,16974.63,NSW1NSW1 +5311,2010-08-10 07:00:00,20318.370000000003,NSW1NSW1 +5312,2010-08-10 08:00:00,21719.010000000002,NSW1NSW1 +5313,2010-08-10 09:00:00,21611.489999999998,NSW1NSW1 +5314,2010-08-10 10:00:00,21901.370000000003,NSW1NSW1 +5315,2010-08-10 11:00:00,21685.25,NSW1NSW1 +5316,2010-08-10 12:00:00,21357.98,NSW1NSW1 +5317,2010-08-10 13:00:00,21184.379999999997,NSW1NSW1 +5318,2010-08-10 14:00:00,21011.3,NSW1NSW1 +5319,2010-08-10 15:00:00,20847.29,NSW1NSW1 +5320,2010-08-10 16:00:00,21373.870000000003,NSW1NSW1 +5321,2010-08-10 17:00:00,22491.550000000003,NSW1NSW1 +5322,2010-08-10 18:00:00,24035.35,NSW1NSW1 +5323,2010-08-10 19:00:00,23384.84,NSW1NSW1 +5324,2010-08-10 20:00:00,22272.79,NSW1NSW1 +5325,2010-08-10 21:00:00,21145.97,NSW1NSW1 +5326,2010-08-10 22:00:00,19882.09,NSW1NSW1 +5327,2010-08-10 23:00:00,18841.34,NSW1NSW1 +5328,2010-08-11 00:00:00,17840.92,NSW1NSW1 +5329,2010-08-11 01:00:00,17093.85,NSW1NSW1 +5330,2010-08-11 02:00:00,16069.01,NSW1NSW1 +5331,2010-08-11 03:00:00,14712.380000000001,NSW1NSW1 +5332,2010-08-11 04:00:00,14195.59,NSW1NSW1 +5333,2010-08-11 05:00:00,14587.16,NSW1NSW1 +5334,2010-08-11 06:00:00,16487.079999999998,NSW1NSW1 +5335,2010-08-11 07:00:00,19580.29,NSW1NSW1 +5336,2010-08-11 08:00:00,20979.309999999998,NSW1NSW1 +5337,2010-08-11 09:00:00,20893.8,NSW1NSW1 +5338,2010-08-11 10:00:00,20906.370000000003,NSW1NSW1 +5339,2010-08-11 11:00:00,20326.93,NSW1NSW1 +5340,2010-08-11 12:00:00,19954.379999999997,NSW1NSW1 +5341,2010-08-11 13:00:00,19471.370000000003,NSW1NSW1 +5342,2010-08-11 14:00:00,19275.19,NSW1NSW1 +5343,2010-08-11 15:00:00,19026.41,NSW1NSW1 +5344,2010-08-11 16:00:00,19365.75,NSW1NSW1 +5345,2010-08-11 17:00:00,20715.02,NSW1NSW1 +5346,2010-08-11 18:00:00,23106.75,NSW1NSW1 +5347,2010-08-11 19:00:00,23020.61,NSW1NSW1 +5348,2010-08-11 20:00:00,22204.440000000002,NSW1NSW1 +5349,2010-08-11 21:00:00,21377.809999999998,NSW1NSW1 +5350,2010-08-11 22:00:00,20238.59,NSW1NSW1 +5351,2010-08-11 23:00:00,19250.77,NSW1NSW1 +5352,2010-08-12 00:00:00,18128.53,NSW1NSW1 +5353,2010-08-12 01:00:00,17304.010000000002,NSW1NSW1 +5354,2010-08-12 02:00:00,16407.67,NSW1NSW1 +5355,2010-08-12 03:00:00,15191.400000000001,NSW1NSW1 +5356,2010-08-12 04:00:00,14662.630000000001,NSW1NSW1 +5357,2010-08-12 05:00:00,15014.3,NSW1NSW1 +5358,2010-08-12 06:00:00,17038.79,NSW1NSW1 +5359,2010-08-12 07:00:00,20128.019999999997,NSW1NSW1 +5360,2010-08-12 08:00:00,21355.36,NSW1NSW1 +5361,2010-08-12 09:00:00,20910.42,NSW1NSW1 +5362,2010-08-12 10:00:00,20780.68,NSW1NSW1 +5363,2010-08-12 11:00:00,20328.71,NSW1NSW1 +5364,2010-08-12 12:00:00,19924.67,NSW1NSW1 +5365,2010-08-12 13:00:00,19655.92,NSW1NSW1 +5366,2010-08-12 14:00:00,19559.690000000002,NSW1NSW1 +5367,2010-08-12 15:00:00,19566.9,NSW1NSW1 +5368,2010-08-12 16:00:00,20379.86,NSW1NSW1 +5369,2010-08-12 17:00:00,21791.52,NSW1NSW1 +5370,2010-08-12 18:00:00,23801.35,NSW1NSW1 +5371,2010-08-12 19:00:00,23608.36,NSW1NSW1 +5372,2010-08-12 20:00:00,22895.03,NSW1NSW1 +5373,2010-08-12 21:00:00,21736.36,NSW1NSW1 +5374,2010-08-12 22:00:00,20374.11,NSW1NSW1 +5375,2010-08-12 23:00:00,19406.56,NSW1NSW1 +5376,2010-08-13 00:00:00,18425.67,NSW1NSW1 +5377,2010-08-13 01:00:00,17600.22,NSW1NSW1 +5378,2010-08-13 02:00:00,16587.86,NSW1NSW1 +5379,2010-08-13 03:00:00,15300.35,NSW1NSW1 +5380,2010-08-13 04:00:00,14780.81,NSW1NSW1 +5381,2010-08-13 05:00:00,15283.880000000001,NSW1NSW1 +5382,2010-08-13 06:00:00,17390.9,NSW1NSW1 +5383,2010-08-13 07:00:00,20456.62,NSW1NSW1 +5384,2010-08-13 08:00:00,21620.63,NSW1NSW1 +5385,2010-08-13 09:00:00,21165.309999999998,NSW1NSW1 +5386,2010-08-13 10:00:00,20650.61,NSW1NSW1 +5387,2010-08-13 11:00:00,19951.35,NSW1NSW1 +5388,2010-08-13 12:00:00,19402.61,NSW1NSW1 +5389,2010-08-13 13:00:00,19098.75,NSW1NSW1 +5390,2010-08-13 14:00:00,18780.23,NSW1NSW1 +5391,2010-08-13 15:00:00,18515.25,NSW1NSW1 +5392,2010-08-13 16:00:00,18696.29,NSW1NSW1 +5393,2010-08-13 17:00:00,19498.05,NSW1NSW1 +5394,2010-08-13 18:00:00,21667.65,NSW1NSW1 +5395,2010-08-13 19:00:00,21661.620000000003,NSW1NSW1 +5396,2010-08-13 20:00:00,21049.77,NSW1NSW1 +5397,2010-08-13 21:00:00,20439.89,NSW1NSW1 +5398,2010-08-13 22:00:00,19889.559999999998,NSW1NSW1 +5399,2010-08-13 23:00:00,19463.2,NSW1NSW1 +5400,2010-08-14 00:00:00,18595.85,NSW1NSW1 +5401,2010-08-14 01:00:00,17668.79,NSW1NSW1 +5402,2010-08-14 02:00:00,16389.27,NSW1NSW1 +5403,2010-08-14 03:00:00,15035.34,NSW1NSW1 +5404,2010-08-14 04:00:00,14258.84,NSW1NSW1 +5405,2010-08-14 05:00:00,14348.67,NSW1NSW1 +5406,2010-08-14 06:00:00,15071.720000000001,NSW1NSW1 +5407,2010-08-14 07:00:00,16597.86,NSW1NSW1 +5408,2010-08-14 08:00:00,18670.17,NSW1NSW1 +5409,2010-08-14 09:00:00,19485.5,NSW1NSW1 +5410,2010-08-14 10:00:00,19213.43,NSW1NSW1 +5411,2010-08-14 11:00:00,18359.89,NSW1NSW1 +5412,2010-08-14 12:00:00,17602.33,NSW1NSW1 +5413,2010-08-14 13:00:00,17034.1,NSW1NSW1 +5414,2010-08-14 14:00:00,16589.17,NSW1NSW1 +5415,2010-08-14 15:00:00,16368.77,NSW1NSW1 +5416,2010-08-14 16:00:00,16784.62,NSW1NSW1 +5417,2010-08-14 17:00:00,17749.690000000002,NSW1NSW1 +5418,2010-08-14 18:00:00,19923.98,NSW1NSW1 +5419,2010-08-14 19:00:00,19957.54,NSW1NSW1 +5420,2010-08-14 20:00:00,19052.260000000002,NSW1NSW1 +5421,2010-08-14 21:00:00,18609.16,NSW1NSW1 +5422,2010-08-14 22:00:00,17985.46,NSW1NSW1 +5423,2010-08-14 23:00:00,17452.879999999997,NSW1NSW1 +5424,2010-08-15 00:00:00,16603.65,NSW1NSW1 +5425,2010-08-15 01:00:00,15573.55,NSW1NSW1 +5426,2010-08-15 02:00:00,14571.1,NSW1NSW1 +5427,2010-08-15 03:00:00,13512.86,NSW1NSW1 +5428,2010-08-15 04:00:00,13053.18,NSW1NSW1 +5429,2010-08-15 05:00:00,13100.099999999999,NSW1NSW1 +5430,2010-08-15 06:00:00,13622.84,NSW1NSW1 +5431,2010-08-15 07:00:00,14454.150000000001,NSW1NSW1 +5432,2010-08-15 08:00:00,16140.94,NSW1NSW1 +5433,2010-08-15 09:00:00,17535.949999999997,NSW1NSW1 +5434,2010-08-15 10:00:00,17754.25,NSW1NSW1 +5435,2010-08-15 11:00:00,17288.480000000003,NSW1NSW1 +5436,2010-08-15 12:00:00,17026.480000000003,NSW1NSW1 +5437,2010-08-15 13:00:00,17005.6,NSW1NSW1 +5438,2010-08-15 14:00:00,16140.2,NSW1NSW1 +5439,2010-08-15 15:00:00,16155.189999999999,NSW1NSW1 +5440,2010-08-15 16:00:00,16633.84,NSW1NSW1 +5441,2010-08-15 17:00:00,17623.75,NSW1NSW1 +5442,2010-08-15 18:00:00,19987.51,NSW1NSW1 +5443,2010-08-15 19:00:00,20249.510000000002,NSW1NSW1 +5444,2010-08-15 20:00:00,19532.32,NSW1NSW1 +5445,2010-08-15 21:00:00,18791.08,NSW1NSW1 +5446,2010-08-15 22:00:00,17763.5,NSW1NSW1 +5447,2010-08-15 23:00:00,16954.4,NSW1NSW1 +5448,2010-08-16 00:00:00,16072.1,NSW1NSW1 +5449,2010-08-16 01:00:00,15271.939999999999,NSW1NSW1 +5450,2010-08-16 02:00:00,14528.84,NSW1NSW1 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00:00:00,17991.05,NSW1NSW1 +5473,2010-08-17 01:00:00,17232.2,NSW1NSW1 +5474,2010-08-17 02:00:00,16164.97,NSW1NSW1 +5475,2010-08-17 03:00:00,14961.240000000002,NSW1NSW1 +5476,2010-08-17 04:00:00,14445.619999999999,NSW1NSW1 +5477,2010-08-17 05:00:00,15120.529999999999,NSW1NSW1 +5478,2010-08-17 06:00:00,17440.97,NSW1NSW1 +5479,2010-08-17 07:00:00,20557.27,NSW1NSW1 +5480,2010-08-17 08:00:00,21552.03,NSW1NSW1 +5481,2010-08-17 09:00:00,21034.93,NSW1NSW1 +5482,2010-08-17 10:00:00,20619.4,NSW1NSW1 +5483,2010-08-17 11:00:00,20003.27,NSW1NSW1 +5484,2010-08-17 12:00:00,19440.6,NSW1NSW1 +5485,2010-08-17 13:00:00,19019.84,NSW1NSW1 +5486,2010-08-17 14:00:00,18762.28,NSW1NSW1 +5487,2010-08-17 15:00:00,18472.12,NSW1NSW1 +5488,2010-08-17 16:00:00,18624.15,NSW1NSW1 +5489,2010-08-17 17:00:00,20204.11,NSW1NSW1 +5490,2010-08-17 18:00:00,22919.79,NSW1NSW1 +5491,2010-08-17 19:00:00,23182.43,NSW1NSW1 +5492,2010-08-17 20:00:00,22516.27,NSW1NSW1 +5493,2010-08-17 21:00:00,21597.87,NSW1NSW1 +5494,2010-08-17 22:00:00,20394.83,NSW1NSW1 +5495,2010-08-17 23:00:00,19274.52,NSW1NSW1 +5496,2010-08-18 00:00:00,18461.17,NSW1NSW1 +5497,2010-08-18 01:00:00,17614.42,NSW1NSW1 +5498,2010-08-18 02:00:00,16584.59,NSW1NSW1 +5499,2010-08-18 03:00:00,15328.56,NSW1NSW1 +5500,2010-08-18 04:00:00,14631.71,NSW1NSW1 +5501,2010-08-18 05:00:00,15199.19,NSW1NSW1 +5502,2010-08-18 06:00:00,17410.97,NSW1NSW1 +5503,2010-08-18 07:00:00,20707.88,NSW1NSW1 +5504,2010-08-18 08:00:00,21966.1,NSW1NSW1 +5505,2010-08-18 09:00:00,21295.190000000002,NSW1NSW1 +5506,2010-08-18 10:00:00,20692.94,NSW1NSW1 +5507,2010-08-18 11:00:00,19979.449999999997,NSW1NSW1 +5508,2010-08-18 12:00:00,19384.010000000002,NSW1NSW1 +5509,2010-08-18 13:00:00,19171.29,NSW1NSW1 +5510,2010-08-18 14:00:00,19279.86,NSW1NSW1 +5511,2010-08-18 15:00:00,19046.83,NSW1NSW1 +5512,2010-08-18 16:00:00,19199.56,NSW1NSW1 +5513,2010-08-18 17:00:00,20278.53,NSW1NSW1 +5514,2010-08-18 18:00:00,22125.059999999998,NSW1NSW1 +5515,2010-08-18 19:00:00,21742.02,NSW1NSW1 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+5538,2010-08-19 18:00:00,20394.28,NSW1NSW1 +5539,2010-08-19 19:00:00,20245.37,NSW1NSW1 +5540,2010-08-19 20:00:00,19469.059999999998,NSW1NSW1 +5541,2010-08-19 21:00:00,18672.75,NSW1NSW1 +5542,2010-08-19 22:00:00,17873.74,NSW1NSW1 +5543,2010-08-19 23:00:00,17385.48,NSW1NSW1 +5544,2010-08-20 00:00:00,16963.620000000003,NSW1NSW1 +5545,2010-08-20 01:00:00,16251.029999999999,NSW1NSW1 +5546,2010-08-20 02:00:00,15127.84,NSW1NSW1 +5547,2010-08-20 03:00:00,13861.630000000001,NSW1NSW1 +5548,2010-08-20 04:00:00,13383.619999999999,NSW1NSW1 +5549,2010-08-20 05:00:00,13920.77,NSW1NSW1 +5550,2010-08-20 06:00:00,15861.529999999999,NSW1NSW1 +5551,2010-08-20 07:00:00,18543.12,NSW1NSW1 +5552,2010-08-20 08:00:00,19530.53,NSW1NSW1 +5553,2010-08-20 09:00:00,19307.59,NSW1NSW1 +5554,2010-08-20 10:00:00,19258.09,NSW1NSW1 +5555,2010-08-20 11:00:00,19031.93,NSW1NSW1 +5556,2010-08-20 12:00:00,18538.86,NSW1NSW1 +5557,2010-08-20 13:00:00,18210.23,NSW1NSW1 +5558,2010-08-20 14:00:00,17996.82,NSW1NSW1 +5559,2010-08-20 15:00:00,17792.410000000003,NSW1NSW1 +5560,2010-08-20 16:00:00,18010.96,NSW1NSW1 +5561,2010-08-20 17:00:00,18786.32,NSW1NSW1 +5562,2010-08-20 18:00:00,20713.97,NSW1NSW1 +5563,2010-08-20 19:00:00,20644.15,NSW1NSW1 +5564,2010-08-20 20:00:00,19978.39,NSW1NSW1 +5565,2010-08-20 21:00:00,19388.440000000002,NSW1NSW1 +5566,2010-08-20 22:00:00,18851.4,NSW1NSW1 +5567,2010-08-20 23:00:00,18450.36,NSW1NSW1 +5568,2010-08-21 00:00:00,17827.620000000003,NSW1NSW1 +5569,2010-08-21 01:00:00,16924.6,NSW1NSW1 +5570,2010-08-21 02:00:00,15734.95,NSW1NSW1 +5571,2010-08-21 03:00:00,14364.189999999999,NSW1NSW1 +5572,2010-08-21 04:00:00,13659.669999999998,NSW1NSW1 +5573,2010-08-21 05:00:00,13717.24,NSW1NSW1 +5574,2010-08-21 06:00:00,14519.38,NSW1NSW1 +5575,2010-08-21 07:00:00,16195.93,NSW1NSW1 +5576,2010-08-21 08:00:00,18105.71,NSW1NSW1 +5577,2010-08-21 09:00:00,18962.82,NSW1NSW1 +5578,2010-08-21 10:00:00,18709.39,NSW1NSW1 +5579,2010-08-21 11:00:00,17981.800000000003,NSW1NSW1 +5580,2010-08-21 12:00:00,17346.87,NSW1NSW1 +5581,2010-08-21 13:00:00,16864.4,NSW1NSW1 +5582,2010-08-21 14:00:00,16471.73,NSW1NSW1 +5583,2010-08-21 15:00:00,16379.829999999998,NSW1NSW1 +5584,2010-08-21 16:00:00,16676.05,NSW1NSW1 +5585,2010-08-21 17:00:00,17633.11,NSW1NSW1 +5586,2010-08-21 18:00:00,20088.760000000002,NSW1NSW1 +5587,2010-08-21 19:00:00,20258.89,NSW1NSW1 +5588,2010-08-21 20:00:00,19629.53,NSW1NSW1 +5589,2010-08-21 21:00:00,19080.37,NSW1NSW1 +5590,2010-08-21 22:00:00,18717.87,NSW1NSW1 +5591,2010-08-21 23:00:00,18466.8,NSW1NSW1 +5592,2010-08-22 00:00:00,17429.61,NSW1NSW1 +5593,2010-08-22 01:00:00,16125.29,NSW1NSW1 +5594,2010-08-22 02:00:00,15040.14,NSW1NSW1 +5595,2010-08-22 03:00:00,13862.29,NSW1NSW1 +5596,2010-08-22 04:00:00,13586.009999999998,NSW1NSW1 +5597,2010-08-22 05:00:00,13666.31,NSW1NSW1 +5598,2010-08-22 06:00:00,14222.06,NSW1NSW1 +5599,2010-08-22 07:00:00,15371.1,NSW1NSW1 +5600,2010-08-22 08:00:00,17205.370000000003,NSW1NSW1 +5601,2010-08-22 09:00:00,18299.94,NSW1NSW1 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07:00:00,19448.22,NSW1NSW1 +5624,2010-08-23 08:00:00,21101.9,NSW1NSW1 +5625,2010-08-23 09:00:00,21258.6,NSW1NSW1 +5626,2010-08-23 10:00:00,21305.73,NSW1NSW1 +5627,2010-08-23 11:00:00,20804.18,NSW1NSW1 +5628,2010-08-23 12:00:00,20613.78,NSW1NSW1 +5629,2010-08-23 13:00:00,20539.35,NSW1NSW1 +5630,2010-08-23 14:00:00,20344.12,NSW1NSW1 +5631,2010-08-23 15:00:00,19926.57,NSW1NSW1 +5632,2010-08-23 16:00:00,20266.46,NSW1NSW1 +5633,2010-08-23 17:00:00,21363.57,NSW1NSW1 +5634,2010-08-23 18:00:00,23481.489999999998,NSW1NSW1 +5635,2010-08-23 19:00:00,23153.83,NSW1NSW1 +5636,2010-08-23 20:00:00,22059.4,NSW1NSW1 +5637,2010-08-23 21:00:00,20921.559999999998,NSW1NSW1 +5638,2010-08-23 22:00:00,19594.27,NSW1NSW1 +5639,2010-08-23 23:00:00,18612.25,NSW1NSW1 +5640,2010-08-24 00:00:00,17721.989999999998,NSW1NSW1 +5641,2010-08-24 01:00:00,16947.58,NSW1NSW1 +5642,2010-08-24 02:00:00,15901.61,NSW1NSW1 +5643,2010-08-24 03:00:00,14575.08,NSW1NSW1 +5644,2010-08-24 04:00:00,13938.45,NSW1NSW1 +5645,2010-08-24 05:00:00,14522.46,NSW1NSW1 +5646,2010-08-24 06:00:00,16553.829999999998,NSW1NSW1 +5647,2010-08-24 07:00:00,19515.989999999998,NSW1NSW1 +5648,2010-08-24 08:00:00,20424.050000000003,NSW1NSW1 +5649,2010-08-24 09:00:00,20046.25,NSW1NSW1 +5650,2010-08-24 10:00:00,19815.65,NSW1NSW1 +5651,2010-08-24 11:00:00,19292.730000000003,NSW1NSW1 +5652,2010-08-24 12:00:00,18879.800000000003,NSW1NSW1 +5653,2010-08-24 13:00:00,18681.510000000002,NSW1NSW1 +5654,2010-08-24 14:00:00,18512.34,NSW1NSW1 +5655,2010-08-24 15:00:00,18079.5,NSW1NSW1 +5656,2010-08-24 16:00:00,18493.620000000003,NSW1NSW1 +5657,2010-08-24 17:00:00,19833.21,NSW1NSW1 +5658,2010-08-24 18:00:00,22088.309999999998,NSW1NSW1 +5659,2010-08-24 19:00:00,22073.42,NSW1NSW1 +5660,2010-08-24 20:00:00,21234.65,NSW1NSW1 +5661,2010-08-24 21:00:00,20298.809999999998,NSW1NSW1 +5662,2010-08-24 22:00:00,19217.34,NSW1NSW1 +5663,2010-08-24 23:00:00,18361.440000000002,NSW1NSW1 +5664,2010-08-25 00:00:00,17621.15,NSW1NSW1 +5665,2010-08-25 01:00:00,16872.35,NSW1NSW1 +5666,2010-08-25 02:00:00,15869.61,NSW1NSW1 +5667,2010-08-25 03:00:00,14554.369999999999,NSW1NSW1 +5668,2010-08-25 04:00:00,13909.29,NSW1NSW1 +5669,2010-08-25 05:00:00,14351.36,NSW1NSW1 +5670,2010-08-25 06:00:00,16565.27,NSW1NSW1 +5671,2010-08-25 07:00:00,19416.66,NSW1NSW1 +5672,2010-08-25 08:00:00,20210.18,NSW1NSW1 +5673,2010-08-25 09:00:00,19874.18,NSW1NSW1 +5674,2010-08-25 10:00:00,19637.3,NSW1NSW1 +5675,2010-08-25 11:00:00,19234.190000000002,NSW1NSW1 +5676,2010-08-25 12:00:00,18890.4,NSW1NSW1 +5677,2010-08-25 13:00:00,18633.489999999998,NSW1NSW1 +5678,2010-08-25 14:00:00,18497.15,NSW1NSW1 +5679,2010-08-25 15:00:00,18320.72,NSW1NSW1 +5680,2010-08-25 16:00:00,18626.27,NSW1NSW1 +5681,2010-08-25 17:00:00,19791.52,NSW1NSW1 +5682,2010-08-25 18:00:00,22298.58,NSW1NSW1 +5683,2010-08-25 19:00:00,22483.32,NSW1NSW1 +5684,2010-08-25 20:00:00,21719.550000000003,NSW1NSW1 +5685,2010-08-25 21:00:00,20883.59,NSW1NSW1 +5686,2010-08-25 22:00:00,19759.440000000002,NSW1NSW1 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18:00:00,21396.8,NSW1NSW1 +5731,2010-08-27 19:00:00,21421.879999999997,NSW1NSW1 +5732,2010-08-27 20:00:00,20835.15,NSW1NSW1 +5733,2010-08-27 21:00:00,20261.34,NSW1NSW1 +5734,2010-08-27 22:00:00,19545.809999999998,NSW1NSW1 +5735,2010-08-27 23:00:00,19043.25,NSW1NSW1 +5736,2010-08-28 00:00:00,18351.32,NSW1NSW1 +5737,2010-08-28 01:00:00,17369.760000000002,NSW1NSW1 +5738,2010-08-28 02:00:00,16172.470000000001,NSW1NSW1 +5739,2010-08-28 03:00:00,14848.52,NSW1NSW1 +5740,2010-08-28 04:00:00,14310.75,NSW1NSW1 +5741,2010-08-28 05:00:00,14359.48,NSW1NSW1 +5742,2010-08-28 06:00:00,15138.95,NSW1NSW1 +5743,2010-08-28 07:00:00,16653.51,NSW1NSW1 +5744,2010-08-28 08:00:00,18502.74,NSW1NSW1 +5745,2010-08-28 09:00:00,19390.93,NSW1NSW1 +5746,2010-08-28 10:00:00,19153.940000000002,NSW1NSW1 +5747,2010-08-28 11:00:00,18453.019999999997,NSW1NSW1 +5748,2010-08-28 12:00:00,17742.68,NSW1NSW1 +5749,2010-08-28 13:00:00,17164.5,NSW1NSW1 +5750,2010-08-28 14:00:00,16725.36,NSW1NSW1 +5751,2010-08-28 15:00:00,16597.34,NSW1NSW1 +5752,2010-08-28 16:00:00,16986.72,NSW1NSW1 +5753,2010-08-28 17:00:00,17867.67,NSW1NSW1 +5754,2010-08-28 18:00:00,20281.190000000002,NSW1NSW1 +5755,2010-08-28 19:00:00,20618.33,NSW1NSW1 +5756,2010-08-28 20:00:00,19875.82,NSW1NSW1 +5757,2010-08-28 21:00:00,19297.48,NSW1NSW1 +5758,2010-08-28 22:00:00,18815.260000000002,NSW1NSW1 +5759,2010-08-28 23:00:00,18349.29,NSW1NSW1 +5760,2010-08-29 00:00:00,17476.91,NSW1NSW1 +5761,2010-08-29 01:00:00,16466.32,NSW1NSW1 +5762,2010-08-29 02:00:00,15454.7,NSW1NSW1 +5763,2010-08-29 03:00:00,14357.21,NSW1NSW1 +5764,2010-08-29 04:00:00,13838.09,NSW1NSW1 +5765,2010-08-29 05:00:00,13896.439999999999,NSW1NSW1 +5766,2010-08-29 06:00:00,14397.3,NSW1NSW1 +5767,2010-08-29 07:00:00,15429.07,NSW1NSW1 +5768,2010-08-29 08:00:00,17120.489999999998,NSW1NSW1 +5769,2010-08-29 09:00:00,18183.839999999997,NSW1NSW1 +5770,2010-08-29 10:00:00,18178.9,NSW1NSW1 +5771,2010-08-29 11:00:00,17543.32,NSW1NSW1 +5772,2010-08-29 12:00:00,16939.910000000003,NSW1NSW1 +5773,2010-08-29 13:00:00,16469.38,NSW1NSW1 +5774,2010-08-29 14:00:00,16034.24,NSW1NSW1 +5775,2010-08-29 15:00:00,15905.779999999999,NSW1NSW1 +5776,2010-08-29 16:00:00,16328.52,NSW1NSW1 +5777,2010-08-29 17:00:00,17291.52,NSW1NSW1 +5778,2010-08-29 18:00:00,19947.85,NSW1NSW1 +5779,2010-08-29 19:00:00,20581.010000000002,NSW1NSW1 +5780,2010-08-29 20:00:00,19801.47,NSW1NSW1 +5781,2010-08-29 21:00:00,19121.27,NSW1NSW1 +5782,2010-08-29 22:00:00,18124.17,NSW1NSW1 +5783,2010-08-29 23:00:00,17188.82,NSW1NSW1 +5784,2010-08-30 00:00:00,16323.34,NSW1NSW1 +5785,2010-08-30 01:00:00,15567.33,NSW1NSW1 +5786,2010-08-30 02:00:00,14820.39,NSW1NSW1 +5787,2010-08-30 03:00:00,13875.400000000001,NSW1NSW1 +5788,2010-08-30 04:00:00,13683.45,NSW1NSW1 +5789,2010-08-30 05:00:00,14352.31,NSW1NSW1 +5790,2010-08-30 06:00:00,16442.43,NSW1NSW1 +5791,2010-08-30 07:00:00,19226.8,NSW1NSW1 +5792,2010-08-30 08:00:00,20233.72,NSW1NSW1 +5793,2010-08-30 09:00:00,19982.59,NSW1NSW1 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03:00:00,14090.14,NSW1NSW1 +5836,2010-09-01 04:00:00,13689.82,NSW1NSW1 +5837,2010-09-01 05:00:00,14142.509999999998,NSW1NSW1 +5838,2010-09-01 06:00:00,15999.259999999998,NSW1NSW1 +5839,2010-09-01 07:00:00,18394.18,NSW1NSW1 +5840,2010-09-01 08:00:00,19317.059999999998,NSW1NSW1 +5841,2010-09-01 09:00:00,19107.79,NSW1NSW1 +5842,2010-09-01 10:00:00,19006.39,NSW1NSW1 +5843,2010-09-01 11:00:00,18723.61,NSW1NSW1 +5844,2010-09-01 12:00:00,18438.769999999997,NSW1NSW1 +5845,2010-09-01 13:00:00,18157.04,NSW1NSW1 +5846,2010-09-01 14:00:00,18134.05,NSW1NSW1 +5847,2010-09-01 15:00:00,17973.839999999997,NSW1NSW1 +5848,2010-09-01 16:00:00,18054.05,NSW1NSW1 +5849,2010-09-01 17:00:00,18653.48,NSW1NSW1 +5850,2010-09-01 18:00:00,19959.66,NSW1NSW1 +5851,2010-09-01 19:00:00,19736.309999999998,NSW1NSW1 +5852,2010-09-01 20:00:00,18825.6,NSW1NSW1 +5853,2010-09-01 21:00:00,17993.16,NSW1NSW1 +5854,2010-09-01 22:00:00,17385.17,NSW1NSW1 +5855,2010-09-01 23:00:00,17072.78,NSW1NSW1 +5856,2010-09-02 00:00:00,16599.1,NSW1NSW1 +5857,2010-09-02 01:00:00,15930.14,NSW1NSW1 +5858,2010-09-02 02:00:00,15023.25,NSW1NSW1 +5859,2010-09-02 03:00:00,13851.15,NSW1NSW1 +5860,2010-09-02 04:00:00,13463.24,NSW1NSW1 +5861,2010-09-02 05:00:00,13852.3,NSW1NSW1 +5862,2010-09-02 06:00:00,15611.27,NSW1NSW1 +5863,2010-09-02 07:00:00,17960.79,NSW1NSW1 +5864,2010-09-02 08:00:00,19055.64,NSW1NSW1 +5865,2010-09-02 09:00:00,19225.940000000002,NSW1NSW1 +5866,2010-09-02 10:00:00,19389.35,NSW1NSW1 +5867,2010-09-02 11:00:00,19246.41,NSW1NSW1 +5868,2010-09-02 12:00:00,19076.550000000003,NSW1NSW1 +5869,2010-09-02 13:00:00,18902.879999999997,NSW1NSW1 +5870,2010-09-02 14:00:00,18722.28,NSW1NSW1 +5871,2010-09-02 15:00:00,18571.34,NSW1NSW1 +5872,2010-09-02 16:00:00,18817.260000000002,NSW1NSW1 +5873,2010-09-02 17:00:00,19588.23,NSW1NSW1 +5874,2010-09-02 18:00:00,20794.38,NSW1NSW1 +5875,2010-09-02 19:00:00,20514.82,NSW1NSW1 +5876,2010-09-02 20:00:00,19519.97,NSW1NSW1 +5877,2010-09-02 21:00:00,18763.32,NSW1NSW1 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19:00:00,20360.260000000002,NSW1NSW1 +5900,2010-09-03 20:00:00,19425.190000000002,NSW1NSW1 +5901,2010-09-03 21:00:00,18643.22,NSW1NSW1 +5902,2010-09-03 22:00:00,18109.2,NSW1NSW1 +5903,2010-09-03 23:00:00,17804.55,NSW1NSW1 +5904,2010-09-04 00:00:00,17191.59,NSW1NSW1 +5905,2010-09-04 01:00:00,16389.43,NSW1NSW1 +5906,2010-09-04 02:00:00,15139.2,NSW1NSW1 +5907,2010-09-04 03:00:00,13744.31,NSW1NSW1 +5908,2010-09-04 04:00:00,13003.84,NSW1NSW1 +5909,2010-09-04 05:00:00,13010.19,NSW1NSW1 +5910,2010-09-04 06:00:00,13540.43,NSW1NSW1 +5911,2010-09-04 07:00:00,14678.05,NSW1NSW1 +5912,2010-09-04 08:00:00,16469.75,NSW1NSW1 +5913,2010-09-04 09:00:00,18059.3,NSW1NSW1 +5914,2010-09-04 10:00:00,18687.589999999997,NSW1NSW1 +5915,2010-09-04 11:00:00,18311.9,NSW1NSW1 +5916,2010-09-04 12:00:00,17992.25,NSW1NSW1 +5917,2010-09-04 13:00:00,17598.47,NSW1NSW1 +5918,2010-09-04 14:00:00,17295.94,NSW1NSW1 +5919,2010-09-04 15:00:00,17147.98,NSW1NSW1 +5920,2010-09-04 16:00:00,17076.57,NSW1NSW1 +5921,2010-09-04 17:00:00,17752.05,NSW1NSW1 +5922,2010-09-04 18:00:00,18793.99,NSW1NSW1 +5923,2010-09-04 19:00:00,18434.71,NSW1NSW1 +5924,2010-09-04 20:00:00,17353.77,NSW1NSW1 +5925,2010-09-04 21:00:00,16796.72,NSW1NSW1 +5926,2010-09-04 22:00:00,16500.89,NSW1NSW1 +5927,2010-09-04 23:00:00,16402.6,NSW1NSW1 +5928,2010-09-05 00:00:00,15687.02,NSW1NSW1 +5929,2010-09-05 01:00:00,14827.79,NSW1NSW1 +5930,2010-09-05 02:00:00,13774.45,NSW1NSW1 +5931,2010-09-05 03:00:00,12767.64,NSW1NSW1 +5932,2010-09-05 04:00:00,12473.42,NSW1NSW1 +5933,2010-09-05 05:00:00,12477.41,NSW1NSW1 +5934,2010-09-05 06:00:00,12723.77,NSW1NSW1 +5935,2010-09-05 07:00:00,13510.5,NSW1NSW1 +5936,2010-09-05 08:00:00,15048.1,NSW1NSW1 +5937,2010-09-05 09:00:00,16091.4,NSW1NSW1 +5938,2010-09-05 10:00:00,16435.510000000002,NSW1NSW1 +5939,2010-09-05 11:00:00,16298.56,NSW1NSW1 +5940,2010-09-05 12:00:00,16035.71,NSW1NSW1 +5941,2010-09-05 13:00:00,15650.54,NSW1NSW1 +5942,2010-09-05 14:00:00,15329.68,NSW1NSW1 +5943,2010-09-05 15:00:00,15233.400000000001,NSW1NSW1 +5944,2010-09-05 16:00:00,15517.380000000001,NSW1NSW1 +5945,2010-09-05 17:00:00,15968.11,NSW1NSW1 +5946,2010-09-05 18:00:00,17533.79,NSW1NSW1 +5947,2010-09-05 19:00:00,17974.29,NSW1NSW1 +5948,2010-09-05 20:00:00,17446.75,NSW1NSW1 +5949,2010-09-05 21:00:00,17018.690000000002,NSW1NSW1 +5950,2010-09-05 22:00:00,16564.29,NSW1NSW1 +5951,2010-09-05 23:00:00,16037.92,NSW1NSW1 +5952,2010-09-06 00:00:00,15293.42,NSW1NSW1 +5953,2010-09-06 01:00:00,14704.54,NSW1NSW1 +5954,2010-09-06 02:00:00,14078.82,NSW1NSW1 +5955,2010-09-06 03:00:00,13338.02,NSW1NSW1 +5956,2010-09-06 04:00:00,13228.279999999999,NSW1NSW1 +5957,2010-09-06 05:00:00,13619.44,NSW1NSW1 +5958,2010-09-06 06:00:00,15515.130000000001,NSW1NSW1 +5959,2010-09-06 07:00:00,18052.120000000003,NSW1NSW1 +5960,2010-09-06 08:00:00,19087.010000000002,NSW1NSW1 +5961,2010-09-06 09:00:00,19102.91,NSW1NSW1 +5962,2010-09-06 10:00:00,19133.0,NSW1NSW1 +5963,2010-09-06 11:00:00,18885.91,NSW1NSW1 +5964,2010-09-06 12:00:00,18622.04,NSW1NSW1 +5965,2010-09-06 13:00:00,18412.79,NSW1NSW1 +5966,2010-09-06 14:00:00,18294.67,NSW1NSW1 +5967,2010-09-06 15:00:00,18049.480000000003,NSW1NSW1 +5968,2010-09-06 16:00:00,18322.239999999998,NSW1NSW1 +5969,2010-09-06 17:00:00,19000.03,NSW1NSW1 +5970,2010-09-06 18:00:00,20612.989999999998,NSW1NSW1 +5971,2010-09-06 19:00:00,20804.260000000002,NSW1NSW1 +5972,2010-09-06 20:00:00,20050.0,NSW1NSW1 +5973,2010-09-06 21:00:00,19177.97,NSW1NSW1 +5974,2010-09-06 22:00:00,18363.2,NSW1NSW1 +5975,2010-09-06 23:00:00,17869.07,NSW1NSW1 +5976,2010-09-07 00:00:00,17315.13,NSW1NSW1 +5977,2010-09-07 01:00:00,16691.879999999997,NSW1NSW1 +5978,2010-09-07 02:00:00,15692.39,NSW1NSW1 +5979,2010-09-07 03:00:00,14485.41,NSW1NSW1 +5980,2010-09-07 04:00:00,13983.26,NSW1NSW1 +5981,2010-09-07 05:00:00,14391.89,NSW1NSW1 +5982,2010-09-07 06:00:00,16466.39,NSW1NSW1 +5983,2010-09-07 07:00:00,19074.15,NSW1NSW1 +5984,2010-09-07 08:00:00,20028.97,NSW1NSW1 +5985,2010-09-07 09:00:00,19717.51,NSW1NSW1 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07:00:00,19261.379999999997,NSW1NSW1 +6008,2010-09-08 08:00:00,20053.050000000003,NSW1NSW1 +6009,2010-09-08 09:00:00,19639.23,NSW1NSW1 +6010,2010-09-08 10:00:00,19375.36,NSW1NSW1 +6011,2010-09-08 11:00:00,18934.42,NSW1NSW1 +6012,2010-09-08 12:00:00,18519.58,NSW1NSW1 +6013,2010-09-08 13:00:00,18225.97,NSW1NSW1 +6014,2010-09-08 14:00:00,18177.79,NSW1NSW1 +6015,2010-09-08 15:00:00,17955.3,NSW1NSW1 +6016,2010-09-08 16:00:00,17996.300000000003,NSW1NSW1 +6017,2010-09-08 17:00:00,18650.54,NSW1NSW1 +6018,2010-09-08 18:00:00,20458.97,NSW1NSW1 +6019,2010-09-08 19:00:00,21040.02,NSW1NSW1 +6020,2010-09-08 20:00:00,20258.8,NSW1NSW1 +6021,2010-09-08 21:00:00,19435.98,NSW1NSW1 +6022,2010-09-08 22:00:00,18562.02,NSW1NSW1 +6023,2010-09-08 23:00:00,17874.92,NSW1NSW1 +6024,2010-09-09 00:00:00,17218.25,NSW1NSW1 +6025,2010-09-09 01:00:00,16499.72,NSW1NSW1 +6026,2010-09-09 02:00:00,15482.65,NSW1NSW1 +6027,2010-09-09 03:00:00,14210.9,NSW1NSW1 +6028,2010-09-09 04:00:00,13715.17,NSW1NSW1 +6029,2010-09-09 05:00:00,14075.439999999999,NSW1NSW1 +6030,2010-09-09 06:00:00,16009.92,NSW1NSW1 +6031,2010-09-09 07:00:00,18792.16,NSW1NSW1 +6032,2010-09-09 08:00:00,20025.16,NSW1NSW1 +6033,2010-09-09 09:00:00,19678.58,NSW1NSW1 +6034,2010-09-09 10:00:00,19203.97,NSW1NSW1 +6035,2010-09-09 11:00:00,18912.64,NSW1NSW1 +6036,2010-09-09 12:00:00,18785.98,NSW1NSW1 +6037,2010-09-09 13:00:00,18785.559999999998,NSW1NSW1 +6038,2010-09-09 14:00:00,18805.16,NSW1NSW1 +6039,2010-09-09 15:00:00,18798.0,NSW1NSW1 +6040,2010-09-09 16:00:00,19467.440000000002,NSW1NSW1 +6041,2010-09-09 17:00:00,20573.67,NSW1NSW1 +6042,2010-09-09 18:00:00,21972.15,NSW1NSW1 +6043,2010-09-09 19:00:00,21773.5,NSW1NSW1 +6044,2010-09-09 20:00:00,20937.18,NSW1NSW1 +6045,2010-09-09 21:00:00,19780.98,NSW1NSW1 +6046,2010-09-09 22:00:00,18562.699999999997,NSW1NSW1 +6047,2010-09-09 23:00:00,17865.93,NSW1NSW1 +6048,2010-09-10 00:00:00,17218.05,NSW1NSW1 +6049,2010-09-10 01:00:00,16489.53,NSW1NSW1 +6050,2010-09-10 02:00:00,15432.48,NSW1NSW1 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00:00:00,17319.629999999997,NSW1NSW1 +6073,2010-09-11 01:00:00,16476.74,NSW1NSW1 +6074,2010-09-11 02:00:00,15294.23,NSW1NSW1 +6075,2010-09-11 03:00:00,14054.05,NSW1NSW1 +6076,2010-09-11 04:00:00,13457.74,NSW1NSW1 +6077,2010-09-11 05:00:00,13426.619999999999,NSW1NSW1 +6078,2010-09-11 06:00:00,14102.279999999999,NSW1NSW1 +6079,2010-09-11 07:00:00,15532.07,NSW1NSW1 +6080,2010-09-11 08:00:00,17133.75,NSW1NSW1 +6081,2010-09-11 09:00:00,18048.6,NSW1NSW1 +6082,2010-09-11 10:00:00,17920.73,NSW1NSW1 +6083,2010-09-11 11:00:00,17331.18,NSW1NSW1 +6084,2010-09-11 12:00:00,16701.59,NSW1NSW1 +6085,2010-09-11 13:00:00,16243.38,NSW1NSW1 +6086,2010-09-11 14:00:00,15851.439999999999,NSW1NSW1 +6087,2010-09-11 15:00:00,15621.42,NSW1NSW1 +6088,2010-09-11 16:00:00,15690.56,NSW1NSW1 +6089,2010-09-11 17:00:00,16194.08,NSW1NSW1 +6090,2010-09-11 18:00:00,17987.36,NSW1NSW1 +6091,2010-09-11 19:00:00,18649.78,NSW1NSW1 +6092,2010-09-11 20:00:00,17968.1,NSW1NSW1 +6093,2010-09-11 21:00:00,17527.18,NSW1NSW1 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12:00:00,18225.67,NSW1NSW1 +6181,2010-09-15 13:00:00,18183.33,NSW1NSW1 +6182,2010-09-15 14:00:00,18048.120000000003,NSW1NSW1 +6183,2010-09-15 15:00:00,17841.52,NSW1NSW1 +6184,2010-09-15 16:00:00,17856.31,NSW1NSW1 +6185,2010-09-15 17:00:00,18187.93,NSW1NSW1 +6186,2010-09-15 18:00:00,19549.53,NSW1NSW1 +6187,2010-09-15 19:00:00,19969.489999999998,NSW1NSW1 +6188,2010-09-15 20:00:00,19243.75,NSW1NSW1 +6189,2010-09-15 21:00:00,18502.17,NSW1NSW1 +6190,2010-09-15 22:00:00,17800.260000000002,NSW1NSW1 +6191,2010-09-15 23:00:00,17310.39,NSW1NSW1 +6192,2010-09-16 00:00:00,16674.879999999997,NSW1NSW1 +6193,2010-09-16 01:00:00,15933.94,NSW1NSW1 +6194,2010-09-16 02:00:00,14934.55,NSW1NSW1 +6195,2010-09-16 03:00:00,13738.2,NSW1NSW1 +6196,2010-09-16 04:00:00,13238.42,NSW1NSW1 +6197,2010-09-16 05:00:00,13606.19,NSW1NSW1 +6198,2010-09-16 06:00:00,15441.34,NSW1NSW1 +6199,2010-09-16 07:00:00,17979.37,NSW1NSW1 +6200,2010-09-16 08:00:00,18911.760000000002,NSW1NSW1 +6201,2010-09-16 09:00:00,18771.76,NSW1NSW1 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04:00:00,13255.09,NSW1NSW1 +6245,2010-09-18 05:00:00,13289.52,NSW1NSW1 +6246,2010-09-18 06:00:00,13913.740000000002,NSW1NSW1 +6247,2010-09-18 07:00:00,15408.83,NSW1NSW1 +6248,2010-09-18 08:00:00,16906.42,NSW1NSW1 +6249,2010-09-18 09:00:00,17896.67,NSW1NSW1 +6250,2010-09-18 10:00:00,17783.300000000003,NSW1NSW1 +6251,2010-09-18 11:00:00,17182.010000000002,NSW1NSW1 +6252,2010-09-18 12:00:00,16630.11,NSW1NSW1 +6253,2010-09-18 13:00:00,16147.16,NSW1NSW1 +6254,2010-09-18 14:00:00,15858.89,NSW1NSW1 +6255,2010-09-18 15:00:00,15640.03,NSW1NSW1 +6256,2010-09-18 16:00:00,15721.27,NSW1NSW1 +6257,2010-09-18 17:00:00,16140.279999999999,NSW1NSW1 +6258,2010-09-18 18:00:00,17787.97,NSW1NSW1 +6259,2010-09-18 19:00:00,18201.96,NSW1NSW1 +6260,2010-09-18 20:00:00,17450.83,NSW1NSW1 +6261,2010-09-18 21:00:00,17035.72,NSW1NSW1 +6262,2010-09-18 22:00:00,16730.17,NSW1NSW1 +6263,2010-09-18 23:00:00,16356.39,NSW1NSW1 +6264,2010-09-19 00:00:00,15762.029999999999,NSW1NSW1 +6265,2010-09-19 01:00:00,14927.98,NSW1NSW1 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23:00:00,16341.39,NSW1NSW1 +6288,2010-09-20 00:00:00,15637.94,NSW1NSW1 +6289,2010-09-20 01:00:00,14959.06,NSW1NSW1 +6290,2010-09-20 02:00:00,14217.32,NSW1NSW1 +6291,2010-09-20 03:00:00,13483.75,NSW1NSW1 +6292,2010-09-20 04:00:00,13226.77,NSW1NSW1 +6293,2010-09-20 05:00:00,13856.0,NSW1NSW1 +6294,2010-09-20 06:00:00,15796.759999999998,NSW1NSW1 +6295,2010-09-20 07:00:00,18249.61,NSW1NSW1 +6296,2010-09-20 08:00:00,19356.25,NSW1NSW1 +6297,2010-09-20 09:00:00,19378.83,NSW1NSW1 +6298,2010-09-20 10:00:00,19514.309999999998,NSW1NSW1 +6299,2010-09-20 11:00:00,19334.3,NSW1NSW1 +6300,2010-09-20 12:00:00,19021.769999999997,NSW1NSW1 +6301,2010-09-20 13:00:00,18855.15,NSW1NSW1 +6302,2010-09-20 14:00:00,18615.870000000003,NSW1NSW1 +6303,2010-09-20 15:00:00,18331.34,NSW1NSW1 +6304,2010-09-20 16:00:00,18259.71,NSW1NSW1 +6305,2010-09-20 17:00:00,18642.28,NSW1NSW1 +6306,2010-09-20 18:00:00,20133.78,NSW1NSW1 +6307,2010-09-20 19:00:00,20399.68,NSW1NSW1 +6308,2010-09-20 20:00:00,19559.84,NSW1NSW1 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18:00:00,19758.07,NSW1NSW1 +6331,2010-09-21 19:00:00,19792.7,NSW1NSW1 +6332,2010-09-21 20:00:00,18906.86,NSW1NSW1 +6333,2010-09-21 21:00:00,18010.46,NSW1NSW1 +6334,2010-09-21 22:00:00,17367.79,NSW1NSW1 +6335,2010-09-21 23:00:00,17070.81,NSW1NSW1 +6336,2010-09-22 00:00:00,16485.38,NSW1NSW1 +6337,2010-09-22 01:00:00,15877.470000000001,NSW1NSW1 +6338,2010-09-22 02:00:00,14953.67,NSW1NSW1 +6339,2010-09-22 03:00:00,13687.49,NSW1NSW1 +6340,2010-09-22 04:00:00,13228.09,NSW1NSW1 +6341,2010-09-22 05:00:00,13684.79,NSW1NSW1 +6342,2010-09-22 06:00:00,15452.05,NSW1NSW1 +6343,2010-09-22 07:00:00,17864.57,NSW1NSW1 +6344,2010-09-22 08:00:00,18697.239999999998,NSW1NSW1 +6345,2010-09-22 09:00:00,18742.32,NSW1NSW1 +6346,2010-09-22 10:00:00,18954.54,NSW1NSW1 +6347,2010-09-22 11:00:00,18809.53,NSW1NSW1 +6348,2010-09-22 12:00:00,18466.489999999998,NSW1NSW1 +6349,2010-09-22 13:00:00,18247.66,NSW1NSW1 +6350,2010-09-22 14:00:00,18193.379999999997,NSW1NSW1 +6351,2010-09-22 15:00:00,17844.85,NSW1NSW1 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14:00:00,18247.59,NSW1NSW1 +6375,2010-09-23 15:00:00,18030.760000000002,NSW1NSW1 +6376,2010-09-23 16:00:00,18068.93,NSW1NSW1 +6377,2010-09-23 17:00:00,18466.96,NSW1NSW1 +6378,2010-09-23 18:00:00,19724.239999999998,NSW1NSW1 +6379,2010-09-23 19:00:00,19946.67,NSW1NSW1 +6380,2010-09-23 20:00:00,19141.72,NSW1NSW1 +6381,2010-09-23 21:00:00,18329.809999999998,NSW1NSW1 +6382,2010-09-23 22:00:00,17482.42,NSW1NSW1 +6383,2010-09-23 23:00:00,17165.0,NSW1NSW1 +6384,2010-09-24 00:00:00,16621.18,NSW1NSW1 +6385,2010-09-24 01:00:00,15938.01,NSW1NSW1 +6386,2010-09-24 02:00:00,14888.23,NSW1NSW1 +6387,2010-09-24 03:00:00,13785.939999999999,NSW1NSW1 +6388,2010-09-24 04:00:00,13295.45,NSW1NSW1 +6389,2010-09-24 05:00:00,13712.759999999998,NSW1NSW1 +6390,2010-09-24 06:00:00,15340.81,NSW1NSW1 +6391,2010-09-24 07:00:00,17465.010000000002,NSW1NSW1 +6392,2010-09-24 08:00:00,18382.09,NSW1NSW1 +6393,2010-09-24 09:00:00,18687.559999999998,NSW1NSW1 +6394,2010-09-24 10:00:00,18866.38,NSW1NSW1 +6395,2010-09-24 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09:00:00,16881.77,NSW1NSW1 +6418,2010-09-25 10:00:00,17098.1,NSW1NSW1 +6419,2010-09-25 11:00:00,16842.57,NSW1NSW1 +6420,2010-09-25 12:00:00,16659.260000000002,NSW1NSW1 +6421,2010-09-25 13:00:00,16364.5,NSW1NSW1 +6422,2010-09-25 14:00:00,16083.119999999999,NSW1NSW1 +6423,2010-09-25 15:00:00,15854.45,NSW1NSW1 +6424,2010-09-25 16:00:00,15734.1,NSW1NSW1 +6425,2010-09-25 17:00:00,15852.67,NSW1NSW1 +6426,2010-09-25 18:00:00,16830.39,NSW1NSW1 +6427,2010-09-25 19:00:00,17190.71,NSW1NSW1 +6428,2010-09-25 20:00:00,16519.66,NSW1NSW1 +6429,2010-09-25 21:00:00,16137.0,NSW1NSW1 +6430,2010-09-25 22:00:00,15787.51,NSW1NSW1 +6431,2010-09-25 23:00:00,15638.380000000001,NSW1NSW1 +6432,2010-09-26 00:00:00,15136.77,NSW1NSW1 +6433,2010-09-26 01:00:00,14368.96,NSW1NSW1 +6434,2010-09-26 02:00:00,13476.029999999999,NSW1NSW1 +6435,2010-09-26 03:00:00,12598.83,NSW1NSW1 +6436,2010-09-26 04:00:00,12413.599999999999,NSW1NSW1 +6437,2010-09-26 05:00:00,12439.96,NSW1NSW1 +6438,2010-09-26 06:00:00,12670.880000000001,NSW1NSW1 +6439,2010-09-26 07:00:00,13461.29,NSW1NSW1 +6440,2010-09-26 08:00:00,14762.970000000001,NSW1NSW1 +6441,2010-09-26 09:00:00,15806.93,NSW1NSW1 +6442,2010-09-26 10:00:00,16169.26,NSW1NSW1 +6443,2010-09-26 11:00:00,16050.380000000001,NSW1NSW1 +6444,2010-09-26 12:00:00,15880.029999999999,NSW1NSW1 +6445,2010-09-26 13:00:00,15458.48,NSW1NSW1 +6446,2010-09-26 14:00:00,15195.0,NSW1NSW1 +6447,2010-09-26 15:00:00,15077.27,NSW1NSW1 +6448,2010-09-26 16:00:00,15186.57,NSW1NSW1 +6449,2010-09-26 17:00:00,15417.45,NSW1NSW1 +6450,2010-09-26 18:00:00,16612.8,NSW1NSW1 +6451,2010-09-26 19:00:00,17304.870000000003,NSW1NSW1 +6452,2010-09-26 20:00:00,16537.3,NSW1NSW1 +6453,2010-09-26 21:00:00,16012.83,NSW1NSW1 +6454,2010-09-26 22:00:00,15447.85,NSW1NSW1 +6455,2010-09-26 23:00:00,15136.59,NSW1NSW1 +6456,2010-09-27 00:00:00,14499.49,NSW1NSW1 +6457,2010-09-27 01:00:00,13949.66,NSW1NSW1 +6458,2010-09-27 02:00:00,13282.41,NSW1NSW1 +6459,2010-09-27 03:00:00,12528.41,NSW1NSW1 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21:00:00,16959.42,NSW1NSW1 +6718,2010-10-07 22:00:00,16634.07,NSW1NSW1 +6719,2010-10-07 23:00:00,16237.83,NSW1NSW1 +6720,2010-10-08 00:00:00,15661.64,NSW1NSW1 +6721,2010-10-08 01:00:00,14788.57,NSW1NSW1 +6722,2010-10-08 02:00:00,13692.46,NSW1NSW1 +6723,2010-10-08 03:00:00,13178.32,NSW1NSW1 +6724,2010-10-08 04:00:00,13453.57,NSW1NSW1 +6725,2010-10-08 05:00:00,14757.46,NSW1NSW1 +6726,2010-10-08 06:00:00,16454.08,NSW1NSW1 +6727,2010-10-08 07:00:00,17846.91,NSW1NSW1 +6728,2010-10-08 08:00:00,18573.21,NSW1NSW1 +6729,2010-10-08 09:00:00,18876.17,NSW1NSW1 +6730,2010-10-08 10:00:00,18769.489999999998,NSW1NSW1 +6731,2010-10-08 11:00:00,18585.4,NSW1NSW1 +6732,2010-10-08 12:00:00,18400.72,NSW1NSW1 +6733,2010-10-08 13:00:00,18186.97,NSW1NSW1 +6734,2010-10-08 14:00:00,18034.559999999998,NSW1NSW1 +6735,2010-10-08 15:00:00,17925.489999999998,NSW1NSW1 +6736,2010-10-08 16:00:00,17955.47,NSW1NSW1 +6737,2010-10-08 17:00:00,17632.85,NSW1NSW1 +6738,2010-10-08 18:00:00,17560.27,NSW1NSW1 +6739,2010-10-08 19:00:00,17605.05,NSW1NSW1 +6740,2010-10-08 20:00:00,17135.46,NSW1NSW1 +6741,2010-10-08 21:00:00,16558.510000000002,NSW1NSW1 +6742,2010-10-08 22:00:00,16645.57,NSW1NSW1 +6743,2010-10-08 23:00:00,16327.490000000002,NSW1NSW1 +6744,2010-10-09 00:00:00,15668.470000000001,NSW1NSW1 +6745,2010-10-09 01:00:00,14710.68,NSW1NSW1 +6746,2010-10-09 02:00:00,13414.439999999999,NSW1NSW1 +6747,2010-10-09 03:00:00,12810.21,NSW1NSW1 +6748,2010-10-09 04:00:00,12759.220000000001,NSW1NSW1 +6749,2010-10-09 05:00:00,13191.779999999999,NSW1NSW1 +6750,2010-10-09 06:00:00,13976.01,NSW1NSW1 +6751,2010-10-09 07:00:00,15510.46,NSW1NSW1 +6752,2010-10-09 08:00:00,16912.97,NSW1NSW1 +6753,2010-10-09 09:00:00,17360.71,NSW1NSW1 +6754,2010-10-09 10:00:00,17367.12,NSW1NSW1 +6755,2010-10-09 11:00:00,17108.010000000002,NSW1NSW1 +6756,2010-10-09 12:00:00,16766.92,NSW1NSW1 +6757,2010-10-09 13:00:00,16408.62,NSW1NSW1 +6758,2010-10-09 14:00:00,16158.9,NSW1NSW1 +6759,2010-10-09 15:00:00,16208.04,NSW1NSW1 +6760,2010-10-09 16:00:00,16343.810000000001,NSW1NSW1 +6761,2010-10-09 17:00:00,16518.59,NSW1NSW1 +6762,2010-10-09 18:00:00,16946.15,NSW1NSW1 +6763,2010-10-09 19:00:00,16947.93,NSW1NSW1 +6764,2010-10-09 20:00:00,16165.23,NSW1NSW1 +6765,2010-10-09 21:00:00,15892.16,NSW1NSW1 +6766,2010-10-09 22:00:00,15775.880000000001,NSW1NSW1 +6767,2010-10-09 23:00:00,15126.16,NSW1NSW1 +6768,2010-10-10 00:00:00,14332.91,NSW1NSW1 +6769,2010-10-10 01:00:00,13607.23,NSW1NSW1 +6770,2010-10-10 02:00:00,12669.849999999999,NSW1NSW1 +6771,2010-10-10 03:00:00,12301.27,NSW1NSW1 +6772,2010-10-10 04:00:00,12352.69,NSW1NSW1 +6773,2010-10-10 05:00:00,12558.86,NSW1NSW1 +6774,2010-10-10 06:00:00,13091.939999999999,NSW1NSW1 +6775,2010-10-10 07:00:00,14364.17,NSW1NSW1 +6776,2010-10-10 08:00:00,15632.09,NSW1NSW1 +6777,2010-10-10 09:00:00,16352.380000000001,NSW1NSW1 +6778,2010-10-10 10:00:00,16474.23,NSW1NSW1 +6779,2010-10-10 11:00:00,16359.119999999999,NSW1NSW1 +6780,2010-10-10 12:00:00,15984.82,NSW1NSW1 +6781,2010-10-10 13:00:00,15619.84,NSW1NSW1 +6782,2010-10-10 14:00:00,15359.23,NSW1NSW1 +6783,2010-10-10 15:00:00,15449.05,NSW1NSW1 +6784,2010-10-10 16:00:00,15570.22,NSW1NSW1 +6785,2010-10-10 17:00:00,16275.51,NSW1NSW1 +6786,2010-10-10 18:00:00,17022.190000000002,NSW1NSW1 +6787,2010-10-10 19:00:00,17147.190000000002,NSW1NSW1 +6788,2010-10-10 20:00:00,16591.39,NSW1NSW1 +6789,2010-10-10 21:00:00,15829.43,NSW1NSW1 +6790,2010-10-10 22:00:00,15317.130000000001,NSW1NSW1 +6791,2010-10-10 23:00:00,14712.67,NSW1NSW1 +6792,2010-10-11 00:00:00,14118.08,NSW1NSW1 +6793,2010-10-11 01:00:00,13448.98,NSW1NSW1 +6794,2010-10-11 02:00:00,12800.880000000001,NSW1NSW1 +6795,2010-10-11 03:00:00,12383.25,NSW1NSW1 +6796,2010-10-11 04:00:00,12869.2,NSW1NSW1 +6797,2010-10-11 05:00:00,14382.99,NSW1NSW1 +6798,2010-10-11 06:00:00,16548.91,NSW1NSW1 +6799,2010-10-11 07:00:00,18101.68,NSW1NSW1 +6800,2010-10-11 08:00:00,18563.29,NSW1NSW1 +6801,2010-10-11 09:00:00,19065.33,NSW1NSW1 +6802,2010-10-11 10:00:00,19039.449999999997,NSW1NSW1 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08:00:00,18814.129999999997,NSW1NSW1 +6825,2010-10-12 09:00:00,19006.86,NSW1NSW1 +6826,2010-10-12 10:00:00,18990.04,NSW1NSW1 +6827,2010-10-12 11:00:00,18846.18,NSW1NSW1 +6828,2010-10-12 12:00:00,18736.46,NSW1NSW1 +6829,2010-10-12 13:00:00,18703.9,NSW1NSW1 +6830,2010-10-12 14:00:00,18586.54,NSW1NSW1 +6831,2010-10-12 15:00:00,18535.98,NSW1NSW1 +6832,2010-10-12 16:00:00,18580.980000000003,NSW1NSW1 +6833,2010-10-12 17:00:00,18440.37,NSW1NSW1 +6834,2010-10-12 18:00:00,18406.33,NSW1NSW1 +6835,2010-10-12 19:00:00,18449.699999999997,NSW1NSW1 +6836,2010-10-12 20:00:00,17732.98,NSW1NSW1 +6837,2010-10-12 21:00:00,17026.85,NSW1NSW1 +6838,2010-10-12 22:00:00,16670.82,NSW1NSW1 +6839,2010-10-12 23:00:00,16219.61,NSW1NSW1 +6840,2010-10-13 00:00:00,15685.71,NSW1NSW1 +6841,2010-10-13 01:00:00,14817.55,NSW1NSW1 +6842,2010-10-13 02:00:00,13583.05,NSW1NSW1 +6843,2010-10-13 03:00:00,12934.74,NSW1NSW1 +6844,2010-10-13 04:00:00,13275.46,NSW1NSW1 +6845,2010-10-13 05:00:00,14934.369999999999,NSW1NSW1 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01:00:00,14498.92,NSW1NSW1 +6890,2010-10-15 02:00:00,13320.15,NSW1NSW1 +6891,2010-10-15 03:00:00,12889.61,NSW1NSW1 +6892,2010-10-15 04:00:00,13150.98,NSW1NSW1 +6893,2010-10-15 05:00:00,14454.45,NSW1NSW1 +6894,2010-10-15 06:00:00,16715.95,NSW1NSW1 +6895,2010-10-15 07:00:00,18259.940000000002,NSW1NSW1 +6896,2010-10-15 08:00:00,18885.07,NSW1NSW1 +6897,2010-10-15 09:00:00,19293.95,NSW1NSW1 +6898,2010-10-15 10:00:00,19367.36,NSW1NSW1 +6899,2010-10-15 11:00:00,19308.2,NSW1NSW1 +6900,2010-10-15 12:00:00,18969.35,NSW1NSW1 +6901,2010-10-15 13:00:00,18846.629999999997,NSW1NSW1 +6902,2010-10-15 14:00:00,18598.04,NSW1NSW1 +6903,2010-10-15 15:00:00,18453.39,NSW1NSW1 +6904,2010-10-15 16:00:00,18445.07,NSW1NSW1 +6905,2010-10-15 17:00:00,18047.02,NSW1NSW1 +6906,2010-10-15 18:00:00,17880.47,NSW1NSW1 +6907,2010-10-15 19:00:00,17770.12,NSW1NSW1 +6908,2010-10-15 20:00:00,17084.46,NSW1NSW1 +6909,2010-10-15 21:00:00,16461.72,NSW1NSW1 +6910,2010-10-15 22:00:00,16315.05,NSW1NSW1 +6911,2010-10-15 23:00:00,15926.81,NSW1NSW1 +6912,2010-10-16 00:00:00,15471.18,NSW1NSW1 +6913,2010-10-16 01:00:00,14457.5,NSW1NSW1 +6914,2010-10-16 02:00:00,13232.060000000001,NSW1NSW1 +6915,2010-10-16 03:00:00,12710.970000000001,NSW1NSW1 +6916,2010-10-16 04:00:00,12792.189999999999,NSW1NSW1 +6917,2010-10-16 05:00:00,13108.84,NSW1NSW1 +6918,2010-10-16 06:00:00,14040.61,NSW1NSW1 +6919,2010-10-16 07:00:00,15825.75,NSW1NSW1 +6920,2010-10-16 08:00:00,17297.15,NSW1NSW1 +6921,2010-10-16 09:00:00,17754.02,NSW1NSW1 +6922,2010-10-16 10:00:00,17513.03,NSW1NSW1 +6923,2010-10-16 11:00:00,17197.629999999997,NSW1NSW1 +6924,2010-10-16 12:00:00,16745.87,NSW1NSW1 +6925,2010-10-16 13:00:00,16196.880000000001,NSW1NSW1 +6926,2010-10-16 14:00:00,15876.74,NSW1NSW1 +6927,2010-10-16 15:00:00,15884.42,NSW1NSW1 +6928,2010-10-16 16:00:00,15948.39,NSW1NSW1 +6929,2010-10-16 17:00:00,16539.67,NSW1NSW1 +6930,2010-10-16 18:00:00,17091.14,NSW1NSW1 +6931,2010-10-16 19:00:00,17496.47,NSW1NSW1 +6932,2010-10-16 20:00:00,17038.95,NSW1NSW1 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18:00:00,16515.78,NSW1NSW1 +6955,2010-10-17 19:00:00,17210.27,NSW1NSW1 +6956,2010-10-17 20:00:00,16803.94,NSW1NSW1 +6957,2010-10-17 21:00:00,16032.439999999999,NSW1NSW1 +6958,2010-10-17 22:00:00,15524.36,NSW1NSW1 +6959,2010-10-17 23:00:00,14970.99,NSW1NSW1 +6960,2010-10-18 00:00:00,14352.76,NSW1NSW1 +6961,2010-10-18 01:00:00,13858.9,NSW1NSW1 +6962,2010-10-18 02:00:00,13228.17,NSW1NSW1 +6963,2010-10-18 03:00:00,12868.18,NSW1NSW1 +6964,2010-10-18 04:00:00,13222.96,NSW1NSW1 +6965,2010-10-18 05:00:00,14789.6,NSW1NSW1 +6966,2010-10-18 06:00:00,17148.239999999998,NSW1NSW1 +6967,2010-10-18 07:00:00,18418.67,NSW1NSW1 +6968,2010-10-18 08:00:00,18523.589999999997,NSW1NSW1 +6969,2010-10-18 09:00:00,18562.84,NSW1NSW1 +6970,2010-10-18 10:00:00,18416.5,NSW1NSW1 +6971,2010-10-18 11:00:00,18194.27,NSW1NSW1 +6972,2010-10-18 12:00:00,18147.4,NSW1NSW1 +6973,2010-10-18 13:00:00,18172.629999999997,NSW1NSW1 +6974,2010-10-18 14:00:00,17972.06,NSW1NSW1 +6975,2010-10-18 15:00:00,18024.86,NSW1NSW1 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13:00:00,18483.92,NSW1NSW1 +6998,2010-10-19 14:00:00,18158.17,NSW1NSW1 +6999,2010-10-19 15:00:00,18213.04,NSW1NSW1 +7000,2010-10-19 16:00:00,18403.04,NSW1NSW1 +7001,2010-10-19 17:00:00,18729.21,NSW1NSW1 +7002,2010-10-19 18:00:00,18874.6,NSW1NSW1 +7003,2010-10-19 19:00:00,18834.07,NSW1NSW1 +7004,2010-10-19 20:00:00,17907.39,NSW1NSW1 +7005,2010-10-19 21:00:00,17091.96,NSW1NSW1 +7006,2010-10-19 22:00:00,16607.57,NSW1NSW1 +7007,2010-10-19 23:00:00,16207.41,NSW1NSW1 +7008,2010-10-20 00:00:00,15776.560000000001,NSW1NSW1 +7009,2010-10-20 01:00:00,14887.49,NSW1NSW1 +7010,2010-10-20 02:00:00,13719.92,NSW1NSW1 +7011,2010-10-20 03:00:00,13121.69,NSW1NSW1 +7012,2010-10-20 04:00:00,13413.25,NSW1NSW1 +7013,2010-10-20 05:00:00,14930.49,NSW1NSW1 +7014,2010-10-20 06:00:00,17110.03,NSW1NSW1 +7015,2010-10-20 07:00:00,18250.39,NSW1NSW1 +7016,2010-10-20 08:00:00,18256.0,NSW1NSW1 +7017,2010-10-20 09:00:00,18449.489999999998,NSW1NSW1 +7018,2010-10-20 10:00:00,18481.480000000003,NSW1NSW1 +7019,2010-10-20 11:00:00,18290.68,NSW1NSW1 +7020,2010-10-20 12:00:00,18162.21,NSW1NSW1 +7021,2010-10-20 13:00:00,18098.8,NSW1NSW1 +7022,2010-10-20 14:00:00,17958.519999999997,NSW1NSW1 +7023,2010-10-20 15:00:00,17942.35,NSW1NSW1 +7024,2010-10-20 16:00:00,17964.08,NSW1NSW1 +7025,2010-10-20 17:00:00,17736.120000000003,NSW1NSW1 +7026,2010-10-20 18:00:00,17697.03,NSW1NSW1 +7027,2010-10-20 19:00:00,17921.28,NSW1NSW1 +7028,2010-10-20 20:00:00,17212.64,NSW1NSW1 +7029,2010-10-20 21:00:00,16541.22,NSW1NSW1 +7030,2010-10-20 22:00:00,16288.119999999999,NSW1NSW1 +7031,2010-10-20 23:00:00,15918.67,NSW1NSW1 +7032,2010-10-21 00:00:00,15423.89,NSW1NSW1 +7033,2010-10-21 01:00:00,14666.99,NSW1NSW1 +7034,2010-10-21 02:00:00,13549.369999999999,NSW1NSW1 +7035,2010-10-21 03:00:00,13002.650000000001,NSW1NSW1 +7036,2010-10-21 04:00:00,13312.880000000001,NSW1NSW1 +7037,2010-10-21 05:00:00,14807.380000000001,NSW1NSW1 +7038,2010-10-21 06:00:00,16947.6,NSW1NSW1 +7039,2010-10-21 07:00:00,17929.72,NSW1NSW1 +7040,2010-10-21 08:00:00,18129.4,NSW1NSW1 +7041,2010-10-21 09:00:00,18466.35,NSW1NSW1 +7042,2010-10-21 10:00:00,18507.53,NSW1NSW1 +7043,2010-10-21 11:00:00,18511.9,NSW1NSW1 +7044,2010-10-21 12:00:00,18479.69,NSW1NSW1 +7045,2010-10-21 13:00:00,18526.73,NSW1NSW1 +7046,2010-10-21 14:00:00,18407.14,NSW1NSW1 +7047,2010-10-21 15:00:00,18411.95,NSW1NSW1 +7048,2010-10-21 16:00:00,18379.42,NSW1NSW1 +7049,2010-10-21 17:00:00,18127.519999999997,NSW1NSW1 +7050,2010-10-21 18:00:00,18207.92,NSW1NSW1 +7051,2010-10-21 19:00:00,18420.36,NSW1NSW1 +7052,2010-10-21 20:00:00,17625.510000000002,NSW1NSW1 +7053,2010-10-21 21:00:00,16673.989999999998,NSW1NSW1 +7054,2010-10-21 22:00:00,16377.14,NSW1NSW1 +7055,2010-10-21 23:00:00,15925.35,NSW1NSW1 +7056,2010-10-22 00:00:00,15382.56,NSW1NSW1 +7057,2010-10-22 01:00:00,14575.599999999999,NSW1NSW1 +7058,2010-10-22 02:00:00,13495.41,NSW1NSW1 +7059,2010-10-22 03:00:00,13048.279999999999,NSW1NSW1 +7060,2010-10-22 04:00:00,13300.41,NSW1NSW1 +7061,2010-10-22 05:00:00,14697.65,NSW1NSW1 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03:00:00,12670.17,NSW1NSW1 +7084,2010-10-23 04:00:00,12662.47,NSW1NSW1 +7085,2010-10-23 05:00:00,13153.73,NSW1NSW1 +7086,2010-10-23 06:00:00,14137.720000000001,NSW1NSW1 +7087,2010-10-23 07:00:00,15608.3,NSW1NSW1 +7088,2010-10-23 08:00:00,16810.51,NSW1NSW1 +7089,2010-10-23 09:00:00,17163.02,NSW1NSW1 +7090,2010-10-23 10:00:00,17122.949999999997,NSW1NSW1 +7091,2010-10-23 11:00:00,17004.89,NSW1NSW1 +7092,2010-10-23 12:00:00,16884.28,NSW1NSW1 +7093,2010-10-23 13:00:00,16588.92,NSW1NSW1 +7094,2010-10-23 14:00:00,16313.77,NSW1NSW1 +7095,2010-10-23 15:00:00,16293.75,NSW1NSW1 +7096,2010-10-23 16:00:00,16261.45,NSW1NSW1 +7097,2010-10-23 17:00:00,16500.23,NSW1NSW1 +7098,2010-10-23 18:00:00,16578.940000000002,NSW1NSW1 +7099,2010-10-23 19:00:00,16618.71,NSW1NSW1 +7100,2010-10-23 20:00:00,16118.279999999999,NSW1NSW1 +7101,2010-10-23 21:00:00,15615.58,NSW1NSW1 +7102,2010-10-23 22:00:00,15388.67,NSW1NSW1 +7103,2010-10-23 23:00:00,14743.79,NSW1NSW1 +7104,2010-10-24 00:00:00,14259.69,NSW1NSW1 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22:00:00,15558.77,NSW1NSW1 +7127,2010-10-24 23:00:00,14918.63,NSW1NSW1 +7128,2010-10-25 00:00:00,14284.869999999999,NSW1NSW1 +7129,2010-10-25 01:00:00,13716.92,NSW1NSW1 +7130,2010-10-25 02:00:00,12994.16,NSW1NSW1 +7131,2010-10-25 03:00:00,12671.51,NSW1NSW1 +7132,2010-10-25 04:00:00,13061.9,NSW1NSW1 +7133,2010-10-25 05:00:00,14698.64,NSW1NSW1 +7134,2010-10-25 06:00:00,17095.41,NSW1NSW1 +7135,2010-10-25 07:00:00,18568.989999999998,NSW1NSW1 +7136,2010-10-25 08:00:00,18706.82,NSW1NSW1 +7137,2010-10-25 09:00:00,19061.94,NSW1NSW1 +7138,2010-10-25 10:00:00,18970.59,NSW1NSW1 +7139,2010-10-25 11:00:00,18760.63,NSW1NSW1 +7140,2010-10-25 12:00:00,18529.48,NSW1NSW1 +7141,2010-10-25 13:00:00,18400.6,NSW1NSW1 +7142,2010-10-25 14:00:00,18205.379999999997,NSW1NSW1 +7143,2010-10-25 15:00:00,18219.910000000003,NSW1NSW1 +7144,2010-10-25 16:00:00,18336.89,NSW1NSW1 +7145,2010-10-25 17:00:00,18171.61,NSW1NSW1 +7146,2010-10-25 18:00:00,18051.03,NSW1NSW1 +7147,2010-10-25 19:00:00,18302.129999999997,NSW1NSW1 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16:00:00,18497.010000000002,NSW1NSW1 +7169,2010-10-26 17:00:00,18164.02,NSW1NSW1 +7170,2010-10-26 18:00:00,17790.13,NSW1NSW1 +7171,2010-10-26 19:00:00,17968.75,NSW1NSW1 +7172,2010-10-26 20:00:00,17281.22,NSW1NSW1 +7173,2010-10-26 21:00:00,16588.2,NSW1NSW1 +7174,2010-10-26 22:00:00,16271.68,NSW1NSW1 +7175,2010-10-26 23:00:00,15954.67,NSW1NSW1 +7176,2010-10-27 00:00:00,15569.17,NSW1NSW1 +7177,2010-10-27 01:00:00,14669.58,NSW1NSW1 +7178,2010-10-27 02:00:00,13540.740000000002,NSW1NSW1 +7179,2010-10-27 03:00:00,13064.599999999999,NSW1NSW1 +7180,2010-10-27 04:00:00,13353.04,NSW1NSW1 +7181,2010-10-27 05:00:00,14770.880000000001,NSW1NSW1 +7182,2010-10-27 06:00:00,16937.18,NSW1NSW1 +7183,2010-10-27 07:00:00,18085.96,NSW1NSW1 +7184,2010-10-27 08:00:00,18411.92,NSW1NSW1 +7185,2010-10-27 09:00:00,18782.02,NSW1NSW1 +7186,2010-10-27 10:00:00,18834.6,NSW1NSW1 +7187,2010-10-27 11:00:00,18641.989999999998,NSW1NSW1 +7188,2010-10-27 12:00:00,18635.67,NSW1NSW1 +7189,2010-10-27 13:00:00,18508.61,NSW1NSW1 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11:00:00,18425.54,NSW1NSW1 +7212,2010-10-28 12:00:00,18391.33,NSW1NSW1 +7213,2010-10-28 13:00:00,18355.309999999998,NSW1NSW1 +7214,2010-10-28 14:00:00,18272.010000000002,NSW1NSW1 +7215,2010-10-28 15:00:00,18213.5,NSW1NSW1 +7216,2010-10-28 16:00:00,18193.55,NSW1NSW1 +7217,2010-10-28 17:00:00,18055.95,NSW1NSW1 +7218,2010-10-28 18:00:00,17916.11,NSW1NSW1 +7219,2010-10-28 19:00:00,18078.739999999998,NSW1NSW1 +7220,2010-10-28 20:00:00,17381.89,NSW1NSW1 +7221,2010-10-28 21:00:00,16507.690000000002,NSW1NSW1 +7222,2010-10-28 22:00:00,16152.970000000001,NSW1NSW1 +7223,2010-10-28 23:00:00,15772.099999999999,NSW1NSW1 +7224,2010-10-29 00:00:00,15300.720000000001,NSW1NSW1 +7225,2010-10-29 01:00:00,14407.779999999999,NSW1NSW1 +7226,2010-10-29 02:00:00,13321.220000000001,NSW1NSW1 +7227,2010-10-29 03:00:00,12837.07,NSW1NSW1 +7228,2010-10-29 04:00:00,13122.189999999999,NSW1NSW1 +7229,2010-10-29 05:00:00,14586.35,NSW1NSW1 +7230,2010-10-29 06:00:00,16748.58,NSW1NSW1 +7231,2010-10-29 07:00:00,18064.93,NSW1NSW1 +7232,2010-10-29 08:00:00,18449.510000000002,NSW1NSW1 +7233,2010-10-29 09:00:00,18670.699999999997,NSW1NSW1 +7234,2010-10-29 10:00:00,18931.62,NSW1NSW1 +7235,2010-10-29 11:00:00,18172.62,NSW1NSW1 +7236,2010-10-29 12:00:00,18029.14,NSW1NSW1 +7237,2010-10-29 13:00:00,17962.190000000002,NSW1NSW1 +7238,2010-10-29 14:00:00,18389.68,NSW1NSW1 +7239,2010-10-29 15:00:00,18392.66,NSW1NSW1 +7240,2010-10-29 16:00:00,18327.309999999998,NSW1NSW1 +7241,2010-10-29 17:00:00,17796.29,NSW1NSW1 +7242,2010-10-29 18:00:00,17438.11,NSW1NSW1 +7243,2010-10-29 19:00:00,17621.41,NSW1NSW1 +7244,2010-10-29 20:00:00,17123.86,NSW1NSW1 +7245,2010-10-29 21:00:00,16541.79,NSW1NSW1 +7246,2010-10-29 22:00:00,16440.91,NSW1NSW1 +7247,2010-10-29 23:00:00,16123.27,NSW1NSW1 +7248,2010-10-30 00:00:00,15455.73,NSW1NSW1 +7249,2010-10-30 01:00:00,14532.04,NSW1NSW1 +7250,2010-10-30 02:00:00,13369.740000000002,NSW1NSW1 +7251,2010-10-30 03:00:00,12807.599999999999,NSW1NSW1 +7252,2010-10-30 04:00:00,12838.279999999999,NSW1NSW1 +7253,2010-10-30 05:00:00,13264.05,NSW1NSW1 +7254,2010-10-30 06:00:00,14245.17,NSW1NSW1 +7255,2010-10-30 07:00:00,15770.45,NSW1NSW1 +7256,2010-10-30 08:00:00,17127.93,NSW1NSW1 +7257,2010-10-30 09:00:00,17542.08,NSW1NSW1 +7258,2010-10-30 10:00:00,17325.019999999997,NSW1NSW1 +7259,2010-10-30 11:00:00,17109.120000000003,NSW1NSW1 +7260,2010-10-30 12:00:00,16905.010000000002,NSW1NSW1 +7261,2010-10-30 13:00:00,16644.14,NSW1NSW1 +7262,2010-10-30 14:00:00,16581.07,NSW1NSW1 +7263,2010-10-30 15:00:00,16666.559999999998,NSW1NSW1 +7264,2010-10-30 16:00:00,16682.129999999997,NSW1NSW1 +7265,2010-10-30 17:00:00,16567.690000000002,NSW1NSW1 +7266,2010-10-30 18:00:00,16536.91,NSW1NSW1 +7267,2010-10-30 19:00:00,16642.53,NSW1NSW1 +7268,2010-10-30 20:00:00,16059.009999999998,NSW1NSW1 +7269,2010-10-30 21:00:00,15605.099999999999,NSW1NSW1 +7270,2010-10-30 22:00:00,15378.34,NSW1NSW1 +7271,2010-10-30 23:00:00,14708.58,NSW1NSW1 +7272,2010-10-31 00:00:00,13957.16,NSW1NSW1 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21:00:00,15932.65,NSW1NSW1 +7294,2010-10-31 22:00:00,15458.23,NSW1NSW1 +7295,2010-10-31 23:00:00,14665.88,NSW1NSW1 +7296,2010-11-01 00:00:00,14139.869999999999,NSW1NSW1 +7297,2010-11-01 01:00:00,13531.4,NSW1NSW1 +7298,2010-11-01 02:00:00,12783.08,NSW1NSW1 +7299,2010-11-01 03:00:00,12555.45,NSW1NSW1 +7300,2010-11-01 04:00:00,13005.7,NSW1NSW1 +7301,2010-11-01 05:00:00,14505.94,NSW1NSW1 +7302,2010-11-01 06:00:00,16651.09,NSW1NSW1 +7303,2010-11-01 07:00:00,18014.09,NSW1NSW1 +7304,2010-11-01 08:00:00,18581.83,NSW1NSW1 +7305,2010-11-01 09:00:00,18991.73,NSW1NSW1 +7306,2010-11-01 10:00:00,19005.440000000002,NSW1NSW1 +7307,2010-11-01 11:00:00,18824.79,NSW1NSW1 +7308,2010-11-01 12:00:00,18482.739999999998,NSW1NSW1 +7309,2010-11-01 13:00:00,18576.33,NSW1NSW1 +7310,2010-11-01 14:00:00,18280.66,NSW1NSW1 +7311,2010-11-01 15:00:00,18475.59,NSW1NSW1 +7312,2010-11-01 16:00:00,18887.45,NSW1NSW1 +7313,2010-11-01 17:00:00,19035.120000000003,NSW1NSW1 +7314,2010-11-01 18:00:00,18714.33,NSW1NSW1 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13:00:00,17911.3,NSW1NSW1 +7358,2010-11-03 14:00:00,17867.03,NSW1NSW1 +7359,2010-11-03 15:00:00,17790.21,NSW1NSW1 +7360,2010-11-03 16:00:00,17832.809999999998,NSW1NSW1 +7361,2010-11-03 17:00:00,17697.16,NSW1NSW1 +7362,2010-11-03 18:00:00,17732.41,NSW1NSW1 +7363,2010-11-03 19:00:00,17899.72,NSW1NSW1 +7364,2010-11-03 20:00:00,17325.65,NSW1NSW1 +7365,2010-11-03 21:00:00,16590.94,NSW1NSW1 +7366,2010-11-03 22:00:00,16265.6,NSW1NSW1 +7367,2010-11-03 23:00:00,15960.25,NSW1NSW1 +7368,2010-11-04 00:00:00,15414.34,NSW1NSW1 +7369,2010-11-04 01:00:00,14511.52,NSW1NSW1 +7370,2010-11-04 02:00:00,13455.58,NSW1NSW1 +7371,2010-11-04 03:00:00,12858.0,NSW1NSW1 +7372,2010-11-04 04:00:00,13115.73,NSW1NSW1 +7373,2010-11-04 05:00:00,14599.849999999999,NSW1NSW1 +7374,2010-11-04 06:00:00,16719.28,NSW1NSW1 +7375,2010-11-04 07:00:00,18025.0,NSW1NSW1 +7376,2010-11-04 08:00:00,18233.21,NSW1NSW1 +7377,2010-11-04 09:00:00,18486.25,NSW1NSW1 +7378,2010-11-04 10:00:00,18480.7,NSW1NSW1 +7379,2010-11-04 11:00:00,18207.57,NSW1NSW1 +7380,2010-11-04 12:00:00,17984.879999999997,NSW1NSW1 +7381,2010-11-04 13:00:00,17885.94,NSW1NSW1 +7382,2010-11-04 14:00:00,17756.18,NSW1NSW1 +7383,2010-11-04 15:00:00,17658.66,NSW1NSW1 +7384,2010-11-04 16:00:00,17846.82,NSW1NSW1 +7385,2010-11-04 17:00:00,18175.68,NSW1NSW1 +7386,2010-11-04 18:00:00,18248.57,NSW1NSW1 +7387,2010-11-04 19:00:00,18387.769999999997,NSW1NSW1 +7388,2010-11-04 20:00:00,17731.1,NSW1NSW1 +7389,2010-11-04 21:00:00,16841.45,NSW1NSW1 +7390,2010-11-04 22:00:00,16305.26,NSW1NSW1 +7391,2010-11-04 23:00:00,15512.73,NSW1NSW1 +7392,2010-11-05 00:00:00,15313.45,NSW1NSW1 +7393,2010-11-05 01:00:00,14501.59,NSW1NSW1 +7394,2010-11-05 02:00:00,13415.42,NSW1NSW1 +7395,2010-11-05 03:00:00,12894.36,NSW1NSW1 +7396,2010-11-05 04:00:00,13241.619999999999,NSW1NSW1 +7397,2010-11-05 05:00:00,14604.82,NSW1NSW1 +7398,2010-11-05 06:00:00,16956.800000000003,NSW1NSW1 +7399,2010-11-05 07:00:00,18298.33,NSW1NSW1 +7400,2010-11-05 08:00:00,18430.58,NSW1NSW1 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03:00:00,12230.83,NSW1NSW1 +7444,2010-11-07 04:00:00,12209.86,NSW1NSW1 +7445,2010-11-07 05:00:00,12464.32,NSW1NSW1 +7446,2010-11-07 06:00:00,13139.04,NSW1NSW1 +7447,2010-11-07 07:00:00,14547.15,NSW1NSW1 +7448,2010-11-07 08:00:00,15684.36,NSW1NSW1 +7449,2010-11-07 09:00:00,16245.880000000001,NSW1NSW1 +7450,2010-11-07 10:00:00,16243.11,NSW1NSW1 +7451,2010-11-07 11:00:00,16109.4,NSW1NSW1 +7452,2010-11-07 12:00:00,15738.09,NSW1NSW1 +7453,2010-11-07 13:00:00,15514.32,NSW1NSW1 +7454,2010-11-07 14:00:00,15450.55,NSW1NSW1 +7455,2010-11-07 15:00:00,15621.57,NSW1NSW1 +7456,2010-11-07 16:00:00,15630.810000000001,NSW1NSW1 +7457,2010-11-07 17:00:00,15907.54,NSW1NSW1 +7458,2010-11-07 18:00:00,16180.49,NSW1NSW1 +7459,2010-11-07 19:00:00,16710.22,NSW1NSW1 +7460,2010-11-07 20:00:00,16349.56,NSW1NSW1 +7461,2010-11-07 21:00:00,15503.880000000001,NSW1NSW1 +7462,2010-11-07 22:00:00,15027.029999999999,NSW1NSW1 +7463,2010-11-07 23:00:00,14479.98,NSW1NSW1 +7464,2010-11-08 00:00:00,13966.529999999999,NSW1NSW1 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22:00:00,16205.509999999998,NSW1NSW1 +7487,2010-11-08 23:00:00,15868.32,NSW1NSW1 +7488,2010-11-09 00:00:00,15311.470000000001,NSW1NSW1 +7489,2010-11-09 01:00:00,14426.849999999999,NSW1NSW1 +7490,2010-11-09 02:00:00,13378.400000000001,NSW1NSW1 +7491,2010-11-09 03:00:00,12873.16,NSW1NSW1 +7492,2010-11-09 04:00:00,13252.16,NSW1NSW1 +7493,2010-11-09 05:00:00,14597.95,NSW1NSW1 +7494,2010-11-09 06:00:00,16705.95,NSW1NSW1 +7495,2010-11-09 07:00:00,17963.36,NSW1NSW1 +7496,2010-11-09 08:00:00,18297.54,NSW1NSW1 +7497,2010-11-09 09:00:00,18615.39,NSW1NSW1 +7498,2010-11-09 10:00:00,19019.28,NSW1NSW1 +7499,2010-11-09 11:00:00,19046.0,NSW1NSW1 +7500,2010-11-09 12:00:00,18974.870000000003,NSW1NSW1 +7501,2010-11-09 13:00:00,19024.989999999998,NSW1NSW1 +7502,2010-11-09 14:00:00,18862.3,NSW1NSW1 +7503,2010-11-09 15:00:00,18908.78,NSW1NSW1 +7504,2010-11-09 16:00:00,18875.809999999998,NSW1NSW1 +7505,2010-11-09 17:00:00,18512.22,NSW1NSW1 +7506,2010-11-09 18:00:00,18067.8,NSW1NSW1 +7507,2010-11-09 19:00:00,18133.32,NSW1NSW1 +7508,2010-11-09 20:00:00,17464.510000000002,NSW1NSW1 +7509,2010-11-09 21:00:00,16737.75,NSW1NSW1 +7510,2010-11-09 22:00:00,16415.35,NSW1NSW1 +7511,2010-11-09 23:00:00,15958.25,NSW1NSW1 +7512,2010-11-10 00:00:00,15322.029999999999,NSW1NSW1 +7513,2010-11-10 01:00:00,14426.57,NSW1NSW1 +7514,2010-11-10 02:00:00,13276.380000000001,NSW1NSW1 +7515,2010-11-10 03:00:00,12887.18,NSW1NSW1 +7516,2010-11-10 04:00:00,13250.470000000001,NSW1NSW1 +7517,2010-11-10 05:00:00,14651.14,NSW1NSW1 +7518,2010-11-10 06:00:00,16783.48,NSW1NSW1 +7519,2010-11-10 07:00:00,18099.52,NSW1NSW1 +7520,2010-11-10 08:00:00,18682.85,NSW1NSW1 +7521,2010-11-10 09:00:00,19329.16,NSW1NSW1 +7522,2010-11-10 10:00:00,19585.73,NSW1NSW1 +7523,2010-11-10 11:00:00,19780.35,NSW1NSW1 +7524,2010-11-10 12:00:00,19730.739999999998,NSW1NSW1 +7525,2010-11-10 13:00:00,19876.24,NSW1NSW1 +7526,2010-11-10 14:00:00,19859.4,NSW1NSW1 +7527,2010-11-10 15:00:00,19549.71,NSW1NSW1 +7528,2010-11-10 16:00:00,19324.989999999998,NSW1NSW1 +7529,2010-11-10 17:00:00,18774.61,NSW1NSW1 +7530,2010-11-10 18:00:00,18218.92,NSW1NSW1 +7531,2010-11-10 19:00:00,18207.21,NSW1NSW1 +7532,2010-11-10 20:00:00,17589.95,NSW1NSW1 +7533,2010-11-10 21:00:00,16705.83,NSW1NSW1 +7534,2010-11-10 22:00:00,16270.25,NSW1NSW1 +7535,2010-11-10 23:00:00,15743.7,NSW1NSW1 +7536,2010-11-11 00:00:00,15076.1,NSW1NSW1 +7537,2010-11-11 01:00:00,14130.95,NSW1NSW1 +7538,2010-11-11 02:00:00,13128.029999999999,NSW1NSW1 +7539,2010-11-11 03:00:00,12639.11,NSW1NSW1 +7540,2010-11-11 04:00:00,13107.2,NSW1NSW1 +7541,2010-11-11 05:00:00,14449.970000000001,NSW1NSW1 +7542,2010-11-11 06:00:00,16680.120000000003,NSW1NSW1 +7543,2010-11-11 07:00:00,18076.22,NSW1NSW1 +7544,2010-11-11 08:00:00,18695.64,NSW1NSW1 +7545,2010-11-11 09:00:00,19277.199999999997,NSW1NSW1 +7546,2010-11-11 10:00:00,19485.11,NSW1NSW1 +7547,2010-11-11 11:00:00,19646.33,NSW1NSW1 +7548,2010-11-11 12:00:00,19664.35,NSW1NSW1 +7549,2010-11-11 13:00:00,19859.99,NSW1NSW1 +7550,2010-11-11 14:00:00,19892.879999999997,NSW1NSW1 +7551,2010-11-11 15:00:00,19958.29,NSW1NSW1 +7552,2010-11-11 16:00:00,20079.78,NSW1NSW1 +7553,2010-11-11 17:00:00,19661.28,NSW1NSW1 +7554,2010-11-11 18:00:00,19061.29,NSW1NSW1 +7555,2010-11-11 19:00:00,19025.260000000002,NSW1NSW1 +7556,2010-11-11 20:00:00,18259.29,NSW1NSW1 +7557,2010-11-11 21:00:00,17157.7,NSW1NSW1 +7558,2010-11-11 22:00:00,16597.190000000002,NSW1NSW1 +7559,2010-11-11 23:00:00,15948.279999999999,NSW1NSW1 +7560,2010-11-12 00:00:00,15210.26,NSW1NSW1 +7561,2010-11-12 01:00:00,14276.61,NSW1NSW1 +7562,2010-11-12 02:00:00,13247.55,NSW1NSW1 +7563,2010-11-12 03:00:00,12852.2,NSW1NSW1 +7564,2010-11-12 04:00:00,13238.49,NSW1NSW1 +7565,2010-11-12 05:00:00,14505.07,NSW1NSW1 +7566,2010-11-12 06:00:00,16724.85,NSW1NSW1 +7567,2010-11-12 07:00:00,18176.59,NSW1NSW1 +7568,2010-11-12 08:00:00,19271.88,NSW1NSW1 +7569,2010-11-12 09:00:00,20168.0,NSW1NSW1 +7570,2010-11-12 10:00:00,20681.14,NSW1NSW1 +7571,2010-11-12 11:00:00,20918.129999999997,NSW1NSW1 +7572,2010-11-12 12:00:00,21048.74,NSW1NSW1 +7573,2010-11-12 13:00:00,21294.33,NSW1NSW1 +7574,2010-11-12 14:00:00,21317.63,NSW1NSW1 +7575,2010-11-12 15:00:00,21368.940000000002,NSW1NSW1 +7576,2010-11-12 16:00:00,21161.53,NSW1NSW1 +7577,2010-11-12 17:00:00,20167.260000000002,NSW1NSW1 +7578,2010-11-12 18:00:00,19031.64,NSW1NSW1 +7579,2010-11-12 19:00:00,18672.52,NSW1NSW1 +7580,2010-11-12 20:00:00,18078.2,NSW1NSW1 +7581,2010-11-12 21:00:00,17333.2,NSW1NSW1 +7582,2010-11-12 22:00:00,16914.72,NSW1NSW1 +7583,2010-11-12 23:00:00,16283.579999999998,NSW1NSW1 +7584,2010-11-13 00:00:00,15391.51,NSW1NSW1 +7585,2010-11-13 01:00:00,14309.76,NSW1NSW1 +7586,2010-11-13 02:00:00,13302.99,NSW1NSW1 +7587,2010-11-13 03:00:00,12855.68,NSW1NSW1 +7588,2010-11-13 04:00:00,12881.259999999998,NSW1NSW1 +7589,2010-11-13 05:00:00,13206.27,NSW1NSW1 +7590,2010-11-13 06:00:00,14333.779999999999,NSW1NSW1 +7591,2010-11-13 07:00:00,15923.300000000001,NSW1NSW1 +7592,2010-11-13 08:00:00,17453.050000000003,NSW1NSW1 +7593,2010-11-13 09:00:00,18332.57,NSW1NSW1 +7594,2010-11-13 10:00:00,18627.45,NSW1NSW1 +7595,2010-11-13 11:00:00,18944.260000000002,NSW1NSW1 +7596,2010-11-13 12:00:00,19232.620000000003,NSW1NSW1 +7597,2010-11-13 13:00:00,19328.89,NSW1NSW1 +7598,2010-11-13 14:00:00,19147.510000000002,NSW1NSW1 +7599,2010-11-13 15:00:00,19111.760000000002,NSW1NSW1 +7600,2010-11-13 16:00:00,19028.61,NSW1NSW1 +7601,2010-11-13 17:00:00,18575.9,NSW1NSW1 +7602,2010-11-13 18:00:00,18341.77,NSW1NSW1 +7603,2010-11-13 19:00:00,18226.25,NSW1NSW1 +7604,2010-11-13 20:00:00,17771.68,NSW1NSW1 +7605,2010-11-13 21:00:00,17014.2,NSW1NSW1 +7606,2010-11-13 22:00:00,16498.71,NSW1NSW1 +7607,2010-11-13 23:00:00,15601.02,NSW1NSW1 +7608,2010-11-14 00:00:00,14699.060000000001,NSW1NSW1 +7609,2010-11-14 01:00:00,13784.880000000001,NSW1NSW1 +7610,2010-11-14 02:00:00,12940.34,NSW1NSW1 +7611,2010-11-14 03:00:00,12605.17,NSW1NSW1 +7612,2010-11-14 04:00:00,12583.380000000001,NSW1NSW1 +7613,2010-11-14 05:00:00,12712.42,NSW1NSW1 +7614,2010-11-14 06:00:00,13362.49,NSW1NSW1 +7615,2010-11-14 07:00:00,14847.0,NSW1NSW1 +7616,2010-11-14 08:00:00,16395.58,NSW1NSW1 +7617,2010-11-14 09:00:00,17463.53,NSW1NSW1 +7618,2010-11-14 10:00:00,18132.559999999998,NSW1NSW1 +7619,2010-11-14 11:00:00,18399.16,NSW1NSW1 +7620,2010-11-14 12:00:00,18874.23,NSW1NSW1 +7621,2010-11-14 13:00:00,18946.93,NSW1NSW1 +7622,2010-11-14 14:00:00,18978.879999999997,NSW1NSW1 +7623,2010-11-14 15:00:00,18990.29,NSW1NSW1 +7624,2010-11-14 16:00:00,18996.16,NSW1NSW1 +7625,2010-11-14 17:00:00,19138.04,NSW1NSW1 +7626,2010-11-14 18:00:00,18846.55,NSW1NSW1 +7627,2010-11-14 19:00:00,18901.64,NSW1NSW1 +7628,2010-11-14 20:00:00,18299.550000000003,NSW1NSW1 +7629,2010-11-14 21:00:00,17218.370000000003,NSW1NSW1 +7630,2010-11-14 22:00:00,16393.69,NSW1NSW1 +7631,2010-11-14 23:00:00,15476.029999999999,NSW1NSW1 +7632,2010-11-15 00:00:00,14795.1,NSW1NSW1 +7633,2010-11-15 01:00:00,14125.54,NSW1NSW1 +7634,2010-11-15 02:00:00,13356.43,NSW1NSW1 +7635,2010-11-15 03:00:00,13108.77,NSW1NSW1 +7636,2010-11-15 04:00:00,13594.310000000001,NSW1NSW1 +7637,2010-11-15 05:00:00,14982.830000000002,NSW1NSW1 +7638,2010-11-15 06:00:00,17353.4,NSW1NSW1 +7639,2010-11-15 07:00:00,19037.760000000002,NSW1NSW1 +7640,2010-11-15 08:00:00,19966.8,NSW1NSW1 +7641,2010-11-15 09:00:00,20493.77,NSW1NSW1 +7642,2010-11-15 10:00:00,20552.53,NSW1NSW1 +7643,2010-11-15 11:00:00,20360.190000000002,NSW1NSW1 +7644,2010-11-15 12:00:00,20008.22,NSW1NSW1 +7645,2010-11-15 13:00:00,19726.47,NSW1NSW1 +7646,2010-11-15 14:00:00,19368.22,NSW1NSW1 +7647,2010-11-15 15:00:00,19296.449999999997,NSW1NSW1 +7648,2010-11-15 16:00:00,19241.37,NSW1NSW1 +7649,2010-11-15 17:00:00,18937.72,NSW1NSW1 +7650,2010-11-15 18:00:00,18418.5,NSW1NSW1 +7651,2010-11-15 19:00:00,17969.21,NSW1NSW1 +7652,2010-11-15 20:00:00,17280.14,NSW1NSW1 +7653,2010-11-15 21:00:00,16544.83,NSW1NSW1 +7654,2010-11-15 22:00:00,16275.23,NSW1NSW1 +7655,2010-11-15 23:00:00,15807.619999999999,NSW1NSW1 +7656,2010-11-16 00:00:00,15236.19,NSW1NSW1 +7657,2010-11-16 01:00:00,14296.91,NSW1NSW1 +7658,2010-11-16 02:00:00,13327.0,NSW1NSW1 +7659,2010-11-16 03:00:00,12983.42,NSW1NSW1 +7660,2010-11-16 04:00:00,13322.900000000001,NSW1NSW1 +7661,2010-11-16 05:00:00,14738.42,NSW1NSW1 +7662,2010-11-16 06:00:00,16891.08,NSW1NSW1 +7663,2010-11-16 07:00:00,18225.52,NSW1NSW1 +7664,2010-11-16 08:00:00,18645.39,NSW1NSW1 +7665,2010-11-16 09:00:00,19052.309999999998,NSW1NSW1 +7666,2010-11-16 10:00:00,19150.620000000003,NSW1NSW1 +7667,2010-11-16 11:00:00,19190.44,NSW1NSW1 +7668,2010-11-16 12:00:00,18914.690000000002,NSW1NSW1 +7669,2010-11-16 13:00:00,18875.54,NSW1NSW1 +7670,2010-11-16 14:00:00,18722.48,NSW1NSW1 +7671,2010-11-16 15:00:00,18792.8,NSW1NSW1 +7672,2010-11-16 16:00:00,18710.0,NSW1NSW1 +7673,2010-11-16 17:00:00,18176.25,NSW1NSW1 +7674,2010-11-16 18:00:00,17778.260000000002,NSW1NSW1 +7675,2010-11-16 19:00:00,17826.48,NSW1NSW1 +7676,2010-11-16 20:00:00,17199.3,NSW1NSW1 +7677,2010-11-16 21:00:00,16541.39,NSW1NSW1 +7678,2010-11-16 22:00:00,16161.310000000001,NSW1NSW1 +7679,2010-11-16 23:00:00,15674.24,NSW1NSW1 +7680,2010-11-17 00:00:00,15072.83,NSW1NSW1 +7681,2010-11-17 01:00:00,14273.43,NSW1NSW1 +7682,2010-11-17 02:00:00,13169.67,NSW1NSW1 +7683,2010-11-17 03:00:00,12758.4,NSW1NSW1 +7684,2010-11-17 04:00:00,13123.77,NSW1NSW1 +7685,2010-11-17 05:00:00,14546.029999999999,NSW1NSW1 +7686,2010-11-17 06:00:00,16681.07,NSW1NSW1 +7687,2010-11-17 07:00:00,17932.08,NSW1NSW1 +7688,2010-11-17 08:00:00,18420.75,NSW1NSW1 +7689,2010-11-17 09:00:00,18797.91,NSW1NSW1 +7690,2010-11-17 10:00:00,18792.379999999997,NSW1NSW1 +7691,2010-11-17 11:00:00,18657.739999999998,NSW1NSW1 +7692,2010-11-17 12:00:00,18597.11,NSW1NSW1 +7693,2010-11-17 13:00:00,18544.72,NSW1NSW1 +7694,2010-11-17 14:00:00,18354.050000000003,NSW1NSW1 +7695,2010-11-17 15:00:00,18339.67,NSW1NSW1 +7696,2010-11-17 16:00:00,18294.07,NSW1NSW1 +7697,2010-11-17 17:00:00,17892.32,NSW1NSW1 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15:00:00,18706.59,NSW1NSW1 +7720,2010-11-18 16:00:00,18627.0,NSW1NSW1 +7721,2010-11-18 17:00:00,18299.43,NSW1NSW1 +7722,2010-11-18 18:00:00,17796.22,NSW1NSW1 +7723,2010-11-18 19:00:00,18083.32,NSW1NSW1 +7724,2010-11-18 20:00:00,17523.27,NSW1NSW1 +7725,2010-11-18 21:00:00,16594.92,NSW1NSW1 +7726,2010-11-18 22:00:00,16196.91,NSW1NSW1 +7727,2010-11-18 23:00:00,15599.93,NSW1NSW1 +7728,2010-11-19 00:00:00,14899.150000000001,NSW1NSW1 +7729,2010-11-19 01:00:00,14067.51,NSW1NSW1 +7730,2010-11-19 02:00:00,13066.03,NSW1NSW1 +7731,2010-11-19 03:00:00,12690.05,NSW1NSW1 +7732,2010-11-19 04:00:00,13048.55,NSW1NSW1 +7733,2010-11-19 05:00:00,14434.84,NSW1NSW1 +7734,2010-11-19 06:00:00,16572.28,NSW1NSW1 +7735,2010-11-19 07:00:00,17930.190000000002,NSW1NSW1 +7736,2010-11-19 08:00:00,18355.71,NSW1NSW1 +7737,2010-11-19 09:00:00,18653.2,NSW1NSW1 +7738,2010-11-19 10:00:00,18582.86,NSW1NSW1 +7739,2010-11-19 11:00:00,18471.08,NSW1NSW1 +7740,2010-11-19 12:00:00,18311.66,NSW1NSW1 +7741,2010-11-19 13:00:00,18141.54,NSW1NSW1 +7742,2010-11-19 14:00:00,17685.35,NSW1NSW1 +7743,2010-11-19 15:00:00,17618.050000000003,NSW1NSW1 +7744,2010-11-19 16:00:00,17649.58,NSW1NSW1 +7745,2010-11-19 17:00:00,17276.34,NSW1NSW1 +7746,2010-11-19 18:00:00,17013.0,NSW1NSW1 +7747,2010-11-19 19:00:00,17082.77,NSW1NSW1 +7748,2010-11-19 20:00:00,16636.41,NSW1NSW1 +7749,2010-11-19 21:00:00,16030.810000000001,NSW1NSW1 +7750,2010-11-19 22:00:00,16089.73,NSW1NSW1 +7751,2010-11-19 23:00:00,15892.130000000001,NSW1NSW1 +7752,2010-11-20 00:00:00,15197.82,NSW1NSW1 +7753,2010-11-20 01:00:00,14217.84,NSW1NSW1 +7754,2010-11-20 02:00:00,13073.630000000001,NSW1NSW1 +7755,2010-11-20 03:00:00,12581.79,NSW1NSW1 +7756,2010-11-20 04:00:00,12653.7,NSW1NSW1 +7757,2010-11-20 05:00:00,12997.39,NSW1NSW1 +7758,2010-11-20 06:00:00,14080.88,NSW1NSW1 +7759,2010-11-20 07:00:00,15561.99,NSW1NSW1 +7760,2010-11-20 08:00:00,16686.11,NSW1NSW1 +7761,2010-11-20 09:00:00,17039.699999999997,NSW1NSW1 +7762,2010-11-20 10:00:00,16948.17,NSW1NSW1 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04:00:00,13229.16,NSW1NSW1 +7829,2010-11-23 05:00:00,14395.630000000001,NSW1NSW1 +7830,2010-11-23 06:00:00,16569.9,NSW1NSW1 +7831,2010-11-23 07:00:00,17899.91,NSW1NSW1 +7832,2010-11-23 08:00:00,18641.4,NSW1NSW1 +7833,2010-11-23 09:00:00,19180.989999999998,NSW1NSW1 +7834,2010-11-23 10:00:00,19385.34,NSW1NSW1 +7835,2010-11-23 11:00:00,19436.39,NSW1NSW1 +7836,2010-11-23 12:00:00,19553.69,NSW1NSW1 +7837,2010-11-23 13:00:00,19550.02,NSW1NSW1 +7838,2010-11-23 14:00:00,19604.53,NSW1NSW1 +7839,2010-11-23 15:00:00,19701.36,NSW1NSW1 +7840,2010-11-23 16:00:00,19655.86,NSW1NSW1 +7841,2010-11-23 17:00:00,19153.36,NSW1NSW1 +7842,2010-11-23 18:00:00,18365.190000000002,NSW1NSW1 +7843,2010-11-23 19:00:00,18086.04,NSW1NSW1 +7844,2010-11-23 20:00:00,17688.489999999998,NSW1NSW1 +7845,2010-11-23 21:00:00,16843.05,NSW1NSW1 +7846,2010-11-23 22:00:00,16449.22,NSW1NSW1 +7847,2010-11-23 23:00:00,15971.220000000001,NSW1NSW1 +7848,2010-11-24 00:00:00,15275.1,NSW1NSW1 +7849,2010-11-24 01:00:00,14410.7,NSW1NSW1 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23:00:00,16054.7,NSW1NSW1 +7872,2010-11-25 00:00:00,15313.73,NSW1NSW1 +7873,2010-11-25 01:00:00,14362.55,NSW1NSW1 +7874,2010-11-25 02:00:00,13348.54,NSW1NSW1 +7875,2010-11-25 03:00:00,12975.49,NSW1NSW1 +7876,2010-11-25 04:00:00,13349.44,NSW1NSW1 +7877,2010-11-25 05:00:00,14686.009999999998,NSW1NSW1 +7878,2010-11-25 06:00:00,16879.940000000002,NSW1NSW1 +7879,2010-11-25 07:00:00,18460.92,NSW1NSW1 +7880,2010-11-25 08:00:00,19270.69,NSW1NSW1 +7881,2010-11-25 09:00:00,19867.989999999998,NSW1NSW1 +7882,2010-11-25 10:00:00,20416.12,NSW1NSW1 +7883,2010-11-25 11:00:00,20751.0,NSW1NSW1 +7884,2010-11-25 12:00:00,20817.93,NSW1NSW1 +7885,2010-11-25 13:00:00,21060.8,NSW1NSW1 +7886,2010-11-25 14:00:00,21294.230000000003,NSW1NSW1 +7887,2010-11-25 15:00:00,21387.5,NSW1NSW1 +7888,2010-11-25 16:00:00,21220.21,NSW1NSW1 +7889,2010-11-25 17:00:00,20585.15,NSW1NSW1 +7890,2010-11-25 18:00:00,19703.67,NSW1NSW1 +7891,2010-11-25 19:00:00,19391.739999999998,NSW1NSW1 +7892,2010-11-25 20:00:00,18706.15,NSW1NSW1 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17:00:00,19372.09,NSW1NSW1 +7914,2010-11-26 18:00:00,18359.129999999997,NSW1NSW1 +7915,2010-11-26 19:00:00,18123.67,NSW1NSW1 +7916,2010-11-26 20:00:00,17802.3,NSW1NSW1 +7917,2010-11-26 21:00:00,17111.79,NSW1NSW1 +7918,2010-11-26 22:00:00,16791.78,NSW1NSW1 +7919,2010-11-26 23:00:00,16251.550000000001,NSW1NSW1 +7920,2010-11-27 00:00:00,15396.720000000001,NSW1NSW1 +7921,2010-11-27 01:00:00,14407.82,NSW1NSW1 +7922,2010-11-27 02:00:00,13417.25,NSW1NSW1 +7923,2010-11-27 03:00:00,12963.39,NSW1NSW1 +7924,2010-11-27 04:00:00,12955.46,NSW1NSW1 +7925,2010-11-27 05:00:00,13404.73,NSW1NSW1 +7926,2010-11-27 06:00:00,14555.17,NSW1NSW1 +7927,2010-11-27 07:00:00,16178.01,NSW1NSW1 +7928,2010-11-27 08:00:00,17569.629999999997,NSW1NSW1 +7929,2010-11-27 09:00:00,18210.58,NSW1NSW1 +7930,2010-11-27 10:00:00,18435.79,NSW1NSW1 +7931,2010-11-27 11:00:00,18504.010000000002,NSW1NSW1 +7932,2010-11-27 12:00:00,18374.15,NSW1NSW1 +7933,2010-11-27 13:00:00,18420.9,NSW1NSW1 +7934,2010-11-27 14:00:00,18316.98,NSW1NSW1 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12:00:00,16436.18,NSW1NSW1 +7957,2010-11-28 13:00:00,16199.99,NSW1NSW1 +7958,2010-11-28 14:00:00,16216.72,NSW1NSW1 +7959,2010-11-28 15:00:00,16191.630000000001,NSW1NSW1 +7960,2010-11-28 16:00:00,16403.03,NSW1NSW1 +7961,2010-11-28 17:00:00,16594.559999999998,NSW1NSW1 +7962,2010-11-28 18:00:00,16420.38,NSW1NSW1 +7963,2010-11-28 19:00:00,16508.53,NSW1NSW1 +7964,2010-11-28 20:00:00,16325.4,NSW1NSW1 +7965,2010-11-28 21:00:00,15690.189999999999,NSW1NSW1 +7966,2010-11-28 22:00:00,15043.18,NSW1NSW1 +7967,2010-11-28 23:00:00,14322.08,NSW1NSW1 +7968,2010-11-29 00:00:00,13835.4,NSW1NSW1 +7969,2010-11-29 01:00:00,13269.85,NSW1NSW1 +7970,2010-11-29 02:00:00,12633.939999999999,NSW1NSW1 +7971,2010-11-29 03:00:00,12546.89,NSW1NSW1 +7972,2010-11-29 04:00:00,12809.1,NSW1NSW1 +7973,2010-11-29 05:00:00,14107.6,NSW1NSW1 +7974,2010-11-29 06:00:00,16265.15,NSW1NSW1 +7975,2010-11-29 07:00:00,17860.13,NSW1NSW1 +7976,2010-11-29 08:00:00,18553.67,NSW1NSW1 +7977,2010-11-29 09:00:00,19039.54,NSW1NSW1 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07:00:00,17961.5,NSW1NSW1 +8000,2010-11-30 08:00:00,18417.36,NSW1NSW1 +8001,2010-11-30 09:00:00,18869.93,NSW1NSW1 +8002,2010-11-30 10:00:00,19031.57,NSW1NSW1 +8003,2010-11-30 11:00:00,19000.309999999998,NSW1NSW1 +8004,2010-11-30 12:00:00,18909.72,NSW1NSW1 +8005,2010-11-30 13:00:00,18857.809999999998,NSW1NSW1 +8006,2010-11-30 14:00:00,18784.38,NSW1NSW1 +8007,2010-11-30 15:00:00,18817.129999999997,NSW1NSW1 +8008,2010-11-30 16:00:00,18912.059999999998,NSW1NSW1 +8009,2010-11-30 17:00:00,18586.65,NSW1NSW1 +8010,2010-11-30 18:00:00,18015.42,NSW1NSW1 +8011,2010-11-30 19:00:00,17832.61,NSW1NSW1 +8012,2010-11-30 20:00:00,17246.71,NSW1NSW1 +8013,2010-11-30 21:00:00,16475.190000000002,NSW1NSW1 +8014,2010-11-30 22:00:00,16082.689999999999,NSW1NSW1 +8015,2010-11-30 23:00:00,15751.39,NSW1NSW1 +8016,2010-12-01 00:00:00,15002.48,NSW1NSW1 +8017,2010-12-01 01:00:00,14172.4,NSW1NSW1 +8018,2010-12-01 02:00:00,13241.21,NSW1NSW1 +8019,2010-12-01 03:00:00,12740.91,NSW1NSW1 +8020,2010-12-01 04:00:00,13139.49,NSW1NSW1 +8021,2010-12-01 05:00:00,14586.24,NSW1NSW1 +8022,2010-12-01 06:00:00,16731.7,NSW1NSW1 +8023,2010-12-01 07:00:00,18292.2,NSW1NSW1 +8024,2010-12-01 08:00:00,18718.0,NSW1NSW1 +8025,2010-12-01 09:00:00,19257.59,NSW1NSW1 +8026,2010-12-01 10:00:00,19371.34,NSW1NSW1 +8027,2010-12-01 11:00:00,19194.059999999998,NSW1NSW1 +8028,2010-12-01 12:00:00,18741.809999999998,NSW1NSW1 +8029,2010-12-01 13:00:00,18663.67,NSW1NSW1 +8030,2010-12-01 14:00:00,18662.07,NSW1NSW1 +8031,2010-12-01 15:00:00,18662.37,NSW1NSW1 +8032,2010-12-01 16:00:00,18734.16,NSW1NSW1 +8033,2010-12-01 17:00:00,18498.41,NSW1NSW1 +8034,2010-12-01 18:00:00,17950.69,NSW1NSW1 +8035,2010-12-01 19:00:00,17664.96,NSW1NSW1 +8036,2010-12-01 20:00:00,17153.15,NSW1NSW1 +8037,2010-12-01 21:00:00,16358.99,NSW1NSW1 +8038,2010-12-01 22:00:00,16122.67,NSW1NSW1 +8039,2010-12-01 23:00:00,15739.48,NSW1NSW1 +8040,2010-12-02 00:00:00,15135.83,NSW1NSW1 +8041,2010-12-02 01:00:00,14251.21,NSW1NSW1 +8042,2010-12-02 02:00:00,13192.45,NSW1NSW1 +8043,2010-12-02 03:00:00,12774.189999999999,NSW1NSW1 +8044,2010-12-02 04:00:00,13170.9,NSW1NSW1 +8045,2010-12-02 05:00:00,14402.25,NSW1NSW1 +8046,2010-12-02 06:00:00,16491.65,NSW1NSW1 +8047,2010-12-02 07:00:00,18035.739999999998,NSW1NSW1 +8048,2010-12-02 08:00:00,18680.129999999997,NSW1NSW1 +8049,2010-12-02 09:00:00,19296.75,NSW1NSW1 +8050,2010-12-02 10:00:00,19399.79,NSW1NSW1 +8051,2010-12-02 11:00:00,19400.18,NSW1NSW1 +8052,2010-12-02 12:00:00,19332.16,NSW1NSW1 +8053,2010-12-02 13:00:00,19416.03,NSW1NSW1 +8054,2010-12-02 14:00:00,19155.879999999997,NSW1NSW1 +8055,2010-12-02 15:00:00,19049.870000000003,NSW1NSW1 +8056,2010-12-02 16:00:00,18977.809999999998,NSW1NSW1 +8057,2010-12-02 17:00:00,18685.81,NSW1NSW1 +8058,2010-12-02 18:00:00,18071.1,NSW1NSW1 +8059,2010-12-02 19:00:00,17977.58,NSW1NSW1 +8060,2010-12-02 20:00:00,17598.5,NSW1NSW1 +8061,2010-12-02 21:00:00,16723.010000000002,NSW1NSW1 +8062,2010-12-02 22:00:00,16455.800000000003,NSW1NSW1 +8063,2010-12-02 23:00:00,15941.75,NSW1NSW1 +8064,2010-12-03 00:00:00,15236.439999999999,NSW1NSW1 +8065,2010-12-03 01:00:00,14458.439999999999,NSW1NSW1 +8066,2010-12-03 02:00:00,13350.71,NSW1NSW1 +8067,2010-12-03 03:00:00,12950.619999999999,NSW1NSW1 +8068,2010-12-03 04:00:00,13350.93,NSW1NSW1 +8069,2010-12-03 05:00:00,14637.18,NSW1NSW1 +8070,2010-12-03 06:00:00,16468.8,NSW1NSW1 +8071,2010-12-03 07:00:00,17781.64,NSW1NSW1 +8072,2010-12-03 08:00:00,19149.85,NSW1NSW1 +8073,2010-12-03 09:00:00,19981.08,NSW1NSW1 +8074,2010-12-03 10:00:00,20131.24,NSW1NSW1 +8075,2010-12-03 11:00:00,20213.559999999998,NSW1NSW1 +8076,2010-12-03 12:00:00,20110.61,NSW1NSW1 +8077,2010-12-03 13:00:00,20083.48,NSW1NSW1 +8078,2010-12-03 14:00:00,19981.190000000002,NSW1NSW1 +8079,2010-12-03 15:00:00,19857.86,NSW1NSW1 +8080,2010-12-03 16:00:00,19444.15,NSW1NSW1 +8081,2010-12-03 17:00:00,18632.84,NSW1NSW1 +8082,2010-12-03 18:00:00,17837.25,NSW1NSW1 +8083,2010-12-03 19:00:00,17719.980000000003,NSW1NSW1 +8084,2010-12-03 20:00:00,17343.760000000002,NSW1NSW1 +8085,2010-12-03 21:00:00,16827.18,NSW1NSW1 +8086,2010-12-03 22:00:00,16762.739999999998,NSW1NSW1 +8087,2010-12-03 23:00:00,16313.130000000001,NSW1NSW1 +8088,2010-12-04 00:00:00,15551.58,NSW1NSW1 +8089,2010-12-04 01:00:00,14472.16,NSW1NSW1 +8090,2010-12-04 02:00:00,13429.400000000001,NSW1NSW1 +8091,2010-12-04 03:00:00,12881.75,NSW1NSW1 +8092,2010-12-04 04:00:00,12938.5,NSW1NSW1 +8093,2010-12-04 05:00:00,13228.79,NSW1NSW1 +8094,2010-12-04 06:00:00,14386.650000000001,NSW1NSW1 +8095,2010-12-04 07:00:00,15862.130000000001,NSW1NSW1 +8096,2010-12-04 08:00:00,17261.66,NSW1NSW1 +8097,2010-12-04 09:00:00,17866.52,NSW1NSW1 +8098,2010-12-04 10:00:00,17904.239999999998,NSW1NSW1 +8099,2010-12-04 11:00:00,17807.91,NSW1NSW1 +8100,2010-12-04 12:00:00,17537.23,NSW1NSW1 +8101,2010-12-04 13:00:00,17494.19,NSW1NSW1 +8102,2010-12-04 14:00:00,17450.89,NSW1NSW1 +8103,2010-12-04 15:00:00,17347.72,NSW1NSW1 +8104,2010-12-04 16:00:00,17166.02,NSW1NSW1 +8105,2010-12-04 17:00:00,17058.77,NSW1NSW1 +8106,2010-12-04 18:00:00,16837.59,NSW1NSW1 +8107,2010-12-04 19:00:00,16677.54,NSW1NSW1 +8108,2010-12-04 20:00:00,16422.7,NSW1NSW1 +8109,2010-12-04 21:00:00,15953.58,NSW1NSW1 +8110,2010-12-04 22:00:00,15682.349999999999,NSW1NSW1 +8111,2010-12-04 23:00:00,15084.77,NSW1NSW1 +8112,2010-12-05 00:00:00,14291.34,NSW1NSW1 +8113,2010-12-05 01:00:00,13607.27,NSW1NSW1 +8114,2010-12-05 02:00:00,12753.61,NSW1NSW1 +8115,2010-12-05 03:00:00,12385.02,NSW1NSW1 +8116,2010-12-05 04:00:00,12299.75,NSW1NSW1 +8117,2010-12-05 05:00:00,12407.07,NSW1NSW1 +8118,2010-12-05 06:00:00,13143.56,NSW1NSW1 +8119,2010-12-05 07:00:00,14531.35,NSW1NSW1 +8120,2010-12-05 08:00:00,15953.35,NSW1NSW1 +8121,2010-12-05 09:00:00,16844.7,NSW1NSW1 +8122,2010-12-05 10:00:00,17185.02,NSW1NSW1 +8123,2010-12-05 11:00:00,17177.09,NSW1NSW1 +8124,2010-12-05 12:00:00,17097.519999999997,NSW1NSW1 +8125,2010-12-05 13:00:00,16881.09,NSW1NSW1 +8126,2010-12-05 14:00:00,16778.18,NSW1NSW1 +8127,2010-12-05 15:00:00,16878.73,NSW1NSW1 +8128,2010-12-05 16:00:00,16886.4,NSW1NSW1 +8129,2010-12-05 17:00:00,16937.07,NSW1NSW1 +8130,2010-12-05 18:00:00,16804.58,NSW1NSW1 +8131,2010-12-05 19:00:00,16931.08,NSW1NSW1 +8132,2010-12-05 20:00:00,16978.08,NSW1NSW1 +8133,2010-12-05 21:00:00,16213.23,NSW1NSW1 +8134,2010-12-05 22:00:00,15583.810000000001,NSW1NSW1 +8135,2010-12-05 23:00:00,14823.51,NSW1NSW1 +8136,2010-12-06 00:00:00,14189.21,NSW1NSW1 +8137,2010-12-06 01:00:00,13516.369999999999,NSW1NSW1 +8138,2010-12-06 02:00:00,12802.119999999999,NSW1NSW1 +8139,2010-12-06 03:00:00,12677.23,NSW1NSW1 +8140,2010-12-06 04:00:00,13037.24,NSW1NSW1 +8141,2010-12-06 05:00:00,14458.3,NSW1NSW1 +8142,2010-12-06 06:00:00,16846.29,NSW1NSW1 +8143,2010-12-06 07:00:00,18487.73,NSW1NSW1 +8144,2010-12-06 08:00:00,19492.629999999997,NSW1NSW1 +8145,2010-12-06 09:00:00,20300.65,NSW1NSW1 +8146,2010-12-06 10:00:00,20538.99,NSW1NSW1 +8147,2010-12-06 11:00:00,20673.53,NSW1NSW1 +8148,2010-12-06 12:00:00,20630.550000000003,NSW1NSW1 +8149,2010-12-06 13:00:00,20684.04,NSW1NSW1 +8150,2010-12-06 14:00:00,20553.22,NSW1NSW1 +8151,2010-12-06 15:00:00,20572.54,NSW1NSW1 +8152,2010-12-06 16:00:00,20424.72,NSW1NSW1 +8153,2010-12-06 17:00:00,19518.1,NSW1NSW1 +8154,2010-12-06 18:00:00,18597.07,NSW1NSW1 +8155,2010-12-06 19:00:00,18352.92,NSW1NSW1 +8156,2010-12-06 20:00:00,18233.4,NSW1NSW1 +8157,2010-12-06 21:00:00,17377.4,NSW1NSW1 +8158,2010-12-06 22:00:00,16794.7,NSW1NSW1 +8159,2010-12-06 23:00:00,16116.460000000001,NSW1NSW1 +8160,2010-12-07 00:00:00,15384.16,NSW1NSW1 +8161,2010-12-07 01:00:00,14395.64,NSW1NSW1 +8162,2010-12-07 02:00:00,13479.39,NSW1NSW1 +8163,2010-12-07 03:00:00,13166.720000000001,NSW1NSW1 +8164,2010-12-07 04:00:00,13446.310000000001,NSW1NSW1 +8165,2010-12-07 05:00:00,14676.130000000001,NSW1NSW1 +8166,2010-12-07 06:00:00,16904.800000000003,NSW1NSW1 +8167,2010-12-07 07:00:00,18513.16,NSW1NSW1 +8168,2010-12-07 08:00:00,19424.300000000003,NSW1NSW1 +8169,2010-12-07 09:00:00,20133.03,NSW1NSW1 +8170,2010-12-07 10:00:00,20321.81,NSW1NSW1 +8171,2010-12-07 11:00:00,20397.870000000003,NSW1NSW1 +8172,2010-12-07 12:00:00,20531.9,NSW1NSW1 +8173,2010-12-07 13:00:00,20697.260000000002,NSW1NSW1 +8174,2010-12-07 14:00:00,20727.6,NSW1NSW1 +8175,2010-12-07 15:00:00,20743.16,NSW1NSW1 +8176,2010-12-07 16:00:00,20692.23,NSW1NSW1 +8177,2010-12-07 17:00:00,19902.96,NSW1NSW1 +8178,2010-12-07 18:00:00,18839.59,NSW1NSW1 +8179,2010-12-07 19:00:00,18470.5,NSW1NSW1 +8180,2010-12-07 20:00:00,18294.58,NSW1NSW1 +8181,2010-12-07 21:00:00,17407.14,NSW1NSW1 +8182,2010-12-07 22:00:00,16795.3,NSW1NSW1 +8183,2010-12-07 23:00:00,16199.349999999999,NSW1NSW1 +8184,2010-12-08 00:00:00,15410.09,NSW1NSW1 +8185,2010-12-08 01:00:00,14475.82,NSW1NSW1 +8186,2010-12-08 02:00:00,13378.22,NSW1NSW1 +8187,2010-12-08 03:00:00,12941.27,NSW1NSW1 +8188,2010-12-08 04:00:00,13325.52,NSW1NSW1 +8189,2010-12-08 05:00:00,14761.02,NSW1NSW1 +8190,2010-12-08 06:00:00,16970.22,NSW1NSW1 +8191,2010-12-08 07:00:00,18689.27,NSW1NSW1 +8192,2010-12-08 08:00:00,19699.47,NSW1NSW1 +8193,2010-12-08 09:00:00,20515.440000000002,NSW1NSW1 +8194,2010-12-08 10:00:00,20920.550000000003,NSW1NSW1 +8195,2010-12-08 11:00:00,21221.879999999997,NSW1NSW1 +8196,2010-12-08 12:00:00,21287.89,NSW1NSW1 +8197,2010-12-08 13:00:00,21527.29,NSW1NSW1 +8198,2010-12-08 14:00:00,21688.36,NSW1NSW1 +8199,2010-12-08 15:00:00,21963.59,NSW1NSW1 +8200,2010-12-08 16:00:00,21979.879999999997,NSW1NSW1 +8201,2010-12-08 17:00:00,21154.010000000002,NSW1NSW1 +8202,2010-12-08 18:00:00,20021.43,NSW1NSW1 +8203,2010-12-08 19:00:00,19477.36,NSW1NSW1 +8204,2010-12-08 20:00:00,19183.42,NSW1NSW1 +8205,2010-12-08 21:00:00,18147.949999999997,NSW1NSW1 +8206,2010-12-08 22:00:00,17316.35,NSW1NSW1 +8207,2010-12-08 23:00:00,16364.650000000001,NSW1NSW1 +8208,2010-12-09 00:00:00,15541.99,NSW1NSW1 +8209,2010-12-09 01:00:00,14701.83,NSW1NSW1 +8210,2010-12-09 02:00:00,13578.27,NSW1NSW1 +8211,2010-12-09 03:00:00,13201.630000000001,NSW1NSW1 +8212,2010-12-09 04:00:00,13661.689999999999,NSW1NSW1 +8213,2010-12-09 05:00:00,15196.02,NSW1NSW1 +8214,2010-12-09 06:00:00,17443.97,NSW1NSW1 +8215,2010-12-09 07:00:00,19234.46,NSW1NSW1 +8216,2010-12-09 08:00:00,20151.08,NSW1NSW1 +8217,2010-12-09 09:00:00,21296.940000000002,NSW1NSW1 +8218,2010-12-09 10:00:00,21830.25,NSW1NSW1 +8219,2010-12-09 11:00:00,22215.91,NSW1NSW1 +8220,2010-12-09 12:00:00,22334.23,NSW1NSW1 +8221,2010-12-09 13:00:00,22696.8,NSW1NSW1 +8222,2010-12-09 14:00:00,22542.11,NSW1NSW1 +8223,2010-12-09 15:00:00,22712.690000000002,NSW1NSW1 +8224,2010-12-09 16:00:00,22414.73,NSW1NSW1 +8225,2010-12-09 17:00:00,21592.82,NSW1NSW1 +8226,2010-12-09 18:00:00,20572.11,NSW1NSW1 +8227,2010-12-09 19:00:00,20067.7,NSW1NSW1 +8228,2010-12-09 20:00:00,19534.35,NSW1NSW1 +8229,2010-12-09 21:00:00,18288.23,NSW1NSW1 +8230,2010-12-09 22:00:00,17461.49,NSW1NSW1 +8231,2010-12-09 23:00:00,16554.81,NSW1NSW1 +8232,2010-12-10 00:00:00,15549.689999999999,NSW1NSW1 +8233,2010-12-10 01:00:00,14548.66,NSW1NSW1 +8234,2010-12-10 02:00:00,13559.02,NSW1NSW1 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+8257,2010-12-11 01:00:00,14106.61,NSW1NSW1 +8258,2010-12-11 02:00:00,13072.17,NSW1NSW1 +8259,2010-12-11 03:00:00,12671.44,NSW1NSW1 +8260,2010-12-11 04:00:00,12747.73,NSW1NSW1 +8261,2010-12-11 05:00:00,13074.17,NSW1NSW1 +8262,2010-12-11 06:00:00,14281.15,NSW1NSW1 +8263,2010-12-11 07:00:00,15726.869999999999,NSW1NSW1 +8264,2010-12-11 08:00:00,16939.239999999998,NSW1NSW1 +8265,2010-12-11 09:00:00,17373.79,NSW1NSW1 +8266,2010-12-11 10:00:00,17452.739999999998,NSW1NSW1 +8267,2010-12-11 11:00:00,17469.96,NSW1NSW1 +8268,2010-12-11 12:00:00,17383.56,NSW1NSW1 +8269,2010-12-11 13:00:00,17362.63,NSW1NSW1 +8270,2010-12-11 14:00:00,17481.239999999998,NSW1NSW1 +8271,2010-12-11 15:00:00,17626.34,NSW1NSW1 +8272,2010-12-11 16:00:00,17560.42,NSW1NSW1 +8273,2010-12-11 17:00:00,17335.489999999998,NSW1NSW1 +8274,2010-12-11 18:00:00,16859.0,NSW1NSW1 +8275,2010-12-11 19:00:00,16502.83,NSW1NSW1 +8276,2010-12-11 20:00:00,16532.15,NSW1NSW1 +8277,2010-12-11 21:00:00,16015.57,NSW1NSW1 +8278,2010-12-11 22:00:00,15569.369999999999,NSW1NSW1 +8279,2010-12-11 23:00:00,14907.5,NSW1NSW1 +8280,2010-12-12 00:00:00,14012.59,NSW1NSW1 +8281,2010-12-12 01:00:00,13105.54,NSW1NSW1 +8282,2010-12-12 02:00:00,12301.02,NSW1NSW1 +8283,2010-12-12 03:00:00,11966.23,NSW1NSW1 +8284,2010-12-12 04:00:00,11984.52,NSW1NSW1 +8285,2010-12-12 05:00:00,12109.43,NSW1NSW1 +8286,2010-12-12 06:00:00,12927.59,NSW1NSW1 +8287,2010-12-12 07:00:00,14300.04,NSW1NSW1 +8288,2010-12-12 08:00:00,15520.86,NSW1NSW1 +8289,2010-12-12 09:00:00,16358.5,NSW1NSW1 +8290,2010-12-12 10:00:00,16608.83,NSW1NSW1 +8291,2010-12-12 11:00:00,16889.72,NSW1NSW1 +8292,2010-12-12 12:00:00,17002.690000000002,NSW1NSW1 +8293,2010-12-12 13:00:00,17012.86,NSW1NSW1 +8294,2010-12-12 14:00:00,17185.02,NSW1NSW1 +8295,2010-12-12 15:00:00,17530.82,NSW1NSW1 +8296,2010-12-12 16:00:00,17553.89,NSW1NSW1 +8297,2010-12-12 17:00:00,17749.82,NSW1NSW1 +8298,2010-12-12 18:00:00,17626.28,NSW1NSW1 +8299,2010-12-12 19:00:00,17342.489999999998,NSW1NSW1 +8300,2010-12-12 20:00:00,17525.120000000003,NSW1NSW1 +8301,2010-12-12 21:00:00,16727.04,NSW1NSW1 +8302,2010-12-12 22:00:00,15833.0,NSW1NSW1 +8303,2010-12-12 23:00:00,14888.49,NSW1NSW1 +8304,2010-12-13 00:00:00,14197.43,NSW1NSW1 +8305,2010-12-13 01:00:00,13558.28,NSW1NSW1 +8306,2010-12-13 02:00:00,12943.369999999999,NSW1NSW1 +8307,2010-12-13 03:00:00,12729.04,NSW1NSW1 +8308,2010-12-13 04:00:00,13129.55,NSW1NSW1 +8309,2010-12-13 05:00:00,14416.27,NSW1NSW1 +8310,2010-12-13 06:00:00,16608.56,NSW1NSW1 +8311,2010-12-13 07:00:00,18303.21,NSW1NSW1 +8312,2010-12-13 08:00:00,19222.440000000002,NSW1NSW1 +8313,2010-12-13 09:00:00,19862.199999999997,NSW1NSW1 +8314,2010-12-13 10:00:00,20201.739999999998,NSW1NSW1 +8315,2010-12-13 11:00:00,20323.059999999998,NSW1NSW1 +8316,2010-12-13 12:00:00,20380.6,NSW1NSW1 +8317,2010-12-13 13:00:00,20594.72,NSW1NSW1 +8318,2010-12-13 14:00:00,20664.54,NSW1NSW1 +8319,2010-12-13 15:00:00,20819.72,NSW1NSW1 +8320,2010-12-13 16:00:00,20669.65,NSW1NSW1 +8321,2010-12-13 17:00:00,19829.31,NSW1NSW1 +8322,2010-12-13 18:00:00,18569.510000000002,NSW1NSW1 +8323,2010-12-13 19:00:00,17902.66,NSW1NSW1 +8324,2010-12-13 20:00:00,17871.07,NSW1NSW1 +8325,2010-12-13 21:00:00,17122.940000000002,NSW1NSW1 +8326,2010-12-13 22:00:00,16554.32,NSW1NSW1 +8327,2010-12-13 23:00:00,15998.880000000001,NSW1NSW1 +8328,2010-12-14 00:00:00,15222.24,NSW1NSW1 +8329,2010-12-14 01:00:00,14329.75,NSW1NSW1 +8330,2010-12-14 02:00:00,13352.970000000001,NSW1NSW1 +8331,2010-12-14 03:00:00,12974.1,NSW1NSW1 +8332,2010-12-14 04:00:00,13336.2,NSW1NSW1 +8333,2010-12-14 05:00:00,14623.18,NSW1NSW1 +8334,2010-12-14 06:00:00,16699.07,NSW1NSW1 +8335,2010-12-14 07:00:00,18281.38,NSW1NSW1 +8336,2010-12-14 08:00:00,19218.52,NSW1NSW1 +8337,2010-12-14 09:00:00,19930.57,NSW1NSW1 +8338,2010-12-14 10:00:00,20232.38,NSW1NSW1 +8339,2010-12-14 11:00:00,20096.23,NSW1NSW1 +8340,2010-12-14 12:00:00,20419.84,NSW1NSW1 +8341,2010-12-14 13:00:00,20525.75,NSW1NSW1 +8342,2010-12-14 14:00:00,20423.739999999998,NSW1NSW1 +8343,2010-12-14 15:00:00,20481.16,NSW1NSW1 +8344,2010-12-14 16:00:00,20240.67,NSW1NSW1 +8345,2010-12-14 17:00:00,19511.29,NSW1NSW1 +8346,2010-12-14 18:00:00,18468.63,NSW1NSW1 +8347,2010-12-14 19:00:00,17943.55,NSW1NSW1 +8348,2010-12-14 20:00:00,17953.86,NSW1NSW1 +8349,2010-12-14 21:00:00,17148.66,NSW1NSW1 +8350,2010-12-14 22:00:00,16606.48,NSW1NSW1 +8351,2010-12-14 23:00:00,15976.32,NSW1NSW1 +8352,2010-12-15 00:00:00,15171.81,NSW1NSW1 +8353,2010-12-15 01:00:00,14234.06,NSW1NSW1 +8354,2010-12-15 02:00:00,13206.77,NSW1NSW1 +8355,2010-12-15 03:00:00,12933.75,NSW1NSW1 +8356,2010-12-15 04:00:00,13354.060000000001,NSW1NSW1 +8357,2010-12-15 05:00:00,14603.76,NSW1NSW1 +8358,2010-12-15 06:00:00,16659.56,NSW1NSW1 +8359,2010-12-15 07:00:00,18386.22,NSW1NSW1 +8360,2010-12-15 08:00:00,19563.73,NSW1NSW1 +8361,2010-12-15 09:00:00,20214.22,NSW1NSW1 +8362,2010-12-15 10:00:00,20597.96,NSW1NSW1 +8363,2010-12-15 11:00:00,20938.62,NSW1NSW1 +8364,2010-12-15 12:00:00,21104.16,NSW1NSW1 +8365,2010-12-15 13:00:00,21616.379999999997,NSW1NSW1 +8366,2010-12-15 14:00:00,21795.78,NSW1NSW1 +8367,2010-12-15 15:00:00,21880.809999999998,NSW1NSW1 +8368,2010-12-15 16:00:00,21727.36,NSW1NSW1 +8369,2010-12-15 17:00:00,21053.19,NSW1NSW1 +8370,2010-12-15 18:00:00,19986.55,NSW1NSW1 +8371,2010-12-15 19:00:00,19281.86,NSW1NSW1 +8372,2010-12-15 20:00:00,19135.36,NSW1NSW1 +8373,2010-12-15 21:00:00,18151.69,NSW1NSW1 +8374,2010-12-15 22:00:00,17347.44,NSW1NSW1 +8375,2010-12-15 23:00:00,16503.99,NSW1NSW1 +8376,2010-12-16 00:00:00,15580.810000000001,NSW1NSW1 +8377,2010-12-16 01:00:00,14579.64,NSW1NSW1 +8378,2010-12-16 02:00:00,13700.099999999999,NSW1NSW1 +8379,2010-12-16 03:00:00,13359.310000000001,NSW1NSW1 +8380,2010-12-16 04:00:00,13697.77,NSW1NSW1 +8381,2010-12-16 05:00:00,14930.18,NSW1NSW1 +8382,2010-12-16 06:00:00,16953.4,NSW1NSW1 +8383,2010-12-16 07:00:00,18585.620000000003,NSW1NSW1 +8384,2010-12-16 08:00:00,19796.79,NSW1NSW1 +8385,2010-12-16 09:00:00,20621.86,NSW1NSW1 +8386,2010-12-16 10:00:00,20971.79,NSW1NSW1 +8387,2010-12-16 11:00:00,20900.28,NSW1NSW1 +8388,2010-12-16 12:00:00,20821.67,NSW1NSW1 +8389,2010-12-16 13:00:00,20335.25,NSW1NSW1 +8390,2010-12-16 14:00:00,19883.78,NSW1NSW1 +8391,2010-12-16 15:00:00,19287.75,NSW1NSW1 +8392,2010-12-16 16:00:00,19188.190000000002,NSW1NSW1 +8393,2010-12-16 17:00:00,18997.239999999998,NSW1NSW1 +8394,2010-12-16 18:00:00,18207.84,NSW1NSW1 +8395,2010-12-16 19:00:00,17927.83,NSW1NSW1 +8396,2010-12-16 20:00:00,17776.08,NSW1NSW1 +8397,2010-12-16 21:00:00,17013.91,NSW1NSW1 +8398,2010-12-16 22:00:00,16460.17,NSW1NSW1 +8399,2010-12-16 23:00:00,15930.53,NSW1NSW1 +8400,2010-12-17 00:00:00,15111.51,NSW1NSW1 +8401,2010-12-17 01:00:00,14191.01,NSW1NSW1 +8402,2010-12-17 02:00:00,13273.220000000001,NSW1NSW1 +8403,2010-12-17 03:00:00,12934.830000000002,NSW1NSW1 +8404,2010-12-17 04:00:00,13339.55,NSW1NSW1 +8405,2010-12-17 05:00:00,14572.130000000001,NSW1NSW1 +8406,2010-12-17 06:00:00,16468.6,NSW1NSW1 +8407,2010-12-17 07:00:00,17798.95,NSW1NSW1 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+8430,2010-12-18 06:00:00,13717.560000000001,NSW1NSW1 +8431,2010-12-18 07:00:00,15123.939999999999,NSW1NSW1 +8432,2010-12-18 08:00:00,16361.150000000001,NSW1NSW1 +8433,2010-12-18 09:00:00,16802.58,NSW1NSW1 +8434,2010-12-18 10:00:00,16843.62,NSW1NSW1 +8435,2010-12-18 11:00:00,16715.89,NSW1NSW1 +8436,2010-12-18 12:00:00,16434.07,NSW1NSW1 +8437,2010-12-18 13:00:00,16181.4,NSW1NSW1 +8438,2010-12-18 14:00:00,16024.130000000001,NSW1NSW1 +8439,2010-12-18 15:00:00,15884.71,NSW1NSW1 +8440,2010-12-18 16:00:00,15802.89,NSW1NSW1 +8441,2010-12-18 17:00:00,15782.89,NSW1NSW1 +8442,2010-12-18 18:00:00,15576.560000000001,NSW1NSW1 +8443,2010-12-18 19:00:00,15671.58,NSW1NSW1 +8444,2010-12-18 20:00:00,15940.75,NSW1NSW1 +8445,2010-12-18 21:00:00,15607.0,NSW1NSW1 +8446,2010-12-18 22:00:00,15380.95,NSW1NSW1 +8447,2010-12-18 23:00:00,14782.98,NSW1NSW1 +8448,2010-12-19 00:00:00,14082.43,NSW1NSW1 +8449,2010-12-19 01:00:00,13274.95,NSW1NSW1 +8450,2010-12-19 02:00:00,12480.12,NSW1NSW1 +8451,2010-12-19 03:00:00,12090.369999999999,NSW1NSW1 +8452,2010-12-19 04:00:00,12074.46,NSW1NSW1 +8453,2010-12-19 05:00:00,12249.4,NSW1NSW1 +8454,2010-12-19 06:00:00,12861.349999999999,NSW1NSW1 +8455,2010-12-19 07:00:00,14058.9,NSW1NSW1 +8456,2010-12-19 08:00:00,15306.42,NSW1NSW1 +8457,2010-12-19 09:00:00,15896.93,NSW1NSW1 +8458,2010-12-19 10:00:00,15997.619999999999,NSW1NSW1 +8459,2010-12-19 11:00:00,15870.39,NSW1NSW1 +8460,2010-12-19 12:00:00,15716.220000000001,NSW1NSW1 +8461,2010-12-19 13:00:00,15512.310000000001,NSW1NSW1 +8462,2010-12-19 14:00:00,15416.57,NSW1NSW1 +8463,2010-12-19 15:00:00,15602.86,NSW1NSW1 +8464,2010-12-19 16:00:00,15798.259999999998,NSW1NSW1 +8465,2010-12-19 17:00:00,16050.869999999999,NSW1NSW1 +8466,2010-12-19 18:00:00,15770.869999999999,NSW1NSW1 +8467,2010-12-19 19:00:00,15670.689999999999,NSW1NSW1 +8468,2010-12-19 20:00:00,15846.75,NSW1NSW1 +8469,2010-12-19 21:00:00,15204.4,NSW1NSW1 +8470,2010-12-19 22:00:00,14745.31,NSW1NSW1 +8471,2010-12-19 23:00:00,14009.53,NSW1NSW1 +8472,2010-12-20 00:00:00,13410.8,NSW1NSW1 +8473,2010-12-20 01:00:00,12815.35,NSW1NSW1 +8474,2010-12-20 02:00:00,12156.94,NSW1NSW1 +8475,2010-12-20 03:00:00,11960.650000000001,NSW1NSW1 +8476,2010-12-20 04:00:00,12363.310000000001,NSW1NSW1 +8477,2010-12-20 05:00:00,13511.79,NSW1NSW1 +8478,2010-12-20 06:00:00,15303.95,NSW1NSW1 +8479,2010-12-20 07:00:00,16757.07,NSW1NSW1 +8480,2010-12-20 08:00:00,17474.68,NSW1NSW1 +8481,2010-12-20 09:00:00,17839.38,NSW1NSW1 +8482,2010-12-20 10:00:00,17709.47,NSW1NSW1 +8483,2010-12-20 11:00:00,17650.0,NSW1NSW1 +8484,2010-12-20 12:00:00,17452.870000000003,NSW1NSW1 +8485,2010-12-20 13:00:00,17451.69,NSW1NSW1 +8486,2010-12-20 14:00:00,17415.64,NSW1NSW1 +8487,2010-12-20 15:00:00,17309.9,NSW1NSW1 +8488,2010-12-20 16:00:00,17317.67,NSW1NSW1 +8489,2010-12-20 17:00:00,17185.769999999997,NSW1NSW1 +8490,2010-12-20 18:00:00,16810.989999999998,NSW1NSW1 +8491,2010-12-20 19:00:00,16614.760000000002,NSW1NSW1 +8492,2010-12-20 20:00:00,16708.78,NSW1NSW1 +8493,2010-12-20 21:00:00,16137.67,NSW1NSW1 +8494,2010-12-20 22:00:00,15863.93,NSW1NSW1 +8495,2010-12-20 23:00:00,15466.35,NSW1NSW1 +8496,2010-12-21 00:00:00,14786.0,NSW1NSW1 +8497,2010-12-21 01:00:00,13866.5,NSW1NSW1 +8498,2010-12-21 02:00:00,12831.25,NSW1NSW1 +8499,2010-12-21 03:00:00,12456.64,NSW1NSW1 +8500,2010-12-21 04:00:00,12642.07,NSW1NSW1 +8501,2010-12-21 05:00:00,13753.98,NSW1NSW1 +8502,2010-12-21 06:00:00,15322.75,NSW1NSW1 +8503,2010-12-21 07:00:00,16692.34,NSW1NSW1 +8504,2010-12-21 08:00:00,17465.28,NSW1NSW1 +8505,2010-12-21 09:00:00,17904.6,NSW1NSW1 +8506,2010-12-21 10:00:00,18086.699999999997,NSW1NSW1 +8507,2010-12-21 11:00:00,18153.879999999997,NSW1NSW1 +8508,2010-12-21 12:00:00,18123.68,NSW1NSW1 +8509,2010-12-21 13:00:00,18227.64,NSW1NSW1 +8510,2010-12-21 14:00:00,18280.480000000003,NSW1NSW1 +8511,2010-12-21 15:00:00,18400.23,NSW1NSW1 +8512,2010-12-21 16:00:00,18337.97,NSW1NSW1 +8513,2010-12-21 17:00:00,18085.11,NSW1NSW1 +8514,2010-12-21 18:00:00,17504.980000000003,NSW1NSW1 +8515,2010-12-21 19:00:00,17054.7,NSW1NSW1 +8516,2010-12-21 20:00:00,17287.699999999997,NSW1NSW1 +8517,2010-12-21 21:00:00,16722.96,NSW1NSW1 +8518,2010-12-21 22:00:00,16314.74,NSW1NSW1 +8519,2010-12-21 23:00:00,15770.85,NSW1NSW1 +8520,2010-12-22 00:00:00,15042.310000000001,NSW1NSW1 +8521,2010-12-22 01:00:00,14120.17,NSW1NSW1 +8522,2010-12-22 02:00:00,13145.17,NSW1NSW1 +8523,2010-12-22 03:00:00,12656.23,NSW1NSW1 +8524,2010-12-22 04:00:00,12809.31,NSW1NSW1 +8525,2010-12-22 05:00:00,13956.28,NSW1NSW1 +8526,2010-12-22 06:00:00,15695.42,NSW1NSW1 +8527,2010-12-22 07:00:00,17091.0,NSW1NSW1 +8528,2010-12-22 08:00:00,17961.08,NSW1NSW1 +8529,2010-12-22 09:00:00,18578.809999999998,NSW1NSW1 +8530,2010-12-22 10:00:00,18849.85,NSW1NSW1 +8531,2010-12-22 11:00:00,18801.519999999997,NSW1NSW1 +8532,2010-12-22 12:00:00,18813.36,NSW1NSW1 +8533,2010-12-22 13:00:00,18828.010000000002,NSW1NSW1 +8534,2010-12-22 14:00:00,18825.86,NSW1NSW1 +8535,2010-12-22 15:00:00,18821.28,NSW1NSW1 +8536,2010-12-22 16:00:00,18813.42,NSW1NSW1 +8537,2010-12-22 17:00:00,18428.08,NSW1NSW1 +8538,2010-12-22 18:00:00,17692.510000000002,NSW1NSW1 +8539,2010-12-22 19:00:00,17248.54,NSW1NSW1 +8540,2010-12-22 20:00:00,17484.02,NSW1NSW1 +8541,2010-12-22 21:00:00,16889.72,NSW1NSW1 +8542,2010-12-22 22:00:00,16477.78,NSW1NSW1 +8543,2010-12-22 23:00:00,15963.99,NSW1NSW1 +8544,2010-12-23 00:00:00,15238.24,NSW1NSW1 +8545,2010-12-23 01:00:00,14274.4,NSW1NSW1 +8546,2010-12-23 02:00:00,13252.11,NSW1NSW1 +8547,2010-12-23 03:00:00,12332.41,NSW1NSW1 +8548,2010-12-23 04:00:00,12833.68,NSW1NSW1 +8549,2010-12-23 05:00:00,14088.44,NSW1NSW1 +8550,2010-12-23 06:00:00,15576.72,NSW1NSW1 +8551,2010-12-23 07:00:00,16698.45,NSW1NSW1 +8552,2010-12-23 08:00:00,17588.14,NSW1NSW1 +8553,2010-12-23 09:00:00,18667.449999999997,NSW1NSW1 +8554,2010-12-23 10:00:00,18809.53,NSW1NSW1 +8555,2010-12-23 11:00:00,18938.120000000003,NSW1NSW1 +8556,2010-12-23 12:00:00,18879.97,NSW1NSW1 +8557,2010-12-23 13:00:00,19249.82,NSW1NSW1 +8558,2010-12-23 14:00:00,19548.309999999998,NSW1NSW1 +8559,2010-12-23 15:00:00,19885.77,NSW1NSW1 +8560,2010-12-23 16:00:00,19874.89,NSW1NSW1 +8561,2010-12-23 17:00:00,19069.39,NSW1NSW1 +8562,2010-12-23 18:00:00,18045.16,NSW1NSW1 +8563,2010-12-23 19:00:00,17542.34,NSW1NSW1 +8564,2010-12-23 20:00:00,17385.34,NSW1NSW1 +8565,2010-12-23 21:00:00,16681.92,NSW1NSW1 +8566,2010-12-23 22:00:00,16343.02,NSW1NSW1 +8567,2010-12-23 23:00:00,15701.43,NSW1NSW1 +8568,2010-12-24 00:00:00,14860.33,NSW1NSW1 +8569,2010-12-24 01:00:00,13897.099999999999,NSW1NSW1 +8570,2010-12-24 02:00:00,12837.34,NSW1NSW1 +8571,2010-12-24 03:00:00,12493.380000000001,NSW1NSW1 +8572,2010-12-24 04:00:00,12659.810000000001,NSW1NSW1 +8573,2010-12-24 05:00:00,13396.09,NSW1NSW1 +8574,2010-12-24 06:00:00,14745.84,NSW1NSW1 +8575,2010-12-24 07:00:00,16040.400000000001,NSW1NSW1 +8576,2010-12-24 08:00:00,16862.44,NSW1NSW1 +8577,2010-12-24 09:00:00,17622.449999999997,NSW1NSW1 +8578,2010-12-24 10:00:00,17646.02,NSW1NSW1 +8579,2010-12-24 11:00:00,17600.82,NSW1NSW1 +8580,2010-12-24 12:00:00,17336.42,NSW1NSW1 +8581,2010-12-24 13:00:00,17164.27,NSW1NSW1 +8582,2010-12-24 14:00:00,17066.62,NSW1NSW1 +8583,2010-12-24 15:00:00,16991.989999999998,NSW1NSW1 +8584,2010-12-24 16:00:00,16954.98,NSW1NSW1 +8585,2010-12-24 17:00:00,16428.78,NSW1NSW1 +8586,2010-12-24 18:00:00,15603.48,NSW1NSW1 +8587,2010-12-24 19:00:00,15249.51,NSW1NSW1 +8588,2010-12-24 20:00:00,15570.95,NSW1NSW1 +8589,2010-12-24 21:00:00,15477.37,NSW1NSW1 +8590,2010-12-24 22:00:00,15628.35,NSW1NSW1 +8591,2010-12-24 23:00:00,15269.26,NSW1NSW1 +8592,2010-12-25 00:00:00,14499.55,NSW1NSW1 +8593,2010-12-25 01:00:00,13428.42,NSW1NSW1 +8594,2010-12-25 02:00:00,12262.259999999998,NSW1NSW1 +8595,2010-12-25 03:00:00,11658.380000000001,NSW1NSW1 +8596,2010-12-25 04:00:00,11540.189999999999,NSW1NSW1 +8597,2010-12-25 05:00:00,11659.32,NSW1NSW1 +8598,2010-12-25 06:00:00,12399.57,NSW1NSW1 +8599,2010-12-25 07:00:00,13563.099999999999,NSW1NSW1 +8600,2010-12-25 08:00:00,14620.22,NSW1NSW1 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06:00:00,12293.220000000001,NSW1NSW1 +8623,2010-12-26 07:00:00,13323.92,NSW1NSW1 +8624,2010-12-26 08:00:00,14471.869999999999,NSW1NSW1 +8625,2010-12-26 09:00:00,15187.529999999999,NSW1NSW1 +8626,2010-12-26 10:00:00,15356.58,NSW1NSW1 +8627,2010-12-26 11:00:00,15247.07,NSW1NSW1 +8628,2010-12-26 12:00:00,15228.14,NSW1NSW1 +8629,2010-12-26 13:00:00,15107.98,NSW1NSW1 +8630,2010-12-26 14:00:00,15438.220000000001,NSW1NSW1 +8631,2010-12-26 15:00:00,15849.630000000001,NSW1NSW1 +8632,2010-12-26 16:00:00,16046.76,NSW1NSW1 +8633,2010-12-26 17:00:00,16133.32,NSW1NSW1 +8634,2010-12-26 18:00:00,16073.55,NSW1NSW1 +8635,2010-12-26 19:00:00,15881.849999999999,NSW1NSW1 +8636,2010-12-26 20:00:00,15479.060000000001,NSW1NSW1 +8637,2010-12-26 21:00:00,14828.630000000001,NSW1NSW1 +8638,2010-12-26 22:00:00,14590.85,NSW1NSW1 +8639,2010-12-26 23:00:00,14021.900000000001,NSW1NSW1 +8640,2010-12-27 00:00:00,13352.26,NSW1NSW1 +8641,2010-12-27 01:00:00,12728.58,NSW1NSW1 +8642,2010-12-27 02:00:00,12004.34,NSW1NSW1 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00:00:00,13883.279999999999,NSW1NSW1 +8665,2010-12-28 01:00:00,13102.14,NSW1NSW1 +8666,2010-12-28 02:00:00,12071.0,NSW1NSW1 +8667,2010-12-28 03:00:00,11560.779999999999,NSW1NSW1 +8668,2010-12-28 04:00:00,11531.09,NSW1NSW1 +8669,2010-12-28 05:00:00,11778.95,NSW1NSW1 +8670,2010-12-28 06:00:00,12328.68,NSW1NSW1 +8671,2010-12-28 07:00:00,13314.59,NSW1NSW1 +8672,2010-12-28 08:00:00,14411.560000000001,NSW1NSW1 +8673,2010-12-28 09:00:00,15157.42,NSW1NSW1 +8674,2010-12-28 10:00:00,15325.33,NSW1NSW1 +8675,2010-12-28 11:00:00,15279.77,NSW1NSW1 +8676,2010-12-28 12:00:00,15176.029999999999,NSW1NSW1 +8677,2010-12-28 13:00:00,15057.3,NSW1NSW1 +8678,2010-12-28 14:00:00,14987.14,NSW1NSW1 +8679,2010-12-28 15:00:00,14960.349999999999,NSW1NSW1 +8680,2010-12-28 16:00:00,15101.79,NSW1NSW1 +8681,2010-12-28 17:00:00,15369.04,NSW1NSW1 +8682,2010-12-28 18:00:00,15207.779999999999,NSW1NSW1 +8683,2010-12-28 19:00:00,15044.970000000001,NSW1NSW1 +8684,2010-12-28 20:00:00,15088.66,NSW1NSW1 +8685,2010-12-28 21:00:00,14816.52,NSW1NSW1 +8686,2010-12-28 22:00:00,14787.6,NSW1NSW1 +8687,2010-12-28 23:00:00,14538.310000000001,NSW1NSW1 +8688,2010-12-29 00:00:00,14040.939999999999,NSW1NSW1 +8689,2010-12-29 01:00:00,13289.01,NSW1NSW1 +8690,2010-12-29 02:00:00,12292.93,NSW1NSW1 +8691,2010-12-29 03:00:00,11856.89,NSW1NSW1 +8692,2010-12-29 04:00:00,11986.279999999999,NSW1NSW1 +8693,2010-12-29 05:00:00,12530.61,NSW1NSW1 +8694,2010-12-29 06:00:00,13517.439999999999,NSW1NSW1 +8695,2010-12-29 07:00:00,14808.02,NSW1NSW1 +8696,2010-12-29 08:00:00,16128.390000000001,NSW1NSW1 +8697,2010-12-29 09:00:00,16878.879999999997,NSW1NSW1 +8698,2010-12-29 10:00:00,16987.989999999998,NSW1NSW1 +8699,2010-12-29 11:00:00,17084.41,NSW1NSW1 +8700,2010-12-29 12:00:00,17182.29,NSW1NSW1 +8701,2010-12-29 13:00:00,17264.809999999998,NSW1NSW1 +8702,2010-12-29 14:00:00,17433.05,NSW1NSW1 +8703,2010-12-29 15:00:00,17469.54,NSW1NSW1 +8704,2010-12-29 16:00:00,17522.17,NSW1NSW1 +8705,2010-12-29 17:00:00,17890.34,NSW1NSW1 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15:00:00,19434.699999999997,NSW1NSW1 +8728,2010-12-30 16:00:00,19598.52,NSW1NSW1 +8729,2010-12-30 17:00:00,19448.010000000002,NSW1NSW1 +8730,2010-12-30 18:00:00,18822.28,NSW1NSW1 +8731,2010-12-30 19:00:00,18268.1,NSW1NSW1 +8732,2010-12-30 20:00:00,18138.58,NSW1NSW1 +8733,2010-12-30 21:00:00,17248.82,NSW1NSW1 +8734,2010-12-30 22:00:00,16722.52,NSW1NSW1 +8735,2010-12-30 23:00:00,15954.03,NSW1NSW1 +8736,2010-12-31 00:00:00,15012.9,NSW1NSW1 +8737,2010-12-31 01:00:00,14004.45,NSW1NSW1 +8738,2010-12-31 02:00:00,13001.83,NSW1NSW1 +8739,2010-12-31 03:00:00,12604.34,NSW1NSW1 +8740,2010-12-31 04:00:00,12684.19,NSW1NSW1 +8741,2010-12-31 05:00:00,13206.52,NSW1NSW1 +8742,2010-12-31 06:00:00,14256.59,NSW1NSW1 +8743,2010-12-31 07:00:00,15728.43,NSW1NSW1 +8744,2010-12-31 08:00:00,17086.86,NSW1NSW1 +8745,2010-12-31 09:00:00,18459.91,NSW1NSW1 +8746,2010-12-31 10:00:00,19259.05,NSW1NSW1 +8747,2010-12-31 11:00:00,19848.27,NSW1NSW1 +8748,2010-12-31 12:00:00,20374.11,NSW1NSW1 +8749,2010-12-31 13:00:00,20835.91,NSW1NSW1 +8750,2010-12-31 14:00:00,21226.67,NSW1NSW1 +8751,2010-12-31 15:00:00,21528.739999999998,NSW1NSW1 +8752,2010-12-31 16:00:00,21615.190000000002,NSW1NSW1 +8753,2010-12-31 17:00:00,20723.1,NSW1NSW1 +8754,2010-12-31 18:00:00,19178.489999999998,NSW1NSW1 +8755,2010-12-31 19:00:00,17877.98,NSW1NSW1 +8756,2010-12-31 20:00:00,17405.739999999998,NSW1NSW1 +8757,2010-12-31 21:00:00,16976.89,NSW1NSW1 +8758,2010-12-31 22:00:00,16957.7,NSW1NSW1 +8759,2010-12-31 23:00:00,16586.93,NSW1NSW1 +8760,2011-01-01 00:00:00,15907.98,NSW1NSW1 +8761,2011-01-01 01:00:00,14751.869999999999,NSW1NSW1 +8762,2011-01-01 02:00:00,13392.9,NSW1NSW1 +8763,2011-01-01 03:00:00,12723.41,NSW1NSW1 +8764,2011-01-01 04:00:00,12457.36,NSW1NSW1 +8765,2011-01-01 05:00:00,12311.009999999998,NSW1NSW1 +8766,2011-01-01 06:00:00,12626.279999999999,NSW1NSW1 +8767,2011-01-01 07:00:00,13724.18,NSW1NSW1 +8768,2011-01-01 08:00:00,15209.25,NSW1NSW1 +8769,2011-01-01 09:00:00,16531.39,NSW1NSW1 +8770,2011-01-01 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09:00:00,20452.08,NSW1NSW1 +14122,2011-08-12 10:00:00,20069.9,NSW1NSW1 +14123,2011-08-12 11:00:00,19761.02,NSW1NSW1 +14124,2011-08-12 12:00:00,19320.11,NSW1NSW1 +14125,2011-08-12 13:00:00,18932.14,NSW1NSW1 +14126,2011-08-12 14:00:00,18654.36,NSW1NSW1 +14127,2011-08-12 15:00:00,18526.3,NSW1NSW1 +14128,2011-08-12 16:00:00,19035.739999999998,NSW1NSW1 +14129,2011-08-12 17:00:00,20073.629999999997,NSW1NSW1 +14130,2011-08-12 18:00:00,21936.059999999998,NSW1NSW1 +14131,2011-08-12 19:00:00,21815.629999999997,NSW1NSW1 +14132,2011-08-12 20:00:00,21091.15,NSW1NSW1 +14133,2011-08-12 21:00:00,20415.59,NSW1NSW1 +14134,2011-08-12 22:00:00,19731.489999999998,NSW1NSW1 +14135,2011-08-12 23:00:00,19298.0,NSW1NSW1 +14136,2011-08-13 00:00:00,18537.71,NSW1NSW1 +14137,2011-08-13 01:00:00,17553.410000000003,NSW1NSW1 +14138,2011-08-13 02:00:00,16388.010000000002,NSW1NSW1 +14139,2011-08-13 03:00:00,15098.33,NSW1NSW1 +14140,2011-08-13 04:00:00,14452.66,NSW1NSW1 +14141,2011-08-13 05:00:00,14473.810000000001,NSW1NSW1 +14142,2011-08-13 06:00:00,15178.17,NSW1NSW1 +14143,2011-08-13 07:00:00,16710.43,NSW1NSW1 +14144,2011-08-13 08:00:00,18592.42,NSW1NSW1 +14145,2011-08-13 09:00:00,19459.67,NSW1NSW1 +14146,2011-08-13 10:00:00,19131.77,NSW1NSW1 +14147,2011-08-13 11:00:00,18324.05,NSW1NSW1 +14148,2011-08-13 12:00:00,17608.2,NSW1NSW1 +14149,2011-08-13 13:00:00,17151.35,NSW1NSW1 +14150,2011-08-13 14:00:00,16971.28,NSW1NSW1 +14151,2011-08-13 15:00:00,16869.199999999997,NSW1NSW1 +14152,2011-08-13 16:00:00,17314.73,NSW1NSW1 +14153,2011-08-13 17:00:00,18470.47,NSW1NSW1 +14154,2011-08-13 18:00:00,20482.120000000003,NSW1NSW1 +14155,2011-08-13 19:00:00,20290.92,NSW1NSW1 +14156,2011-08-13 20:00:00,19554.75,NSW1NSW1 +14157,2011-08-13 21:00:00,18910.42,NSW1NSW1 +14158,2011-08-13 22:00:00,18321.760000000002,NSW1NSW1 +14159,2011-08-13 23:00:00,17797.59,NSW1NSW1 +14160,2011-08-14 00:00:00,17047.690000000002,NSW1NSW1 +14161,2011-08-14 01:00:00,16055.0,NSW1NSW1 +14162,2011-08-14 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23:00:00,17317.489999999998,NSW1NSW1 +14184,2011-08-15 00:00:00,16499.42,NSW1NSW1 +14185,2011-08-15 01:00:00,15718.75,NSW1NSW1 +14186,2011-08-15 02:00:00,14967.72,NSW1NSW1 +14187,2011-08-15 03:00:00,14028.49,NSW1NSW1 +14188,2011-08-15 04:00:00,13829.77,NSW1NSW1 +14189,2011-08-15 05:00:00,14448.15,NSW1NSW1 +14190,2011-08-15 06:00:00,16567.35,NSW1NSW1 +14191,2011-08-15 07:00:00,19717.84,NSW1NSW1 +14192,2011-08-15 08:00:00,21113.66,NSW1NSW1 +14193,2011-08-15 09:00:00,20670.39,NSW1NSW1 +14194,2011-08-15 10:00:00,20241.57,NSW1NSW1 +14195,2011-08-15 11:00:00,19591.059999999998,NSW1NSW1 +14196,2011-08-15 12:00:00,19018.93,NSW1NSW1 +14197,2011-08-15 13:00:00,18912.89,NSW1NSW1 +14198,2011-08-15 14:00:00,18877.18,NSW1NSW1 +14199,2011-08-15 15:00:00,18849.79,NSW1NSW1 +14200,2011-08-15 16:00:00,19244.29,NSW1NSW1 +14201,2011-08-15 17:00:00,20674.190000000002,NSW1NSW1 +14202,2011-08-15 18:00:00,22638.58,NSW1NSW1 +14203,2011-08-15 19:00:00,22265.23,NSW1NSW1 +14204,2011-08-15 20:00:00,21249.15,NSW1NSW1 +14205,2011-08-15 21:00:00,20430.67,NSW1NSW1 +14206,2011-08-15 22:00:00,19293.19,NSW1NSW1 +14207,2011-08-15 23:00:00,18354.5,NSW1NSW1 +14208,2011-08-16 00:00:00,17809.48,NSW1NSW1 +14209,2011-08-16 01:00:00,17059.800000000003,NSW1NSW1 +14210,2011-08-16 02:00:00,16039.82,NSW1NSW1 +14211,2011-08-16 03:00:00,14849.11,NSW1NSW1 +14212,2011-08-16 04:00:00,14393.33,NSW1NSW1 +14213,2011-08-16 05:00:00,14854.83,NSW1NSW1 +14214,2011-08-16 06:00:00,16879.32,NSW1NSW1 +14215,2011-08-16 07:00:00,19711.55,NSW1NSW1 +14216,2011-08-16 08:00:00,20604.010000000002,NSW1NSW1 +14217,2011-08-16 09:00:00,20118.300000000003,NSW1NSW1 +14218,2011-08-16 10:00:00,19701.71,NSW1NSW1 +14219,2011-08-16 11:00:00,19136.949999999997,NSW1NSW1 +14220,2011-08-16 12:00:00,18745.56,NSW1NSW1 +14221,2011-08-16 13:00:00,18595.17,NSW1NSW1 +14222,2011-08-16 14:00:00,18267.03,NSW1NSW1 +14223,2011-08-16 15:00:00,18158.43,NSW1NSW1 +14224,2011-08-16 16:00:00,18562.86,NSW1NSW1 +14225,2011-08-16 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16:00:00,17018.96,NSW1NSW1 +16193,2011-11-06 17:00:00,17309.97,NSW1NSW1 +16194,2011-11-06 18:00:00,17323.84,NSW1NSW1 +16195,2011-11-06 19:00:00,17496.04,NSW1NSW1 +16196,2011-11-06 20:00:00,16965.0,NSW1NSW1 +16197,2011-11-06 21:00:00,15946.119999999999,NSW1NSW1 +16198,2011-11-06 22:00:00,15313.77,NSW1NSW1 +16199,2011-11-06 23:00:00,14683.419999999998,NSW1NSW1 +16200,2011-11-07 00:00:00,14159.1,NSW1NSW1 +16201,2011-11-07 01:00:00,13587.29,NSW1NSW1 +16202,2011-11-07 02:00:00,12816.39,NSW1NSW1 +16203,2011-11-07 03:00:00,12528.3,NSW1NSW1 +16204,2011-11-07 04:00:00,12913.990000000002,NSW1NSW1 +16205,2011-11-07 05:00:00,14317.25,NSW1NSW1 +16206,2011-11-07 06:00:00,16434.59,NSW1NSW1 +16207,2011-11-07 07:00:00,18040.35,NSW1NSW1 +16208,2011-11-07 08:00:00,19018.33,NSW1NSW1 +16209,2011-11-07 09:00:00,19822.25,NSW1NSW1 +16210,2011-11-07 10:00:00,20280.56,NSW1NSW1 +16211,2011-11-07 11:00:00,20558.02,NSW1NSW1 +16212,2011-11-07 12:00:00,20636.65,NSW1NSW1 +16213,2011-11-07 13:00:00,20951.27,NSW1NSW1 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11:00:00,20550.17,NSW1NSW1 +16236,2011-11-08 12:00:00,20899.38,NSW1NSW1 +16237,2011-11-08 13:00:00,21382.9,NSW1NSW1 +16238,2011-11-08 14:00:00,21645.239999999998,NSW1NSW1 +16239,2011-11-08 15:00:00,22011.71,NSW1NSW1 +16240,2011-11-08 16:00:00,21653.91,NSW1NSW1 +16241,2011-11-08 17:00:00,20535.58,NSW1NSW1 +16242,2011-11-08 18:00:00,19752.54,NSW1NSW1 +16243,2011-11-08 19:00:00,19456.010000000002,NSW1NSW1 +16244,2011-11-08 20:00:00,18554.27,NSW1NSW1 +16245,2011-11-08 21:00:00,17503.65,NSW1NSW1 +16246,2011-11-08 22:00:00,16829.14,NSW1NSW1 +16247,2011-11-08 23:00:00,16148.9,NSW1NSW1 +16248,2011-11-09 00:00:00,15330.990000000002,NSW1NSW1 +16249,2011-11-09 01:00:00,14506.79,NSW1NSW1 +16250,2011-11-09 02:00:00,13437.529999999999,NSW1NSW1 +16251,2011-11-09 03:00:00,13037.89,NSW1NSW1 +16252,2011-11-09 04:00:00,13477.54,NSW1NSW1 +16253,2011-11-09 05:00:00,14818.08,NSW1NSW1 +16254,2011-11-09 06:00:00,16938.03,NSW1NSW1 +16255,2011-11-09 07:00:00,18512.440000000002,NSW1NSW1 +16256,2011-11-09 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16:00:00,16522.53,NSW1NSW1 +16361,2011-11-13 17:00:00,16754.42,NSW1NSW1 +16362,2011-11-13 18:00:00,16756.5,NSW1NSW1 +16363,2011-11-13 19:00:00,17101.190000000002,NSW1NSW1 +16364,2011-11-13 20:00:00,16768.63,NSW1NSW1 +16365,2011-11-13 21:00:00,15883.330000000002,NSW1NSW1 +16366,2011-11-13 22:00:00,15426.130000000001,NSW1NSW1 +16367,2011-11-13 23:00:00,14799.36,NSW1NSW1 +16368,2011-11-14 00:00:00,14235.99,NSW1NSW1 +16369,2011-11-14 01:00:00,13594.14,NSW1NSW1 +16370,2011-11-14 02:00:00,12806.93,NSW1NSW1 +16371,2011-11-14 03:00:00,12637.58,NSW1NSW1 +16372,2011-11-14 04:00:00,13072.43,NSW1NSW1 +16373,2011-11-14 05:00:00,14380.73,NSW1NSW1 +16374,2011-11-14 06:00:00,16571.59,NSW1NSW1 +16375,2011-11-14 07:00:00,18219.78,NSW1NSW1 +16376,2011-11-14 08:00:00,19169.760000000002,NSW1NSW1 +16377,2011-11-14 09:00:00,19840.629999999997,NSW1NSW1 +16378,2011-11-14 10:00:00,20205.9,NSW1NSW1 +16379,2011-11-14 11:00:00,21062.36,NSW1NSW1 +16380,2011-11-14 12:00:00,21597.35,NSW1NSW1 +16381,2011-11-14 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10:00:00,19980.47,NSW1NSW1 +16403,2011-11-15 11:00:00,20016.07,NSW1NSW1 +16404,2011-11-15 12:00:00,20076.32,NSW1NSW1 +16405,2011-11-15 13:00:00,20206.76,NSW1NSW1 +16406,2011-11-15 14:00:00,20304.29,NSW1NSW1 +16407,2011-11-15 15:00:00,20589.489999999998,NSW1NSW1 +16408,2011-11-15 16:00:00,20615.48,NSW1NSW1 +16409,2011-11-15 17:00:00,19967.34,NSW1NSW1 +16410,2011-11-15 18:00:00,19118.199999999997,NSW1NSW1 +16411,2011-11-15 19:00:00,18963.3,NSW1NSW1 +16412,2011-11-15 20:00:00,18364.88,NSW1NSW1 +16413,2011-11-15 21:00:00,17332.309999999998,NSW1NSW1 +16414,2011-11-15 22:00:00,16707.77,NSW1NSW1 +16415,2011-11-15 23:00:00,15940.66,NSW1NSW1 +16416,2011-11-16 00:00:00,15164.1,NSW1NSW1 +16417,2011-11-16 01:00:00,14181.73,NSW1NSW1 +16418,2011-11-16 02:00:00,13294.48,NSW1NSW1 +16419,2011-11-16 03:00:00,12895.64,NSW1NSW1 +16420,2011-11-16 04:00:00,13410.560000000001,NSW1NSW1 +16421,2011-11-16 05:00:00,14654.11,NSW1NSW1 +16422,2011-11-16 06:00:00,16613.75,NSW1NSW1 +16423,2011-11-16 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22:00:00,16001.81,NSW1NSW1 +17159,2011-12-16 23:00:00,15658.34,NSW1NSW1 +17160,2011-12-17 00:00:00,15047.34,NSW1NSW1 +17161,2011-12-17 01:00:00,14132.93,NSW1NSW1 +17162,2011-12-17 02:00:00,13008.369999999999,NSW1NSW1 +17163,2011-12-17 03:00:00,12431.11,NSW1NSW1 +17164,2011-12-17 04:00:00,12461.119999999999,NSW1NSW1 +17165,2011-12-17 05:00:00,12846.619999999999,NSW1NSW1 +17166,2011-12-17 06:00:00,13855.470000000001,NSW1NSW1 +17167,2011-12-17 07:00:00,15309.59,NSW1NSW1 +17168,2011-12-17 08:00:00,16428.0,NSW1NSW1 +17169,2011-12-17 09:00:00,16910.41,NSW1NSW1 +17170,2011-12-17 10:00:00,16788.93,NSW1NSW1 +17171,2011-12-17 11:00:00,16492.4,NSW1NSW1 +17172,2011-12-17 12:00:00,16143.85,NSW1NSW1 +17173,2011-12-17 13:00:00,15943.94,NSW1NSW1 +17174,2011-12-17 14:00:00,15834.18,NSW1NSW1 +17175,2011-12-17 15:00:00,15917.8,NSW1NSW1 +17176,2011-12-17 16:00:00,15994.900000000001,NSW1NSW1 +17177,2011-12-17 17:00:00,15883.36,NSW1NSW1 +17178,2011-12-17 18:00:00,15566.77,NSW1NSW1 +17179,2011-12-17 19:00:00,15558.33,NSW1NSW1 +17180,2011-12-17 20:00:00,15866.55,NSW1NSW1 +17181,2011-12-17 21:00:00,15498.57,NSW1NSW1 +17182,2011-12-17 22:00:00,15331.150000000001,NSW1NSW1 +17183,2011-12-17 23:00:00,14684.61,NSW1NSW1 +17184,2011-12-18 00:00:00,13941.81,NSW1NSW1 +17185,2011-12-18 01:00:00,13125.93,NSW1NSW1 +17186,2011-12-18 02:00:00,12319.61,NSW1NSW1 +17187,2011-12-18 03:00:00,11935.22,NSW1NSW1 +17188,2011-12-18 04:00:00,11990.88,NSW1NSW1 +17189,2011-12-18 05:00:00,12144.23,NSW1NSW1 +17190,2011-12-18 06:00:00,12781.67,NSW1NSW1 +17191,2011-12-18 07:00:00,14042.32,NSW1NSW1 +17192,2011-12-18 08:00:00,15244.74,NSW1NSW1 +17193,2011-12-18 09:00:00,15868.64,NSW1NSW1 +17194,2011-12-18 10:00:00,15902.990000000002,NSW1NSW1 +17195,2011-12-18 11:00:00,15789.21,NSW1NSW1 +17196,2011-12-18 12:00:00,15605.439999999999,NSW1NSW1 +17197,2011-12-18 13:00:00,15350.58,NSW1NSW1 +17198,2011-12-18 14:00:00,15281.560000000001,NSW1NSW1 +17199,2011-12-18 15:00:00,15478.880000000001,NSW1NSW1 +17200,2011-12-18 16:00:00,15565.28,NSW1NSW1 +17201,2011-12-18 17:00:00,15785.61,NSW1NSW1 +17202,2011-12-18 18:00:00,15698.28,NSW1NSW1 +17203,2011-12-18 19:00:00,15891.52,NSW1NSW1 +17204,2011-12-18 20:00:00,16167.61,NSW1NSW1 +17205,2011-12-18 21:00:00,15586.34,NSW1NSW1 +17206,2011-12-18 22:00:00,15161.89,NSW1NSW1 +17207,2011-12-18 23:00:00,14445.720000000001,NSW1NSW1 +17208,2011-12-19 00:00:00,13978.98,NSW1NSW1 +17209,2011-12-19 01:00:00,13337.21,NSW1NSW1 +17210,2011-12-19 02:00:00,12575.1,NSW1NSW1 +17211,2011-12-19 03:00:00,12396.029999999999,NSW1NSW1 +17212,2011-12-19 04:00:00,12802.93,NSW1NSW1 +17213,2011-12-19 05:00:00,13927.720000000001,NSW1NSW1 +17214,2011-12-19 06:00:00,15840.43,NSW1NSW1 +17215,2011-12-19 07:00:00,17481.34,NSW1NSW1 +17216,2011-12-19 08:00:00,18368.59,NSW1NSW1 +17217,2011-12-19 09:00:00,18867.42,NSW1NSW1 +17218,2011-12-19 10:00:00,18986.15,NSW1NSW1 +17219,2011-12-19 11:00:00,18951.6,NSW1NSW1 +17220,2011-12-19 12:00:00,18809.68,NSW1NSW1 +17221,2011-12-19 13:00:00,18719.42,NSW1NSW1 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22:00:00,14367.3,NSW1NSW1 +37031,2014-03-23 23:00:00,13663.76,NSW1NSW1 +37032,2014-03-24 00:00:00,13091.08,NSW1NSW1 +37033,2014-03-24 01:00:00,12424.880000000001,NSW1NSW1 +37034,2014-03-24 02:00:00,11855.02,NSW1NSW1 +37035,2014-03-24 03:00:00,11737.66,NSW1NSW1 +37036,2014-03-24 04:00:00,12310.42,NSW1NSW1 +37037,2014-03-24 05:00:00,13810.189999999999,NSW1NSW1 +37038,2014-03-24 06:00:00,15973.48,NSW1NSW1 +37039,2014-03-24 07:00:00,17329.86,NSW1NSW1 +37040,2014-03-24 08:00:00,17731.93,NSW1NSW1 +37041,2014-03-24 09:00:00,17937.75,NSW1NSW1 +37042,2014-03-24 10:00:00,17975.65,NSW1NSW1 +37043,2014-03-24 11:00:00,18002.239999999998,NSW1NSW1 +37044,2014-03-24 12:00:00,17907.8,NSW1NSW1 +37045,2014-03-24 13:00:00,17633.9,NSW1NSW1 +37046,2014-03-24 14:00:00,17309.09,NSW1NSW1 +37047,2014-03-24 15:00:00,17258.9,NSW1NSW1 +37048,2014-03-24 16:00:00,17398.18,NSW1NSW1 +37049,2014-03-24 17:00:00,17343.309999999998,NSW1NSW1 +37050,2014-03-24 18:00:00,17236.97,NSW1NSW1 +37051,2014-03-24 19:00:00,16701.43,NSW1NSW1 +37052,2014-03-24 20:00:00,15701.8,NSW1NSW1 +37053,2014-03-24 21:00:00,14962.39,NSW1NSW1 +37054,2014-03-24 22:00:00,14535.220000000001,NSW1NSW1 +37055,2014-03-24 23:00:00,14316.58,NSW1NSW1 +37056,2014-03-25 00:00:00,13730.36,NSW1NSW1 +37057,2014-03-25 01:00:00,12738.55,NSW1NSW1 +37058,2014-03-25 02:00:00,11866.880000000001,NSW1NSW1 +37059,2014-03-25 03:00:00,11606.91,NSW1NSW1 +37060,2014-03-25 04:00:00,12012.91,NSW1NSW1 +37061,2014-03-25 05:00:00,13405.369999999999,NSW1NSW1 +37062,2014-03-25 06:00:00,15518.42,NSW1NSW1 +37063,2014-03-25 07:00:00,16563.64,NSW1NSW1 +37064,2014-03-25 08:00:00,16821.52,NSW1NSW1 +37065,2014-03-25 09:00:00,17193.73,NSW1NSW1 +37066,2014-03-25 10:00:00,17365.67,NSW1NSW1 +37067,2014-03-25 11:00:00,17456.989999999998,NSW1NSW1 +37068,2014-03-25 12:00:00,17568.46,NSW1NSW1 +37069,2014-03-25 13:00:00,17494.15,NSW1NSW1 +37070,2014-03-25 14:00:00,17464.04,NSW1NSW1 +37071,2014-03-25 15:00:00,17581.71,NSW1NSW1 +37072,2014-03-25 16:00:00,17627.38,NSW1NSW1 +37073,2014-03-25 17:00:00,17509.02,NSW1NSW1 +37074,2014-03-25 18:00:00,17413.05,NSW1NSW1 +37075,2014-03-25 19:00:00,17128.11,NSW1NSW1 +37076,2014-03-25 20:00:00,16315.52,NSW1NSW1 +37077,2014-03-25 21:00:00,15554.36,NSW1NSW1 +37078,2014-03-25 22:00:00,15132.56,NSW1NSW1 +37079,2014-03-25 23:00:00,14687.78,NSW1NSW1 +37080,2014-03-26 00:00:00,14164.150000000001,NSW1NSW1 +37081,2014-03-26 01:00:00,13215.35,NSW1NSW1 +37082,2014-03-26 02:00:00,12361.619999999999,NSW1NSW1 +37083,2014-03-26 03:00:00,12107.05,NSW1NSW1 +37084,2014-03-26 04:00:00,12486.23,NSW1NSW1 +37085,2014-03-26 05:00:00,13958.59,NSW1NSW1 +37086,2014-03-26 06:00:00,16093.869999999999,NSW1NSW1 +37087,2014-03-26 07:00:00,17333.62,NSW1NSW1 +37088,2014-03-26 08:00:00,17809.4,NSW1NSW1 +37089,2014-03-26 09:00:00,18234.879999999997,NSW1NSW1 +37090,2014-03-26 10:00:00,18273.04,NSW1NSW1 +37091,2014-03-26 11:00:00,18308.620000000003,NSW1NSW1 +37092,2014-03-26 12:00:00,18261.72,NSW1NSW1 +37093,2014-03-26 13:00:00,18344.48,NSW1NSW1 +37094,2014-03-26 14:00:00,18127.58,NSW1NSW1 +37095,2014-03-26 15:00:00,18081.739999999998,NSW1NSW1 +37096,2014-03-26 16:00:00,18149.43,NSW1NSW1 +37097,2014-03-26 17:00:00,17938.57,NSW1NSW1 +37098,2014-03-26 18:00:00,18022.47,NSW1NSW1 +37099,2014-03-26 19:00:00,17504.84,NSW1NSW1 +37100,2014-03-26 20:00:00,16587.37,NSW1NSW1 +37101,2014-03-26 21:00:00,15850.58,NSW1NSW1 +37102,2014-03-26 22:00:00,15274.93,NSW1NSW1 +37103,2014-03-26 23:00:00,14790.04,NSW1NSW1 +37104,2014-03-27 00:00:00,14351.21,NSW1NSW1 +37105,2014-03-27 01:00:00,13441.26,NSW1NSW1 +37106,2014-03-27 02:00:00,12458.84,NSW1NSW1 +37107,2014-03-27 03:00:00,12271.05,NSW1NSW1 +37108,2014-03-27 04:00:00,12655.83,NSW1NSW1 +37109,2014-03-27 05:00:00,14153.0,NSW1NSW1 +37110,2014-03-27 06:00:00,16376.899999999998,NSW1NSW1 +37111,2014-03-27 07:00:00,17781.98,NSW1NSW1 +37112,2014-03-27 08:00:00,18150.95,NSW1NSW1 +37113,2014-03-27 09:00:00,18433.04,NSW1NSW1 +37114,2014-03-27 10:00:00,18379.38,NSW1NSW1 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07:00:00,17427.38,NSW1NSW1 +37136,2014-03-28 08:00:00,17822.55,NSW1NSW1 +37137,2014-03-28 09:00:00,18060.58,NSW1NSW1 +37138,2014-03-28 10:00:00,18135.08,NSW1NSW1 +37139,2014-03-28 11:00:00,18039.61,NSW1NSW1 +37140,2014-03-28 12:00:00,17926.36,NSW1NSW1 +37141,2014-03-28 13:00:00,17860.73,NSW1NSW1 +37142,2014-03-28 14:00:00,17586.1,NSW1NSW1 +37143,2014-03-28 15:00:00,17543.440000000002,NSW1NSW1 +37144,2014-03-28 16:00:00,17575.02,NSW1NSW1 +37145,2014-03-28 17:00:00,17383.410000000003,NSW1NSW1 +37146,2014-03-28 18:00:00,17290.29,NSW1NSW1 +37147,2014-03-28 19:00:00,16871.23,NSW1NSW1 +37148,2014-03-28 20:00:00,16203.68,NSW1NSW1 +37149,2014-03-28 21:00:00,15672.61,NSW1NSW1 +37150,2014-03-28 22:00:00,15610.86,NSW1NSW1 +37151,2014-03-28 23:00:00,15143.21,NSW1NSW1 +37152,2014-03-29 00:00:00,14460.42,NSW1NSW1 +37153,2014-03-29 01:00:00,13354.14,NSW1NSW1 +37154,2014-03-29 02:00:00,12232.78,NSW1NSW1 +37155,2014-03-29 03:00:00,11806.76,NSW1NSW1 +37156,2014-03-29 04:00:00,11833.8,NSW1NSW1 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22:00:00,14258.45,NSW1NSW1 +37199,2014-03-30 23:00:00,13730.33,NSW1NSW1 +37200,2014-03-31 00:00:00,13223.46,NSW1NSW1 +37201,2014-03-31 01:00:00,12527.53,NSW1NSW1 +37202,2014-03-31 02:00:00,11919.33,NSW1NSW1 +37203,2014-03-31 03:00:00,11828.56,NSW1NSW1 +37204,2014-03-31 04:00:00,12196.34,NSW1NSW1 +37205,2014-03-31 05:00:00,13580.099999999999,NSW1NSW1 +37206,2014-03-31 06:00:00,15602.84,NSW1NSW1 +37207,2014-03-31 07:00:00,16873.910000000003,NSW1NSW1 +37208,2014-03-31 08:00:00,17247.87,NSW1NSW1 +37209,2014-03-31 09:00:00,17673.54,NSW1NSW1 +37210,2014-03-31 10:00:00,17837.79,NSW1NSW1 +37211,2014-03-31 11:00:00,17848.989999999998,NSW1NSW1 +37212,2014-03-31 12:00:00,17843.120000000003,NSW1NSW1 +37213,2014-03-31 13:00:00,17846.3,NSW1NSW1 +37214,2014-03-31 14:00:00,17838.11,NSW1NSW1 +37215,2014-03-31 15:00:00,18066.690000000002,NSW1NSW1 +37216,2014-03-31 16:00:00,18194.18,NSW1NSW1 +37217,2014-03-31 17:00:00,18030.739999999998,NSW1NSW1 +37218,2014-03-31 18:00:00,17949.739999999998,NSW1NSW1 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10:00:00,17232.71,NSW1NSW1 +38099,2014-05-07 11:00:00,16737.309999999998,NSW1NSW1 +38100,2014-05-07 12:00:00,16516.52,NSW1NSW1 +38101,2014-05-07 13:00:00,16433.08,NSW1NSW1 +38102,2014-05-07 14:00:00,16402.09,NSW1NSW1 +38103,2014-05-07 15:00:00,16436.260000000002,NSW1NSW1 +38104,2014-05-07 16:00:00,16800.18,NSW1NSW1 +38105,2014-05-07 17:00:00,18043.239999999998,NSW1NSW1 +38106,2014-05-07 18:00:00,19667.78,NSW1NSW1 +38107,2014-05-07 19:00:00,19122.440000000002,NSW1NSW1 +38108,2014-05-07 20:00:00,18344.97,NSW1NSW1 +38109,2014-05-07 21:00:00,17722.02,NSW1NSW1 +38110,2014-05-07 22:00:00,17052.42,NSW1NSW1 +38111,2014-05-07 23:00:00,16450.739999999998,NSW1NSW1 +38112,2014-05-08 00:00:00,15884.38,NSW1NSW1 +38113,2014-05-08 01:00:00,14978.95,NSW1NSW1 +38114,2014-05-08 02:00:00,13988.41,NSW1NSW1 +38115,2014-05-08 03:00:00,12955.119999999999,NSW1NSW1 +38116,2014-05-08 04:00:00,12574.01,NSW1NSW1 +38117,2014-05-08 05:00:00,13104.61,NSW1NSW1 +38118,2014-05-08 06:00:00,14920.779999999999,NSW1NSW1 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11:00:00,14408.02,NSW1NSW1 +41868,2014-10-11 12:00:00,14345.4,NSW1NSW1 +41869,2014-10-11 13:00:00,14349.630000000001,NSW1NSW1 +41870,2014-10-11 14:00:00,14437.05,NSW1NSW1 +41871,2014-10-11 15:00:00,14787.45,NSW1NSW1 +41872,2014-10-11 16:00:00,14960.51,NSW1NSW1 +41873,2014-10-11 17:00:00,15195.55,NSW1NSW1 +41874,2014-10-11 18:00:00,15250.779999999999,NSW1NSW1 +41875,2014-10-11 19:00:00,15354.869999999999,NSW1NSW1 +41876,2014-10-11 20:00:00,14699.150000000001,NSW1NSW1 +41877,2014-10-11 21:00:00,14175.01,NSW1NSW1 +41878,2014-10-11 22:00:00,14064.42,NSW1NSW1 +41879,2014-10-11 23:00:00,13565.880000000001,NSW1NSW1 +41880,2014-10-12 00:00:00,12947.18,NSW1NSW1 +41881,2014-10-12 01:00:00,12230.66,NSW1NSW1 +41882,2014-10-12 02:00:00,11455.369999999999,NSW1NSW1 +41883,2014-10-12 03:00:00,11099.95,NSW1NSW1 +41884,2014-10-12 04:00:00,11099.92,NSW1NSW1 +41885,2014-10-12 05:00:00,11290.66,NSW1NSW1 +41886,2014-10-12 06:00:00,11836.19,NSW1NSW1 +41887,2014-10-12 07:00:00,12751.93,NSW1NSW1 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00:00:00,13951.27,NSW1NSW1 +41929,2014-10-14 01:00:00,13148.79,NSW1NSW1 +41930,2014-10-14 02:00:00,12158.76,NSW1NSW1 +41931,2014-10-14 03:00:00,11780.46,NSW1NSW1 +41932,2014-10-14 04:00:00,12124.57,NSW1NSW1 +41933,2014-10-14 05:00:00,13572.66,NSW1NSW1 +41934,2014-10-14 06:00:00,15512.349999999999,NSW1NSW1 +41935,2014-10-14 07:00:00,16446.15,NSW1NSW1 +41936,2014-10-14 08:00:00,16430.09,NSW1NSW1 +41937,2014-10-14 09:00:00,16493.16,NSW1NSW1 +41938,2014-10-14 10:00:00,16552.14,NSW1NSW1 +41939,2014-10-14 11:00:00,16597.08,NSW1NSW1 +41940,2014-10-14 12:00:00,16489.879999999997,NSW1NSW1 +41941,2014-10-14 13:00:00,16343.63,NSW1NSW1 +41942,2014-10-14 14:00:00,16122.57,NSW1NSW1 +41943,2014-10-14 15:00:00,16226.78,NSW1NSW1 +41944,2014-10-14 16:00:00,16639.84,NSW1NSW1 +41945,2014-10-14 17:00:00,17139.9,NSW1NSW1 +41946,2014-10-14 18:00:00,17529.57,NSW1NSW1 +41947,2014-10-14 19:00:00,17367.27,NSW1NSW1 +41948,2014-10-14 20:00:00,16591.17,NSW1NSW1 +41949,2014-10-14 21:00:00,15749.55,NSW1NSW1 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01:00:00,12625.95,NSW1NSW1 +43058,2014-11-30 02:00:00,11897.26,NSW1NSW1 +43059,2014-11-30 03:00:00,11581.05,NSW1NSW1 +43060,2014-11-30 04:00:00,11560.75,NSW1NSW1 +43061,2014-11-30 05:00:00,11635.36,NSW1NSW1 +43062,2014-11-30 06:00:00,12225.3,NSW1NSW1 +43063,2014-11-30 07:00:00,13378.66,NSW1NSW1 +43064,2014-11-30 08:00:00,14330.25,NSW1NSW1 +43065,2014-11-30 09:00:00,15016.7,NSW1NSW1 +43066,2014-11-30 10:00:00,15536.36,NSW1NSW1 +43067,2014-11-30 11:00:00,15823.06,NSW1NSW1 +43068,2014-11-30 12:00:00,16290.98,NSW1NSW1 +43069,2014-11-30 13:00:00,16557.14,NSW1NSW1 +43070,2014-11-30 14:00:00,16668.1,NSW1NSW1 +43071,2014-11-30 15:00:00,16551.32,NSW1NSW1 +43072,2014-11-30 16:00:00,16446.92,NSW1NSW1 +43073,2014-11-30 17:00:00,16457.18,NSW1NSW1 +43074,2014-11-30 18:00:00,16238.880000000001,NSW1NSW1 +43075,2014-11-30 19:00:00,16369.029999999999,NSW1NSW1 +43076,2014-11-30 20:00:00,15924.98,NSW1NSW1 +43077,2014-11-30 21:00:00,14951.02,NSW1NSW1 +43078,2014-11-30 22:00:00,14343.71,NSW1NSW1 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20:00:00,17382.49,NSW1NSW1 +43101,2014-12-01 21:00:00,16350.150000000001,NSW1NSW1 +43102,2014-12-01 22:00:00,15639.619999999999,NSW1NSW1 +43103,2014-12-01 23:00:00,15092.52,NSW1NSW1 +43104,2014-12-02 00:00:00,14496.57,NSW1NSW1 +43105,2014-12-02 01:00:00,13511.34,NSW1NSW1 +43106,2014-12-02 02:00:00,12659.19,NSW1NSW1 +43107,2014-12-02 03:00:00,12417.59,NSW1NSW1 +43108,2014-12-02 04:00:00,12664.32,NSW1NSW1 +43109,2014-12-02 05:00:00,13842.45,NSW1NSW1 +43110,2014-12-02 06:00:00,15721.14,NSW1NSW1 +43111,2014-12-02 07:00:00,16899.989999999998,NSW1NSW1 +43112,2014-12-02 08:00:00,17552.34,NSW1NSW1 +43113,2014-12-02 09:00:00,18206.93,NSW1NSW1 +43114,2014-12-02 10:00:00,18727.809999999998,NSW1NSW1 +43115,2014-12-02 11:00:00,19191.51,NSW1NSW1 +43116,2014-12-02 12:00:00,19665.18,NSW1NSW1 +43117,2014-12-02 13:00:00,20413.78,NSW1NSW1 +43118,2014-12-02 14:00:00,20967.79,NSW1NSW1 +43119,2014-12-02 15:00:00,21189.940000000002,NSW1NSW1 +43120,2014-12-02 16:00:00,21345.13,NSW1NSW1 +43121,2014-12-02 17:00:00,20956.1,NSW1NSW1 +43122,2014-12-02 18:00:00,20050.98,NSW1NSW1 +43123,2014-12-02 19:00:00,19437.11,NSW1NSW1 +43124,2014-12-02 20:00:00,18701.11,NSW1NSW1 +43125,2014-12-02 21:00:00,17580.54,NSW1NSW1 +43126,2014-12-02 22:00:00,16518.35,NSW1NSW1 +43127,2014-12-02 23:00:00,15588.11,NSW1NSW1 +43128,2014-12-03 00:00:00,14811.009999999998,NSW1NSW1 +43129,2014-12-03 01:00:00,13797.69,NSW1NSW1 +43130,2014-12-03 02:00:00,12816.86,NSW1NSW1 +43131,2014-12-03 03:00:00,12576.69,NSW1NSW1 +43132,2014-12-03 04:00:00,12947.07,NSW1NSW1 +43133,2014-12-03 05:00:00,14125.92,NSW1NSW1 +43134,2014-12-03 06:00:00,16138.84,NSW1NSW1 +43135,2014-12-03 07:00:00,17711.97,NSW1NSW1 +43136,2014-12-03 08:00:00,18622.09,NSW1NSW1 +43137,2014-12-03 09:00:00,19479.309999999998,NSW1NSW1 +43138,2014-12-03 10:00:00,20234.870000000003,NSW1NSW1 +43139,2014-12-03 11:00:00,20840.14,NSW1NSW1 +43140,2014-12-03 12:00:00,21477.34,NSW1NSW1 +43141,2014-12-03 13:00:00,21976.82,NSW1NSW1 +43142,2014-12-03 14:00:00,22031.21,NSW1NSW1 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11:00:00,18704.52,NSW1NSW1 +43164,2014-12-04 12:00:00,19078.18,NSW1NSW1 +43165,2014-12-04 13:00:00,19543.309999999998,NSW1NSW1 +43166,2014-12-04 14:00:00,19878.629999999997,NSW1NSW1 +43167,2014-12-04 15:00:00,20416.33,NSW1NSW1 +43168,2014-12-04 16:00:00,20417.940000000002,NSW1NSW1 +43169,2014-12-04 17:00:00,19863.67,NSW1NSW1 +43170,2014-12-04 18:00:00,19175.760000000002,NSW1NSW1 +43171,2014-12-04 19:00:00,18586.86,NSW1NSW1 +43172,2014-12-04 20:00:00,18244.239999999998,NSW1NSW1 +43173,2014-12-04 21:00:00,17183.53,NSW1NSW1 +43174,2014-12-04 22:00:00,16112.490000000002,NSW1NSW1 +43175,2014-12-04 23:00:00,15252.95,NSW1NSW1 +43176,2014-12-05 00:00:00,14543.89,NSW1NSW1 +43177,2014-12-05 01:00:00,13628.32,NSW1NSW1 +43178,2014-12-05 02:00:00,12684.11,NSW1NSW1 +43179,2014-12-05 03:00:00,12474.51,NSW1NSW1 +43180,2014-12-05 04:00:00,12777.0,NSW1NSW1 +43181,2014-12-05 05:00:00,13994.66,NSW1NSW1 +43182,2014-12-05 06:00:00,15846.71,NSW1NSW1 +43183,2014-12-05 07:00:00,17190.07,NSW1NSW1 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05:00:00,12277.09,NSW1NSW1 +43206,2014-12-06 06:00:00,13245.19,NSW1NSW1 +43207,2014-12-06 07:00:00,14600.26,NSW1NSW1 +43208,2014-12-06 08:00:00,15603.279999999999,NSW1NSW1 +43209,2014-12-06 09:00:00,16042.97,NSW1NSW1 +43210,2014-12-06 10:00:00,16159.35,NSW1NSW1 +43211,2014-12-06 11:00:00,16090.630000000001,NSW1NSW1 +43212,2014-12-06 12:00:00,16160.970000000001,NSW1NSW1 +43213,2014-12-06 13:00:00,16293.1,NSW1NSW1 +43214,2014-12-06 14:00:00,16296.1,NSW1NSW1 +43215,2014-12-06 15:00:00,16508.55,NSW1NSW1 +43216,2014-12-06 16:00:00,16230.82,NSW1NSW1 +43217,2014-12-06 17:00:00,15922.119999999999,NSW1NSW1 +43218,2014-12-06 18:00:00,15362.7,NSW1NSW1 +43219,2014-12-06 19:00:00,15182.779999999999,NSW1NSW1 +43220,2014-12-06 20:00:00,14991.8,NSW1NSW1 +43221,2014-12-06 21:00:00,14636.939999999999,NSW1NSW1 +43222,2014-12-06 22:00:00,14204.8,NSW1NSW1 +43223,2014-12-06 23:00:00,13625.92,NSW1NSW1 +43224,2014-12-07 00:00:00,13117.7,NSW1NSW1 +43225,2014-12-07 01:00:00,12330.34,NSW1NSW1 +43226,2014-12-07 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20:00:00,17454.54,NSW1NSW1 +43269,2014-12-08 21:00:00,16422.92,NSW1NSW1 +43270,2014-12-08 22:00:00,15536.119999999999,NSW1NSW1 +43271,2014-12-08 23:00:00,14769.73,NSW1NSW1 +43272,2014-12-09 00:00:00,14040.18,NSW1NSW1 +43273,2014-12-09 01:00:00,13142.41,NSW1NSW1 +43274,2014-12-09 02:00:00,12289.59,NSW1NSW1 +43275,2014-12-09 03:00:00,11991.189999999999,NSW1NSW1 +43276,2014-12-09 04:00:00,12416.470000000001,NSW1NSW1 +43277,2014-12-09 05:00:00,13586.150000000001,NSW1NSW1 +43278,2014-12-09 06:00:00,15553.16,NSW1NSW1 +43279,2014-12-09 07:00:00,16923.78,NSW1NSW1 +43280,2014-12-09 08:00:00,17569.940000000002,NSW1NSW1 +43281,2014-12-09 09:00:00,17873.3,NSW1NSW1 +43282,2014-12-09 10:00:00,18115.67,NSW1NSW1 +43283,2014-12-09 11:00:00,18339.14,NSW1NSW1 +43284,2014-12-09 12:00:00,18417.64,NSW1NSW1 +43285,2014-12-09 13:00:00,18438.09,NSW1NSW1 +43286,2014-12-09 14:00:00,18484.47,NSW1NSW1 +43287,2014-12-09 15:00:00,18264.5,NSW1NSW1 +43288,2014-12-09 16:00:00,18101.03,NSW1NSW1 +43289,2014-12-09 17:00:00,17694.85,NSW1NSW1 +43290,2014-12-09 18:00:00,17207.260000000002,NSW1NSW1 +43291,2014-12-09 19:00:00,17023.34,NSW1NSW1 +43292,2014-12-09 20:00:00,16740.66,NSW1NSW1 +43293,2014-12-09 21:00:00,15933.39,NSW1NSW1 +43294,2014-12-09 22:00:00,15301.5,NSW1NSW1 +43295,2014-12-09 23:00:00,14776.01,NSW1NSW1 +43296,2014-12-10 00:00:00,14136.42,NSW1NSW1 +43297,2014-12-10 01:00:00,13228.849999999999,NSW1NSW1 +43298,2014-12-10 02:00:00,12198.849999999999,NSW1NSW1 +43299,2014-12-10 03:00:00,12032.33,NSW1NSW1 +43300,2014-12-10 04:00:00,12510.32,NSW1NSW1 +43301,2014-12-10 05:00:00,13688.720000000001,NSW1NSW1 +43302,2014-12-10 06:00:00,15507.3,NSW1NSW1 +43303,2014-12-10 07:00:00,16800.37,NSW1NSW1 +43304,2014-12-10 08:00:00,17486.77,NSW1NSW1 +43305,2014-12-10 09:00:00,17900.0,NSW1NSW1 +43306,2014-12-10 10:00:00,18125.199999999997,NSW1NSW1 +43307,2014-12-10 11:00:00,18140.15,NSW1NSW1 +43308,2014-12-10 12:00:00,18303.73,NSW1NSW1 +43309,2014-12-10 13:00:00,18573.4,NSW1NSW1 +43310,2014-12-10 14:00:00,18588.4,NSW1NSW1 +43311,2014-12-10 15:00:00,18678.75,NSW1NSW1 +43312,2014-12-10 16:00:00,18433.16,NSW1NSW1 +43313,2014-12-10 17:00:00,17965.22,NSW1NSW1 +43314,2014-12-10 18:00:00,17430.3,NSW1NSW1 +43315,2014-12-10 19:00:00,16939.66,NSW1NSW1 +43316,2014-12-10 20:00:00,16566.92,NSW1NSW1 +43317,2014-12-10 21:00:00,15790.619999999999,NSW1NSW1 +43318,2014-12-10 22:00:00,15247.099999999999,NSW1NSW1 +43319,2014-12-10 23:00:00,14634.92,NSW1NSW1 +43320,2014-12-11 00:00:00,14073.66,NSW1NSW1 +43321,2014-12-11 01:00:00,13174.08,NSW1NSW1 +43322,2014-12-11 02:00:00,12242.740000000002,NSW1NSW1 +43323,2014-12-11 03:00:00,12015.509999999998,NSW1NSW1 +43324,2014-12-11 04:00:00,12497.3,NSW1NSW1 +43325,2014-12-11 05:00:00,13612.21,NSW1NSW1 +43326,2014-12-11 06:00:00,15571.55,NSW1NSW1 +43327,2014-12-11 07:00:00,16949.24,NSW1NSW1 +43328,2014-12-11 08:00:00,17615.260000000002,NSW1NSW1 +43329,2014-12-11 09:00:00,17886.879999999997,NSW1NSW1 +43330,2014-12-11 10:00:00,17845.9,NSW1NSW1 +43331,2014-12-11 11:00:00,17554.48,NSW1NSW1 +43332,2014-12-11 12:00:00,17157.39,NSW1NSW1 +43333,2014-12-11 13:00:00,16963.91,NSW1NSW1 +43334,2014-12-11 14:00:00,16692.18,NSW1NSW1 +43335,2014-12-11 15:00:00,16571.0,NSW1NSW1 +43336,2014-12-11 16:00:00,16625.84,NSW1NSW1 +43337,2014-12-11 17:00:00,16577.64,NSW1NSW1 +43338,2014-12-11 18:00:00,16250.630000000001,NSW1NSW1 +43339,2014-12-11 19:00:00,16077.83,NSW1NSW1 +43340,2014-12-11 20:00:00,15805.92,NSW1NSW1 +43341,2014-12-11 21:00:00,15094.740000000002,NSW1NSW1 +43342,2014-12-11 22:00:00,14660.16,NSW1NSW1 +43343,2014-12-11 23:00:00,14234.4,NSW1NSW1 +43344,2014-12-12 00:00:00,13555.28,NSW1NSW1 +43345,2014-12-12 01:00:00,12615.619999999999,NSW1NSW1 +43346,2014-12-12 02:00:00,11690.220000000001,NSW1NSW1 +43347,2014-12-12 03:00:00,11376.76,NSW1NSW1 +43348,2014-12-12 04:00:00,11861.66,NSW1NSW1 +43349,2014-12-12 05:00:00,13036.279999999999,NSW1NSW1 +43350,2014-12-12 06:00:00,14834.08,NSW1NSW1 +43351,2014-12-12 07:00:00,15760.220000000001,NSW1NSW1 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05:00:00,11817.85,NSW1NSW1 +43374,2014-12-13 06:00:00,12573.560000000001,NSW1NSW1 +43375,2014-12-13 07:00:00,13775.83,NSW1NSW1 +43376,2014-12-13 08:00:00,14632.49,NSW1NSW1 +43377,2014-12-13 09:00:00,14870.759999999998,NSW1NSW1 +43378,2014-12-13 10:00:00,14847.310000000001,NSW1NSW1 +43379,2014-12-13 11:00:00,14628.470000000001,NSW1NSW1 +43380,2014-12-13 12:00:00,14296.58,NSW1NSW1 +43381,2014-12-13 13:00:00,14133.0,NSW1NSW1 +43382,2014-12-13 14:00:00,14109.48,NSW1NSW1 +43383,2014-12-13 15:00:00,14226.67,NSW1NSW1 +43384,2014-12-13 16:00:00,14390.25,NSW1NSW1 +43385,2014-12-13 17:00:00,14564.369999999999,NSW1NSW1 +43386,2014-12-13 18:00:00,14580.88,NSW1NSW1 +43387,2014-12-13 19:00:00,14501.78,NSW1NSW1 +43388,2014-12-13 20:00:00,14568.3,NSW1NSW1 +43389,2014-12-13 21:00:00,14179.630000000001,NSW1NSW1 +43390,2014-12-13 22:00:00,13916.869999999999,NSW1NSW1 +43391,2014-12-13 23:00:00,13393.94,NSW1NSW1 +43392,2014-12-14 00:00:00,12951.92,NSW1NSW1 +43393,2014-12-14 01:00:00,12191.65,NSW1NSW1 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23:00:00,13343.25,NSW1NSW1 +43416,2014-12-15 00:00:00,12841.03,NSW1NSW1 +43417,2014-12-15 01:00:00,12205.6,NSW1NSW1 +43418,2014-12-15 02:00:00,11541.630000000001,NSW1NSW1 +43419,2014-12-15 03:00:00,11400.69,NSW1NSW1 +43420,2014-12-15 04:00:00,11824.509999999998,NSW1NSW1 +43421,2014-12-15 05:00:00,12920.66,NSW1NSW1 +43422,2014-12-15 06:00:00,14669.25,NSW1NSW1 +43423,2014-12-15 07:00:00,15876.5,NSW1NSW1 +43424,2014-12-15 08:00:00,16454.84,NSW1NSW1 +43425,2014-12-15 09:00:00,16896.34,NSW1NSW1 +43426,2014-12-15 10:00:00,17159.45,NSW1NSW1 +43427,2014-12-15 11:00:00,17328.050000000003,NSW1NSW1 +43428,2014-12-15 12:00:00,17491.65,NSW1NSW1 +43429,2014-12-15 13:00:00,17867.769999999997,NSW1NSW1 +43430,2014-12-15 14:00:00,18104.23,NSW1NSW1 +43431,2014-12-15 15:00:00,18416.57,NSW1NSW1 +43432,2014-12-15 16:00:00,18582.98,NSW1NSW1 +43433,2014-12-15 17:00:00,18239.879999999997,NSW1NSW1 +43434,2014-12-15 18:00:00,17482.190000000002,NSW1NSW1 +43435,2014-12-15 19:00:00,16928.489999999998,NSW1NSW1 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13:00:00,17230.69,NSW1NSW1 +43478,2014-12-17 14:00:00,17256.93,NSW1NSW1 +43479,2014-12-17 15:00:00,17409.0,NSW1NSW1 +43480,2014-12-17 16:00:00,17298.08,NSW1NSW1 +43481,2014-12-17 17:00:00,17038.129999999997,NSW1NSW1 +43482,2014-12-17 18:00:00,16652.86,NSW1NSW1 +43483,2014-12-17 19:00:00,16404.01,NSW1NSW1 +43484,2014-12-17 20:00:00,16073.310000000001,NSW1NSW1 +43485,2014-12-17 21:00:00,15415.26,NSW1NSW1 +43486,2014-12-17 22:00:00,14968.54,NSW1NSW1 +43487,2014-12-17 23:00:00,14549.73,NSW1NSW1 +43488,2014-12-18 00:00:00,13876.61,NSW1NSW1 +43489,2014-12-18 01:00:00,12966.18,NSW1NSW1 +43490,2014-12-18 02:00:00,12079.130000000001,NSW1NSW1 +43491,2014-12-18 03:00:00,11805.33,NSW1NSW1 +43492,2014-12-18 04:00:00,12158.17,NSW1NSW1 +43493,2014-12-18 05:00:00,13241.470000000001,NSW1NSW1 +43494,2014-12-18 06:00:00,14902.16,NSW1NSW1 +43495,2014-12-18 07:00:00,16069.93,NSW1NSW1 +43496,2014-12-18 08:00:00,16735.620000000003,NSW1NSW1 +43497,2014-12-18 09:00:00,17012.75,NSW1NSW1 +43498,2014-12-18 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03:00:00,12336.740000000002,NSW1NSW1 +44044,2015-01-10 04:00:00,12358.67,NSW1NSW1 +44045,2015-01-10 05:00:00,12642.35,NSW1NSW1 +44046,2015-01-10 06:00:00,13288.52,NSW1NSW1 +44047,2015-01-10 07:00:00,14498.84,NSW1NSW1 +44048,2015-01-10 08:00:00,15714.619999999999,NSW1NSW1 +44049,2015-01-10 09:00:00,16508.64,NSW1NSW1 +44050,2015-01-10 10:00:00,16950.9,NSW1NSW1 +44051,2015-01-10 11:00:00,17446.77,NSW1NSW1 +44052,2015-01-10 12:00:00,17612.17,NSW1NSW1 +44053,2015-01-10 13:00:00,17800.65,NSW1NSW1 +44054,2015-01-10 14:00:00,17865.83,NSW1NSW1 +44055,2015-01-10 15:00:00,17841.21,NSW1NSW1 +44056,2015-01-10 16:00:00,17756.79,NSW1NSW1 +44057,2015-01-10 17:00:00,17830.2,NSW1NSW1 +44058,2015-01-10 18:00:00,17247.76,NSW1NSW1 +44059,2015-01-10 19:00:00,16553.67,NSW1NSW1 +44060,2015-01-10 20:00:00,16253.039999999999,NSW1NSW1 +44061,2015-01-10 21:00:00,15566.57,NSW1NSW1 +44062,2015-01-10 22:00:00,14965.89,NSW1NSW1 +44063,2015-01-10 23:00:00,14287.720000000001,NSW1NSW1 +44064,2015-01-11 00:00:00,13454.369999999999,NSW1NSW1 +44065,2015-01-11 01:00:00,12678.56,NSW1NSW1 +44066,2015-01-11 02:00:00,11943.69,NSW1NSW1 +44067,2015-01-11 03:00:00,11645.369999999999,NSW1NSW1 +44068,2015-01-11 04:00:00,11547.9,NSW1NSW1 +44069,2015-01-11 05:00:00,11782.560000000001,NSW1NSW1 +44070,2015-01-11 06:00:00,12270.18,NSW1NSW1 +44071,2015-01-11 07:00:00,13332.42,NSW1NSW1 +44072,2015-01-11 08:00:00,14314.61,NSW1NSW1 +44073,2015-01-11 09:00:00,15190.24,NSW1NSW1 +44074,2015-01-11 10:00:00,15330.349999999999,NSW1NSW1 +44075,2015-01-11 11:00:00,15212.45,NSW1NSW1 +44076,2015-01-11 12:00:00,15077.119999999999,NSW1NSW1 +44077,2015-01-11 13:00:00,14855.58,NSW1NSW1 +44078,2015-01-11 14:00:00,14805.2,NSW1NSW1 +44079,2015-01-11 15:00:00,14897.04,NSW1NSW1 +44080,2015-01-11 16:00:00,14928.86,NSW1NSW1 +44081,2015-01-11 17:00:00,15078.98,NSW1NSW1 +44082,2015-01-11 18:00:00,14975.73,NSW1NSW1 +44083,2015-01-11 19:00:00,14719.369999999999,NSW1NSW1 +44084,2015-01-11 20:00:00,14654.92,NSW1NSW1 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18:00:00,16770.739999999998,NSW1NSW1 +44107,2015-01-12 19:00:00,16433.0,NSW1NSW1 +44108,2015-01-12 20:00:00,16324.97,NSW1NSW1 +44109,2015-01-12 21:00:00,15702.18,NSW1NSW1 +44110,2015-01-12 22:00:00,15161.55,NSW1NSW1 +44111,2015-01-12 23:00:00,14815.18,NSW1NSW1 +44112,2015-01-13 00:00:00,14196.56,NSW1NSW1 +44113,2015-01-13 01:00:00,13214.91,NSW1NSW1 +44114,2015-01-13 02:00:00,12196.939999999999,NSW1NSW1 +44115,2015-01-13 03:00:00,11933.86,NSW1NSW1 +44116,2015-01-13 04:00:00,12301.939999999999,NSW1NSW1 +44117,2015-01-13 05:00:00,13268.24,NSW1NSW1 +44118,2015-01-13 06:00:00,14847.0,NSW1NSW1 +44119,2015-01-13 07:00:00,16313.74,NSW1NSW1 +44120,2015-01-13 08:00:00,17263.92,NSW1NSW1 +44121,2015-01-13 09:00:00,17792.16,NSW1NSW1 +44122,2015-01-13 10:00:00,18036.15,NSW1NSW1 +44123,2015-01-13 11:00:00,18147.690000000002,NSW1NSW1 +44124,2015-01-13 12:00:00,18284.32,NSW1NSW1 +44125,2015-01-13 13:00:00,18595.22,NSW1NSW1 +44126,2015-01-13 14:00:00,18865.38,NSW1NSW1 +44127,2015-01-13 15:00:00,19234.28,NSW1NSW1 +44128,2015-01-13 16:00:00,19220.32,NSW1NSW1 +44129,2015-01-13 17:00:00,18729.760000000002,NSW1NSW1 +44130,2015-01-13 18:00:00,18096.96,NSW1NSW1 +44131,2015-01-13 19:00:00,17680.5,NSW1NSW1 +44132,2015-01-13 20:00:00,17457.97,NSW1NSW1 +44133,2015-01-13 21:00:00,16697.25,NSW1NSW1 +44134,2015-01-13 22:00:00,16016.86,NSW1NSW1 +44135,2015-01-13 23:00:00,15288.98,NSW1NSW1 +44136,2015-01-14 00:00:00,14530.4,NSW1NSW1 +44137,2015-01-14 01:00:00,13424.14,NSW1NSW1 +44138,2015-01-14 02:00:00,12452.79,NSW1NSW1 +44139,2015-01-14 03:00:00,12132.779999999999,NSW1NSW1 +44140,2015-01-14 04:00:00,12530.91,NSW1NSW1 +44141,2015-01-14 05:00:00,13495.92,NSW1NSW1 +44142,2015-01-14 06:00:00,15209.77,NSW1NSW1 +44143,2015-01-14 07:00:00,17170.28,NSW1NSW1 +44144,2015-01-14 08:00:00,18438.64,NSW1NSW1 +44145,2015-01-14 09:00:00,19084.61,NSW1NSW1 +44146,2015-01-14 10:00:00,19395.77,NSW1NSW1 +44147,2015-01-14 11:00:00,19607.4,NSW1NSW1 +44148,2015-01-14 12:00:00,19968.059999999998,NSW1NSW1 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09:00:00,18212.23,NSW1NSW1 +44170,2015-01-15 10:00:00,18531.75,NSW1NSW1 +44171,2015-01-15 11:00:00,18779.67,NSW1NSW1 +44172,2015-01-15 12:00:00,18857.53,NSW1NSW1 +44173,2015-01-15 13:00:00,19053.809999999998,NSW1NSW1 +44174,2015-01-15 14:00:00,19149.9,NSW1NSW1 +44175,2015-01-15 15:00:00,19304.17,NSW1NSW1 +44176,2015-01-15 16:00:00,19469.71,NSW1NSW1 +44177,2015-01-15 17:00:00,19288.19,NSW1NSW1 +44178,2015-01-15 18:00:00,18604.89,NSW1NSW1 +44179,2015-01-15 19:00:00,17875.73,NSW1NSW1 +44180,2015-01-15 20:00:00,17536.78,NSW1NSW1 +44181,2015-01-15 21:00:00,16818.09,NSW1NSW1 +44182,2015-01-15 22:00:00,16064.05,NSW1NSW1 +44183,2015-01-15 23:00:00,15254.68,NSW1NSW1 +44184,2015-01-16 00:00:00,14408.79,NSW1NSW1 +44185,2015-01-16 01:00:00,13455.689999999999,NSW1NSW1 +44186,2015-01-16 02:00:00,12632.89,NSW1NSW1 +44187,2015-01-16 03:00:00,12411.32,NSW1NSW1 +44188,2015-01-16 04:00:00,12652.84,NSW1NSW1 +44189,2015-01-16 05:00:00,13588.96,NSW1NSW1 +44190,2015-01-16 06:00:00,15130.869999999999,NSW1NSW1 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13:00:00,16841.18,NSW1NSW1 +45542,2015-03-13 14:00:00,16666.14,NSW1NSW1 +45543,2015-03-13 15:00:00,16816.989999999998,NSW1NSW1 +45544,2015-03-13 16:00:00,16738.93,NSW1NSW1 +45545,2015-03-13 17:00:00,16531.9,NSW1NSW1 +45546,2015-03-13 18:00:00,16300.05,NSW1NSW1 +45547,2015-03-13 19:00:00,16230.77,NSW1NSW1 +45548,2015-03-13 20:00:00,15592.48,NSW1NSW1 +45549,2015-03-13 21:00:00,15017.560000000001,NSW1NSW1 +45550,2015-03-13 22:00:00,14856.46,NSW1NSW1 +45551,2015-03-13 23:00:00,14599.99,NSW1NSW1 +45552,2015-03-14 00:00:00,14071.77,NSW1NSW1 +45553,2015-03-14 01:00:00,13151.82,NSW1NSW1 +45554,2015-03-14 02:00:00,12149.39,NSW1NSW1 +45555,2015-03-14 03:00:00,11718.43,NSW1NSW1 +45556,2015-03-14 04:00:00,11700.740000000002,NSW1NSW1 +45557,2015-03-14 05:00:00,12217.68,NSW1NSW1 +45558,2015-03-14 06:00:00,13044.869999999999,NSW1NSW1 +45559,2015-03-14 07:00:00,14205.849999999999,NSW1NSW1 +45560,2015-03-14 08:00:00,15035.98,NSW1NSW1 +45561,2015-03-14 09:00:00,15235.22,NSW1NSW1 +45562,2015-03-14 10:00:00,15131.869999999999,NSW1NSW1 +45563,2015-03-14 11:00:00,14888.27,NSW1NSW1 +45564,2015-03-14 12:00:00,14477.560000000001,NSW1NSW1 +45565,2015-03-14 13:00:00,14358.66,NSW1NSW1 +45566,2015-03-14 14:00:00,14309.54,NSW1NSW1 +45567,2015-03-14 15:00:00,14760.35,NSW1NSW1 +45568,2015-03-14 16:00:00,14951.83,NSW1NSW1 +45569,2015-03-14 17:00:00,15180.17,NSW1NSW1 +45570,2015-03-14 18:00:00,15125.76,NSW1NSW1 +45571,2015-03-14 19:00:00,15420.67,NSW1NSW1 +45572,2015-03-14 20:00:00,14872.11,NSW1NSW1 +45573,2015-03-14 21:00:00,14337.189999999999,NSW1NSW1 +45574,2015-03-14 22:00:00,14049.3,NSW1NSW1 +45575,2015-03-14 23:00:00,13594.5,NSW1NSW1 +45576,2015-03-15 00:00:00,13044.07,NSW1NSW1 +45577,2015-03-15 01:00:00,12381.349999999999,NSW1NSW1 +45578,2015-03-15 02:00:00,11658.119999999999,NSW1NSW1 +45579,2015-03-15 03:00:00,11418.509999999998,NSW1NSW1 +45580,2015-03-15 04:00:00,11393.23,NSW1NSW1 +45581,2015-03-15 05:00:00,11595.27,NSW1NSW1 +45582,2015-03-15 06:00:00,11985.05,NSW1NSW1 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01:00:00,13193.45,NSW1NSW1 +45626,2015-03-17 02:00:00,12268.86,NSW1NSW1 +45627,2015-03-17 03:00:00,12026.67,NSW1NSW1 +45628,2015-03-17 04:00:00,12414.46,NSW1NSW1 +45629,2015-03-17 05:00:00,13726.58,NSW1NSW1 +45630,2015-03-17 06:00:00,15685.54,NSW1NSW1 +45631,2015-03-17 07:00:00,16730.16,NSW1NSW1 +45632,2015-03-17 08:00:00,16751.48,NSW1NSW1 +45633,2015-03-17 09:00:00,16831.3,NSW1NSW1 +45634,2015-03-17 10:00:00,16861.82,NSW1NSW1 +45635,2015-03-17 11:00:00,16985.94,NSW1NSW1 +45636,2015-03-17 12:00:00,16977.67,NSW1NSW1 +45637,2015-03-17 13:00:00,17013.53,NSW1NSW1 +45638,2015-03-17 14:00:00,17084.23,NSW1NSW1 +45639,2015-03-17 15:00:00,17286.77,NSW1NSW1 +45640,2015-03-17 16:00:00,17292.18,NSW1NSW1 +45641,2015-03-17 17:00:00,17213.61,NSW1NSW1 +45642,2015-03-17 18:00:00,16987.31,NSW1NSW1 +45643,2015-03-17 19:00:00,17038.98,NSW1NSW1 +45644,2015-03-17 20:00:00,16453.02,NSW1NSW1 +45645,2015-03-17 21:00:00,15605.55,NSW1NSW1 +45646,2015-03-17 22:00:00,15247.130000000001,NSW1NSW1 +45647,2015-03-17 23:00:00,14729.560000000001,NSW1NSW1 +45648,2015-03-18 00:00:00,14266.82,NSW1NSW1 +45649,2015-03-18 01:00:00,13376.369999999999,NSW1NSW1 +45650,2015-03-18 02:00:00,12365.64,NSW1NSW1 +45651,2015-03-18 03:00:00,12053.71,NSW1NSW1 +45652,2015-03-18 04:00:00,12466.84,NSW1NSW1 +45653,2015-03-18 05:00:00,13806.9,NSW1NSW1 +45654,2015-03-18 06:00:00,15877.91,NSW1NSW1 +45655,2015-03-18 07:00:00,17156.98,NSW1NSW1 +45656,2015-03-18 08:00:00,17458.71,NSW1NSW1 +45657,2015-03-18 09:00:00,17632.21,NSW1NSW1 +45658,2015-03-18 10:00:00,17745.16,NSW1NSW1 +45659,2015-03-18 11:00:00,17865.62,NSW1NSW1 +45660,2015-03-18 12:00:00,18012.64,NSW1NSW1 +45661,2015-03-18 13:00:00,18093.940000000002,NSW1NSW1 +45662,2015-03-18 14:00:00,18366.690000000002,NSW1NSW1 +45663,2015-03-18 15:00:00,18745.949999999997,NSW1NSW1 +45664,2015-03-18 16:00:00,18944.309999999998,NSW1NSW1 +45665,2015-03-18 17:00:00,18536.78,NSW1NSW1 +45666,2015-03-18 18:00:00,18146.08,NSW1NSW1 +45667,2015-03-18 19:00:00,18147.91,NSW1NSW1 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16:00:00,20504.11,NSW1NSW1 +45689,2015-03-19 17:00:00,20386.71,NSW1NSW1 +45690,2015-03-19 18:00:00,19689.68,NSW1NSW1 +45691,2015-03-19 19:00:00,19398.370000000003,NSW1NSW1 +45692,2015-03-19 20:00:00,18259.61,NSW1NSW1 +45693,2015-03-19 21:00:00,16981.53,NSW1NSW1 +45694,2015-03-19 22:00:00,16104.59,NSW1NSW1 +45695,2015-03-19 23:00:00,15447.99,NSW1NSW1 +45696,2015-03-20 00:00:00,14670.36,NSW1NSW1 +45697,2015-03-20 01:00:00,13750.11,NSW1NSW1 +45698,2015-03-20 02:00:00,12751.21,NSW1NSW1 +45699,2015-03-20 03:00:00,12440.029999999999,NSW1NSW1 +45700,2015-03-20 04:00:00,12720.33,NSW1NSW1 +45701,2015-03-20 05:00:00,14036.02,NSW1NSW1 +45702,2015-03-20 06:00:00,16018.0,NSW1NSW1 +45703,2015-03-20 07:00:00,17181.73,NSW1NSW1 +45704,2015-03-20 08:00:00,17636.79,NSW1NSW1 +45705,2015-03-20 09:00:00,18153.46,NSW1NSW1 +45706,2015-03-20 10:00:00,18720.29,NSW1NSW1 +45707,2015-03-20 11:00:00,19115.440000000002,NSW1NSW1 +45708,2015-03-20 12:00:00,19524.309999999998,NSW1NSW1 +45709,2015-03-20 13:00:00,19740.23,NSW1NSW1 +45710,2015-03-20 14:00:00,19518.34,NSW1NSW1 +45711,2015-03-20 15:00:00,19184.800000000003,NSW1NSW1 +45712,2015-03-20 16:00:00,18778.84,NSW1NSW1 +45713,2015-03-20 17:00:00,18034.0,NSW1NSW1 +45714,2015-03-20 18:00:00,17524.14,NSW1NSW1 +45715,2015-03-20 19:00:00,17040.8,NSW1NSW1 +45716,2015-03-20 20:00:00,16176.580000000002,NSW1NSW1 +45717,2015-03-20 21:00:00,15528.26,NSW1NSW1 +45718,2015-03-20 22:00:00,15141.23,NSW1NSW1 +45719,2015-03-20 23:00:00,14736.45,NSW1NSW1 +45720,2015-03-21 00:00:00,14022.25,NSW1NSW1 +45721,2015-03-21 01:00:00,13053.599999999999,NSW1NSW1 +45722,2015-03-21 02:00:00,12013.34,NSW1NSW1 +45723,2015-03-21 03:00:00,11700.69,NSW1NSW1 +45724,2015-03-21 04:00:00,11848.24,NSW1NSW1 +45725,2015-03-21 05:00:00,12360.869999999999,NSW1NSW1 +45726,2015-03-21 06:00:00,13200.689999999999,NSW1NSW1 +45727,2015-03-21 07:00:00,14425.84,NSW1NSW1 +45728,2015-03-21 08:00:00,15355.31,NSW1NSW1 +45729,2015-03-21 09:00:00,15712.32,NSW1NSW1 +45730,2015-03-21 10:00:00,15603.29,NSW1NSW1 +45731,2015-03-21 11:00:00,15280.119999999999,NSW1NSW1 +45732,2015-03-21 12:00:00,14935.82,NSW1NSW1 +45733,2015-03-21 13:00:00,14683.68,NSW1NSW1 +45734,2015-03-21 14:00:00,14537.119999999999,NSW1NSW1 +45735,2015-03-21 15:00:00,14549.060000000001,NSW1NSW1 +45736,2015-03-21 16:00:00,14772.14,NSW1NSW1 +45737,2015-03-21 17:00:00,15004.35,NSW1NSW1 +45738,2015-03-21 18:00:00,15249.93,NSW1NSW1 +45739,2015-03-21 19:00:00,15223.119999999999,NSW1NSW1 +45740,2015-03-21 20:00:00,14684.01,NSW1NSW1 +45741,2015-03-21 21:00:00,14245.439999999999,NSW1NSW1 +45742,2015-03-21 22:00:00,14086.45,NSW1NSW1 +45743,2015-03-21 23:00:00,13555.78,NSW1NSW1 +45744,2015-03-22 00:00:00,13022.220000000001,NSW1NSW1 +45745,2015-03-22 01:00:00,12284.55,NSW1NSW1 +45746,2015-03-22 02:00:00,11551.71,NSW1NSW1 +45747,2015-03-22 03:00:00,11371.15,NSW1NSW1 +45748,2015-03-22 04:00:00,11327.02,NSW1NSW1 +45749,2015-03-22 05:00:00,11707.91,NSW1NSW1 +45750,2015-03-22 06:00:00,12379.54,NSW1NSW1 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04:00:00,12106.19,NSW1NSW1 +45773,2015-03-23 05:00:00,13532.279999999999,NSW1NSW1 +45774,2015-03-23 06:00:00,15660.83,NSW1NSW1 +45775,2015-03-23 07:00:00,16782.1,NSW1NSW1 +45776,2015-03-23 08:00:00,17187.33,NSW1NSW1 +45777,2015-03-23 09:00:00,17518.39,NSW1NSW1 +45778,2015-03-23 10:00:00,17493.22,NSW1NSW1 +45779,2015-03-23 11:00:00,17431.52,NSW1NSW1 +45780,2015-03-23 12:00:00,17578.74,NSW1NSW1 +45781,2015-03-23 13:00:00,17842.9,NSW1NSW1 +45782,2015-03-23 14:00:00,18058.12,NSW1NSW1 +45783,2015-03-23 15:00:00,18419.760000000002,NSW1NSW1 +45784,2015-03-23 16:00:00,18695.9,NSW1NSW1 +45785,2015-03-23 17:00:00,18542.690000000002,NSW1NSW1 +45786,2015-03-23 18:00:00,18068.019999999997,NSW1NSW1 +45787,2015-03-23 19:00:00,17941.01,NSW1NSW1 +45788,2015-03-23 20:00:00,16928.11,NSW1NSW1 +45789,2015-03-23 21:00:00,16063.98,NSW1NSW1 +45790,2015-03-23 22:00:00,15562.65,NSW1NSW1 +45791,2015-03-23 23:00:00,15037.53,NSW1NSW1 +45792,2015-03-24 00:00:00,14280.46,NSW1NSW1 +45793,2015-03-24 01:00:00,13382.18,NSW1NSW1 +45794,2015-03-24 02:00:00,12430.970000000001,NSW1NSW1 +45795,2015-03-24 03:00:00,12073.19,NSW1NSW1 +45796,2015-03-24 04:00:00,12417.84,NSW1NSW1 +45797,2015-03-24 05:00:00,13932.369999999999,NSW1NSW1 +45798,2015-03-24 06:00:00,16101.35,NSW1NSW1 +45799,2015-03-24 07:00:00,17375.57,NSW1NSW1 +45800,2015-03-24 08:00:00,17675.800000000003,NSW1NSW1 +45801,2015-03-24 09:00:00,18014.05,NSW1NSW1 +45802,2015-03-24 10:00:00,18235.23,NSW1NSW1 +45803,2015-03-24 11:00:00,18351.16,NSW1NSW1 +45804,2015-03-24 12:00:00,18626.52,NSW1NSW1 +45805,2015-03-24 13:00:00,18371.94,NSW1NSW1 +45806,2015-03-24 14:00:00,18155.84,NSW1NSW1 +45807,2015-03-24 15:00:00,17981.98,NSW1NSW1 +45808,2015-03-24 16:00:00,17917.19,NSW1NSW1 +45809,2015-03-24 17:00:00,17816.92,NSW1NSW1 +45810,2015-03-24 18:00:00,17640.61,NSW1NSW1 +45811,2015-03-24 19:00:00,17268.98,NSW1NSW1 +45812,2015-03-24 20:00:00,16528.309999999998,NSW1NSW1 +45813,2015-03-24 21:00:00,15740.89,NSW1NSW1 +45814,2015-03-24 22:00:00,15234.740000000002,NSW1NSW1 +45815,2015-03-24 23:00:00,14756.41,NSW1NSW1 +45816,2015-03-25 00:00:00,14166.36,NSW1NSW1 +45817,2015-03-25 01:00:00,13272.08,NSW1NSW1 +45818,2015-03-25 02:00:00,12321.69,NSW1NSW1 +45819,2015-03-25 03:00:00,12036.380000000001,NSW1NSW1 +45820,2015-03-25 04:00:00,12402.83,NSW1NSW1 +45821,2015-03-25 05:00:00,13740.35,NSW1NSW1 +45822,2015-03-25 06:00:00,15754.130000000001,NSW1NSW1 +45823,2015-03-25 07:00:00,16583.58,NSW1NSW1 +45824,2015-03-25 08:00:00,16575.519999999997,NSW1NSW1 +45825,2015-03-25 09:00:00,16668.85,NSW1NSW1 +45826,2015-03-25 10:00:00,16737.7,NSW1NSW1 +45827,2015-03-25 11:00:00,16703.79,NSW1NSW1 +45828,2015-03-25 12:00:00,16747.05,NSW1NSW1 +45829,2015-03-25 13:00:00,16795.34,NSW1NSW1 +45830,2015-03-25 14:00:00,16696.0,NSW1NSW1 +45831,2015-03-25 15:00:00,16893.83,NSW1NSW1 +45832,2015-03-25 16:00:00,16959.949999999997,NSW1NSW1 +45833,2015-03-25 17:00:00,16844.67,NSW1NSW1 +45834,2015-03-25 18:00:00,16736.6,NSW1NSW1 +45835,2015-03-25 19:00:00,16709.91,NSW1NSW1 +45836,2015-03-25 20:00:00,15957.54,NSW1NSW1 +45837,2015-03-25 21:00:00,15284.6,NSW1NSW1 +45838,2015-03-25 22:00:00,14937.91,NSW1NSW1 +45839,2015-03-25 23:00:00,14712.76,NSW1NSW1 +45840,2015-03-26 00:00:00,14138.71,NSW1NSW1 +45841,2015-03-26 01:00:00,13157.76,NSW1NSW1 +45842,2015-03-26 02:00:00,12129.720000000001,NSW1NSW1 +45843,2015-03-26 03:00:00,11857.18,NSW1NSW1 +45844,2015-03-26 04:00:00,12175.400000000001,NSW1NSW1 +45845,2015-03-26 05:00:00,13527.119999999999,NSW1NSW1 +45846,2015-03-26 06:00:00,15553.900000000001,NSW1NSW1 +45847,2015-03-26 07:00:00,16464.21,NSW1NSW1 +45848,2015-03-26 08:00:00,16662.769999999997,NSW1NSW1 +45849,2015-03-26 09:00:00,16618.75,NSW1NSW1 +45850,2015-03-26 10:00:00,16574.620000000003,NSW1NSW1 +45851,2015-03-26 11:00:00,16678.52,NSW1NSW1 +45852,2015-03-26 12:00:00,16673.36,NSW1NSW1 +45853,2015-03-26 13:00:00,16731.95,NSW1NSW1 +45854,2015-03-26 14:00:00,16913.440000000002,NSW1NSW1 +45855,2015-03-26 15:00:00,17167.67,NSW1NSW1 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04:00:00,10848.17,NSW1NSW1 +46085,2015-04-05 05:00:00,11037.67,NSW1NSW1 +46086,2015-04-05 06:00:00,11394.56,NSW1NSW1 +46087,2015-04-05 07:00:00,12299.89,NSW1NSW1 +46088,2015-04-05 08:00:00,13365.36,NSW1NSW1 +46089,2015-04-05 09:00:00,13974.11,NSW1NSW1 +46090,2015-04-05 10:00:00,13913.130000000001,NSW1NSW1 +46091,2015-04-05 11:00:00,13661.04,NSW1NSW1 +46092,2015-04-05 12:00:00,13494.689999999999,NSW1NSW1 +46093,2015-04-05 13:00:00,13325.92,NSW1NSW1 +46094,2015-04-05 14:00:00,13158.619999999999,NSW1NSW1 +46095,2015-04-05 15:00:00,13199.31,NSW1NSW1 +46096,2015-04-05 16:00:00,13474.0,NSW1NSW1 +46097,2015-04-05 17:00:00,14022.16,NSW1NSW1 +46098,2015-04-05 18:00:00,14739.68,NSW1NSW1 +46099,2015-04-05 19:00:00,14877.36,NSW1NSW1 +46100,2015-04-05 20:00:00,14143.29,NSW1NSW1 +46101,2015-04-05 21:00:00,13592.2,NSW1NSW1 +46102,2015-04-05 22:00:00,13354.9,NSW1NSW1 +46103,2015-04-05 23:00:00,13341.349999999999,NSW1NSW1 +46104,2015-04-06 00:00:00,12947.279999999999,NSW1NSW1 +46105,2015-04-06 01:00:00,12277.58,NSW1NSW1 +46106,2015-04-06 02:00:00,11589.2,NSW1NSW1 +46107,2015-04-06 03:00:00,11019.85,NSW1NSW1 +46108,2015-04-06 04:00:00,10828.060000000001,NSW1NSW1 +46109,2015-04-06 05:00:00,11012.380000000001,NSW1NSW1 +46110,2015-04-06 06:00:00,11531.42,NSW1NSW1 +46111,2015-04-06 07:00:00,12174.369999999999,NSW1NSW1 +46112,2015-04-06 08:00:00,12923.89,NSW1NSW1 +46113,2015-04-06 09:00:00,13723.99,NSW1NSW1 +46114,2015-04-06 10:00:00,14144.869999999999,NSW1NSW1 +46115,2015-04-06 11:00:00,14215.16,NSW1NSW1 +46116,2015-04-06 12:00:00,14218.34,NSW1NSW1 +46117,2015-04-06 13:00:00,14240.19,NSW1NSW1 +46118,2015-04-06 14:00:00,14315.84,NSW1NSW1 +46119,2015-04-06 15:00:00,14384.39,NSW1NSW1 +46120,2015-04-06 16:00:00,14553.01,NSW1NSW1 +46121,2015-04-06 17:00:00,15107.64,NSW1NSW1 +46122,2015-04-06 18:00:00,16015.46,NSW1NSW1 +46123,2015-04-06 19:00:00,15561.48,NSW1NSW1 +46124,2015-04-06 20:00:00,14609.71,NSW1NSW1 +46125,2015-04-06 21:00:00,13927.05,NSW1NSW1 +46126,2015-04-06 22:00:00,13697.619999999999,NSW1NSW1 +46127,2015-04-06 23:00:00,13636.0,NSW1NSW1 +46128,2015-04-07 00:00:00,13481.79,NSW1NSW1 +46129,2015-04-07 01:00:00,12785.82,NSW1NSW1 +46130,2015-04-07 02:00:00,12005.529999999999,NSW1NSW1 +46131,2015-04-07 03:00:00,11248.630000000001,NSW1NSW1 +46132,2015-04-07 04:00:00,11054.09,NSW1NSW1 +46133,2015-04-07 05:00:00,11619.380000000001,NSW1NSW1 +46134,2015-04-07 06:00:00,12894.2,NSW1NSW1 +46135,2015-04-07 07:00:00,14417.619999999999,NSW1NSW1 +46136,2015-04-07 08:00:00,15412.69,NSW1NSW1 +46137,2015-04-07 09:00:00,15873.1,NSW1NSW1 +46138,2015-04-07 10:00:00,16076.099999999999,NSW1NSW1 +46139,2015-04-07 11:00:00,16093.89,NSW1NSW1 +46140,2015-04-07 12:00:00,16161.36,NSW1NSW1 +46141,2015-04-07 13:00:00,16413.03,NSW1NSW1 +46142,2015-04-07 14:00:00,15952.64,NSW1NSW1 +46143,2015-04-07 15:00:00,15787.970000000001,NSW1NSW1 +46144,2015-04-07 16:00:00,15884.92,NSW1NSW1 +46145,2015-04-07 17:00:00,16289.84,NSW1NSW1 +46146,2015-04-07 18:00:00,17303.87,NSW1NSW1 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16:00:00,15920.43,NSW1NSW1 +46169,2015-04-08 17:00:00,16378.48,NSW1NSW1 +46170,2015-04-08 18:00:00,17448.57,NSW1NSW1 +46171,2015-04-08 19:00:00,17218.85,NSW1NSW1 +46172,2015-04-08 20:00:00,16240.380000000001,NSW1NSW1 +46173,2015-04-08 21:00:00,15505.91,NSW1NSW1 +46174,2015-04-08 22:00:00,15064.3,NSW1NSW1 +46175,2015-04-08 23:00:00,14814.84,NSW1NSW1 +46176,2015-04-09 00:00:00,14549.67,NSW1NSW1 +46177,2015-04-09 01:00:00,13790.970000000001,NSW1NSW1 +46178,2015-04-09 02:00:00,12753.5,NSW1NSW1 +46179,2015-04-09 03:00:00,11891.23,NSW1NSW1 +46180,2015-04-09 04:00:00,11652.380000000001,NSW1NSW1 +46181,2015-04-09 05:00:00,12076.66,NSW1NSW1 +46182,2015-04-09 06:00:00,13399.17,NSW1NSW1 +46183,2015-04-09 07:00:00,14927.74,NSW1NSW1 +46184,2015-04-09 08:00:00,15626.52,NSW1NSW1 +46185,2015-04-09 09:00:00,15905.189999999999,NSW1NSW1 +46186,2015-04-09 10:00:00,15913.57,NSW1NSW1 +46187,2015-04-09 11:00:00,15888.76,NSW1NSW1 +46188,2015-04-09 12:00:00,15697.779999999999,NSW1NSW1 +46189,2015-04-09 13:00:00,15483.14,NSW1NSW1 +46190,2015-04-09 14:00:00,15419.119999999999,NSW1NSW1 +46191,2015-04-09 15:00:00,15466.0,NSW1NSW1 +46192,2015-04-09 16:00:00,15716.150000000001,NSW1NSW1 +46193,2015-04-09 17:00:00,16091.369999999999,NSW1NSW1 +46194,2015-04-09 18:00:00,17245.08,NSW1NSW1 +46195,2015-04-09 19:00:00,17262.39,NSW1NSW1 +46196,2015-04-09 20:00:00,16392.42,NSW1NSW1 +46197,2015-04-09 21:00:00,15616.470000000001,NSW1NSW1 +46198,2015-04-09 22:00:00,15143.96,NSW1NSW1 +46199,2015-04-09 23:00:00,14871.060000000001,NSW1NSW1 +46200,2015-04-10 00:00:00,14555.380000000001,NSW1NSW1 +46201,2015-04-10 01:00:00,13919.21,NSW1NSW1 +46202,2015-04-10 02:00:00,12935.64,NSW1NSW1 +46203,2015-04-10 03:00:00,12056.15,NSW1NSW1 +46204,2015-04-10 04:00:00,11799.97,NSW1NSW1 +46205,2015-04-10 05:00:00,12113.349999999999,NSW1NSW1 +46206,2015-04-10 06:00:00,13419.939999999999,NSW1NSW1 +46207,2015-04-10 07:00:00,14864.900000000001,NSW1NSW1 +46208,2015-04-10 08:00:00,15718.41,NSW1NSW1 +46209,2015-04-10 09:00:00,16094.46,NSW1NSW1 +46210,2015-04-10 10:00:00,16140.97,NSW1NSW1 +46211,2015-04-10 11:00:00,16046.8,NSW1NSW1 +46212,2015-04-10 12:00:00,15975.98,NSW1NSW1 +46213,2015-04-10 13:00:00,15735.529999999999,NSW1NSW1 +46214,2015-04-10 14:00:00,15696.91,NSW1NSW1 +46215,2015-04-10 15:00:00,15670.279999999999,NSW1NSW1 +46216,2015-04-10 16:00:00,15793.44,NSW1NSW1 +46217,2015-04-10 17:00:00,16176.74,NSW1NSW1 +46218,2015-04-10 18:00:00,17030.15,NSW1NSW1 +46219,2015-04-10 19:00:00,16605.96,NSW1NSW1 +46220,2015-04-10 20:00:00,15761.83,NSW1NSW1 +46221,2015-04-10 21:00:00,15085.84,NSW1NSW1 +46222,2015-04-10 22:00:00,14774.5,NSW1NSW1 +46223,2015-04-10 23:00:00,14731.71,NSW1NSW1 +46224,2015-04-11 00:00:00,14594.51,NSW1NSW1 +46225,2015-04-11 01:00:00,13831.33,NSW1NSW1 +46226,2015-04-11 02:00:00,12830.95,NSW1NSW1 +46227,2015-04-11 03:00:00,11834.05,NSW1NSW1 +46228,2015-04-11 04:00:00,11498.55,NSW1NSW1 +46229,2015-04-11 05:00:00,11527.01,NSW1NSW1 +46230,2015-04-11 06:00:00,12083.26,NSW1NSW1 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14:00:00,16726.870000000003,NSW1NSW1 +47007,2015-05-13 15:00:00,16850.769999999997,NSW1NSW1 +47008,2015-05-13 16:00:00,17838.35,NSW1NSW1 +47009,2015-05-13 17:00:00,19552.27,NSW1NSW1 +47010,2015-05-13 18:00:00,21251.6,NSW1NSW1 +47011,2015-05-13 19:00:00,20832.66,NSW1NSW1 +47012,2015-05-13 20:00:00,19835.19,NSW1NSW1 +47013,2015-05-13 21:00:00,18831.48,NSW1NSW1 +47014,2015-05-13 22:00:00,17775.309999999998,NSW1NSW1 +47015,2015-05-13 23:00:00,16907.559999999998,NSW1NSW1 +47016,2015-05-14 00:00:00,16203.490000000002,NSW1NSW1 +47017,2015-05-14 01:00:00,15340.74,NSW1NSW1 +47018,2015-05-14 02:00:00,14249.29,NSW1NSW1 +47019,2015-05-14 03:00:00,13253.96,NSW1NSW1 +47020,2015-05-14 04:00:00,12914.96,NSW1NSW1 +47021,2015-05-14 05:00:00,13478.75,NSW1NSW1 +47022,2015-05-14 06:00:00,15562.630000000001,NSW1NSW1 +47023,2015-05-14 07:00:00,18420.760000000002,NSW1NSW1 +47024,2015-05-14 08:00:00,19291.88,NSW1NSW1 +47025,2015-05-14 09:00:00,18469.85,NSW1NSW1 +47026,2015-05-14 10:00:00,17736.39,NSW1NSW1 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04:00:00,12468.6,NSW1NSW1 +47069,2015-05-16 05:00:00,12605.71,NSW1NSW1 +47070,2015-05-16 06:00:00,13261.900000000001,NSW1NSW1 +47071,2015-05-16 07:00:00,14499.57,NSW1NSW1 +47072,2015-05-16 08:00:00,15822.97,NSW1NSW1 +47073,2015-05-16 09:00:00,16371.42,NSW1NSW1 +47074,2015-05-16 10:00:00,16195.92,NSW1NSW1 +47075,2015-05-16 11:00:00,15675.99,NSW1NSW1 +47076,2015-05-16 12:00:00,15276.630000000001,NSW1NSW1 +47077,2015-05-16 13:00:00,15015.119999999999,NSW1NSW1 +47078,2015-05-16 14:00:00,14829.939999999999,NSW1NSW1 +47079,2015-05-16 15:00:00,14894.470000000001,NSW1NSW1 +47080,2015-05-16 16:00:00,15506.369999999999,NSW1NSW1 +47081,2015-05-16 17:00:00,16715.8,NSW1NSW1 +47082,2015-05-16 18:00:00,18108.190000000002,NSW1NSW1 +47083,2015-05-16 19:00:00,17577.14,NSW1NSW1 +47084,2015-05-16 20:00:00,16833.07,NSW1NSW1 +47085,2015-05-16 21:00:00,16297.509999999998,NSW1NSW1 +47086,2015-05-16 22:00:00,15817.6,NSW1NSW1 +47087,2015-05-16 23:00:00,15365.779999999999,NSW1NSW1 +47088,2015-05-17 00:00:00,14911.6,NSW1NSW1 +47089,2015-05-17 01:00:00,14141.11,NSW1NSW1 +47090,2015-05-17 02:00:00,13204.64,NSW1NSW1 +47091,2015-05-17 03:00:00,12355.52,NSW1NSW1 +47092,2015-05-17 04:00:00,12058.99,NSW1NSW1 +47093,2015-05-17 05:00:00,12167.59,NSW1NSW1 +47094,2015-05-17 06:00:00,12687.34,NSW1NSW1 +47095,2015-05-17 07:00:00,13608.96,NSW1NSW1 +47096,2015-05-17 08:00:00,14954.4,NSW1NSW1 +47097,2015-05-17 09:00:00,15730.95,NSW1NSW1 +47098,2015-05-17 10:00:00,15783.89,NSW1NSW1 +47099,2015-05-17 11:00:00,15296.619999999999,NSW1NSW1 +47100,2015-05-17 12:00:00,14905.11,NSW1NSW1 +47101,2015-05-17 13:00:00,14793.96,NSW1NSW1 +47102,2015-05-17 14:00:00,14641.59,NSW1NSW1 +47103,2015-05-17 15:00:00,14856.720000000001,NSW1NSW1 +47104,2015-05-17 16:00:00,15484.85,NSW1NSW1 +47105,2015-05-17 17:00:00,16860.18,NSW1NSW1 +47106,2015-05-17 18:00:00,18471.29,NSW1NSW1 +47107,2015-05-17 19:00:00,18165.3,NSW1NSW1 +47108,2015-05-17 20:00:00,17419.59,NSW1NSW1 +47109,2015-05-17 21:00:00,16722.54,NSW1NSW1 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18:00:00,20298.96,NSW1NSW1 +47131,2015-05-18 19:00:00,19617.02,NSW1NSW1 +47132,2015-05-18 20:00:00,18633.06,NSW1NSW1 +47133,2015-05-18 21:00:00,17845.71,NSW1NSW1 +47134,2015-05-18 22:00:00,17027.78,NSW1NSW1 +47135,2015-05-18 23:00:00,16269.8,NSW1NSW1 +47136,2015-05-19 00:00:00,15764.68,NSW1NSW1 +47137,2015-05-19 01:00:00,14919.58,NSW1NSW1 +47138,2015-05-19 02:00:00,13907.98,NSW1NSW1 +47139,2015-05-19 03:00:00,12861.759999999998,NSW1NSW1 +47140,2015-05-19 04:00:00,12474.59,NSW1NSW1 +47141,2015-05-19 05:00:00,12993.220000000001,NSW1NSW1 +47142,2015-05-19 06:00:00,14649.220000000001,NSW1NSW1 +47143,2015-05-19 07:00:00,16951.6,NSW1NSW1 +47144,2015-05-19 08:00:00,18147.17,NSW1NSW1 +47145,2015-05-19 09:00:00,17991.53,NSW1NSW1 +47146,2015-05-19 10:00:00,18027.629999999997,NSW1NSW1 +47147,2015-05-19 11:00:00,17835.41,NSW1NSW1 +47148,2015-05-19 12:00:00,17539.760000000002,NSW1NSW1 +47149,2015-05-19 13:00:00,17321.78,NSW1NSW1 +47150,2015-05-19 14:00:00,17172.03,NSW1NSW1 +47151,2015-05-19 15:00:00,17106.39,NSW1NSW1 +47152,2015-05-19 16:00:00,17711.58,NSW1NSW1 +47153,2015-05-19 17:00:00,18896.92,NSW1NSW1 +47154,2015-05-19 18:00:00,19692.769999999997,NSW1NSW1 +47155,2015-05-19 19:00:00,18973.510000000002,NSW1NSW1 +47156,2015-05-19 20:00:00,18128.45,NSW1NSW1 +47157,2015-05-19 21:00:00,17122.96,NSW1NSW1 +47158,2015-05-19 22:00:00,16190.98,NSW1NSW1 +47159,2015-05-19 23:00:00,15699.59,NSW1NSW1 +47160,2015-05-20 00:00:00,15384.8,NSW1NSW1 +47161,2015-05-20 01:00:00,14624.45,NSW1NSW1 +47162,2015-05-20 02:00:00,13550.04,NSW1NSW1 +47163,2015-05-20 03:00:00,12454.91,NSW1NSW1 +47164,2015-05-20 04:00:00,12130.33,NSW1NSW1 +47165,2015-05-20 05:00:00,12633.32,NSW1NSW1 +47166,2015-05-20 06:00:00,14298.66,NSW1NSW1 +47167,2015-05-20 07:00:00,16627.02,NSW1NSW1 +47168,2015-05-20 08:00:00,17602.05,NSW1NSW1 +47169,2015-05-20 09:00:00,17325.730000000003,NSW1NSW1 +47170,2015-05-20 10:00:00,17106.39,NSW1NSW1 +47171,2015-05-20 11:00:00,16728.3,NSW1NSW1 +47172,2015-05-20 12:00:00,16565.050000000003,NSW1NSW1 +47173,2015-05-20 13:00:00,16428.43,NSW1NSW1 +47174,2015-05-20 14:00:00,16458.39,NSW1NSW1 +47175,2015-05-20 15:00:00,16540.2,NSW1NSW1 +47176,2015-05-20 16:00:00,16978.239999999998,NSW1NSW1 +47177,2015-05-20 17:00:00,18049.67,NSW1NSW1 +47178,2015-05-20 18:00:00,18979.63,NSW1NSW1 +47179,2015-05-20 19:00:00,18256.1,NSW1NSW1 +47180,2015-05-20 20:00:00,17392.5,NSW1NSW1 +47181,2015-05-20 21:00:00,16668.95,NSW1NSW1 +47182,2015-05-20 22:00:00,16135.64,NSW1NSW1 +47183,2015-05-20 23:00:00,15666.34,NSW1NSW1 +47184,2015-05-21 00:00:00,15382.71,NSW1NSW1 +47185,2015-05-21 01:00:00,14659.25,NSW1NSW1 +47186,2015-05-21 02:00:00,13664.18,NSW1NSW1 +47187,2015-05-21 03:00:00,12767.99,NSW1NSW1 +47188,2015-05-21 04:00:00,12434.8,NSW1NSW1 +47189,2015-05-21 05:00:00,12924.81,NSW1NSW1 +47190,2015-05-21 06:00:00,14620.47,NSW1NSW1 +47191,2015-05-21 07:00:00,16805.18,NSW1NSW1 +47192,2015-05-21 08:00:00,17506.93,NSW1NSW1 +47193,2015-05-21 09:00:00,17222.81,NSW1NSW1 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06:00:00,14629.27,NSW1NSW1 +47215,2015-05-22 07:00:00,17048.91,NSW1NSW1 +47216,2015-05-22 08:00:00,18182.66,NSW1NSW1 +47217,2015-05-22 09:00:00,18185.36,NSW1NSW1 +47218,2015-05-22 10:00:00,18423.8,NSW1NSW1 +47219,2015-05-22 11:00:00,18421.25,NSW1NSW1 +47220,2015-05-22 12:00:00,18275.96,NSW1NSW1 +47221,2015-05-22 13:00:00,17806.71,NSW1NSW1 +47222,2015-05-22 14:00:00,17447.65,NSW1NSW1 +47223,2015-05-22 15:00:00,17289.739999999998,NSW1NSW1 +47224,2015-05-22 16:00:00,17885.300000000003,NSW1NSW1 +47225,2015-05-22 17:00:00,19192.620000000003,NSW1NSW1 +47226,2015-05-22 18:00:00,20240.050000000003,NSW1NSW1 +47227,2015-05-22 19:00:00,19534.34,NSW1NSW1 +47228,2015-05-22 20:00:00,18598.29,NSW1NSW1 +47229,2015-05-22 21:00:00,17851.21,NSW1NSW1 +47230,2015-05-22 22:00:00,17168.949999999997,NSW1NSW1 +47231,2015-05-22 23:00:00,16784.35,NSW1NSW1 +47232,2015-05-23 00:00:00,16344.73,NSW1NSW1 +47233,2015-05-23 01:00:00,15441.16,NSW1NSW1 +47234,2015-05-23 02:00:00,14277.95,NSW1NSW1 +47235,2015-05-23 03:00:00,13095.720000000001,NSW1NSW1 +47236,2015-05-23 04:00:00,12530.5,NSW1NSW1 +47237,2015-05-23 05:00:00,12625.09,NSW1NSW1 +47238,2015-05-23 06:00:00,13393.55,NSW1NSW1 +47239,2015-05-23 07:00:00,14700.0,NSW1NSW1 +47240,2015-05-23 08:00:00,16250.73,NSW1NSW1 +47241,2015-05-23 09:00:00,16964.4,NSW1NSW1 +47242,2015-05-23 10:00:00,16628.77,NSW1NSW1 +47243,2015-05-23 11:00:00,16016.68,NSW1NSW1 +47244,2015-05-23 12:00:00,15452.55,NSW1NSW1 +47245,2015-05-23 13:00:00,15111.99,NSW1NSW1 +47246,2015-05-23 14:00:00,14922.009999999998,NSW1NSW1 +47247,2015-05-23 15:00:00,15096.95,NSW1NSW1 +47248,2015-05-23 16:00:00,15698.9,NSW1NSW1 +47249,2015-05-23 17:00:00,17362.57,NSW1NSW1 +47250,2015-05-23 18:00:00,18890.43,NSW1NSW1 +47251,2015-05-23 19:00:00,18377.83,NSW1NSW1 +47252,2015-05-23 20:00:00,17673.260000000002,NSW1NSW1 +47253,2015-05-23 21:00:00,17146.35,NSW1NSW1 +47254,2015-05-23 22:00:00,16652.62,NSW1NSW1 +47255,2015-05-23 23:00:00,16312.380000000001,NSW1NSW1 +47256,2015-05-24 00:00:00,15661.21,NSW1NSW1 +47257,2015-05-24 01:00:00,14698.01,NSW1NSW1 +47258,2015-05-24 02:00:00,13737.94,NSW1NSW1 +47259,2015-05-24 03:00:00,12845.279999999999,NSW1NSW1 +47260,2015-05-24 04:00:00,12523.75,NSW1NSW1 +47261,2015-05-24 05:00:00,12652.69,NSW1NSW1 +47262,2015-05-24 06:00:00,13213.23,NSW1NSW1 +47263,2015-05-24 07:00:00,14224.310000000001,NSW1NSW1 +47264,2015-05-24 08:00:00,15740.41,NSW1NSW1 +47265,2015-05-24 09:00:00,16566.04,NSW1NSW1 +47266,2015-05-24 10:00:00,16515.0,NSW1NSW1 +47267,2015-05-24 11:00:00,15951.98,NSW1NSW1 +47268,2015-05-24 12:00:00,15221.619999999999,NSW1NSW1 +47269,2015-05-24 13:00:00,14853.279999999999,NSW1NSW1 +47270,2015-05-24 14:00:00,14695.5,NSW1NSW1 +47271,2015-05-24 15:00:00,14933.24,NSW1NSW1 +47272,2015-05-24 16:00:00,15904.54,NSW1NSW1 +47273,2015-05-24 17:00:00,17947.739999999998,NSW1NSW1 +47274,2015-05-24 18:00:00,19691.07,NSW1NSW1 +47275,2015-05-24 19:00:00,19273.66,NSW1NSW1 +47276,2015-05-24 20:00:00,18557.17,NSW1NSW1 +47277,2015-05-24 21:00:00,17811.83,NSW1NSW1 +47278,2015-05-24 22:00:00,16864.760000000002,NSW1NSW1 +47279,2015-05-24 23:00:00,16091.17,NSW1NSW1 +47280,2015-05-25 00:00:00,15398.439999999999,NSW1NSW1 +47281,2015-05-25 01:00:00,14506.1,NSW1NSW1 +47282,2015-05-25 02:00:00,13724.279999999999,NSW1NSW1 +47283,2015-05-25 03:00:00,12967.130000000001,NSW1NSW1 +47284,2015-05-25 04:00:00,12805.98,NSW1NSW1 +47285,2015-05-25 05:00:00,13425.63,NSW1NSW1 +47286,2015-05-25 06:00:00,15497.03,NSW1NSW1 +47287,2015-05-25 07:00:00,18366.31,NSW1NSW1 +47288,2015-05-25 08:00:00,19537.85,NSW1NSW1 +47289,2015-05-25 09:00:00,19189.61,NSW1NSW1 +47290,2015-05-25 10:00:00,18703.550000000003,NSW1NSW1 +47291,2015-05-25 11:00:00,18133.01,NSW1NSW1 +47292,2015-05-25 12:00:00,17679.61,NSW1NSW1 +47293,2015-05-25 13:00:00,17447.489999999998,NSW1NSW1 +47294,2015-05-25 14:00:00,17323.760000000002,NSW1NSW1 +47295,2015-05-25 15:00:00,17198.07,NSW1NSW1 +47296,2015-05-25 16:00:00,17917.65,NSW1NSW1 +47297,2015-05-25 17:00:00,19905.96,NSW1NSW1 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00:00:00,17518.809999999998,NSW1NSW1 +47569,2015-06-06 01:00:00,16410.85,NSW1NSW1 +47570,2015-06-06 02:00:00,15266.76,NSW1NSW1 +47571,2015-06-06 03:00:00,13929.45,NSW1NSW1 +47572,2015-06-06 04:00:00,13306.17,NSW1NSW1 +47573,2015-06-06 05:00:00,13304.0,NSW1NSW1 +47574,2015-06-06 06:00:00,14094.04,NSW1NSW1 +47575,2015-06-06 07:00:00,15389.470000000001,NSW1NSW1 +47576,2015-06-06 08:00:00,17267.64,NSW1NSW1 +47577,2015-06-06 09:00:00,18039.71,NSW1NSW1 +47578,2015-06-06 10:00:00,17519.8,NSW1NSW1 +47579,2015-06-06 11:00:00,16578.74,NSW1NSW1 +47580,2015-06-06 12:00:00,15790.1,NSW1NSW1 +47581,2015-06-06 13:00:00,15178.09,NSW1NSW1 +47582,2015-06-06 14:00:00,15011.65,NSW1NSW1 +47583,2015-06-06 15:00:00,15049.71,NSW1NSW1 +47584,2015-06-06 16:00:00,15792.66,NSW1NSW1 +47585,2015-06-06 17:00:00,17594.86,NSW1NSW1 +47586,2015-06-06 18:00:00,19155.59,NSW1NSW1 +47587,2015-06-06 19:00:00,18649.03,NSW1NSW1 +47588,2015-06-06 20:00:00,17967.0,NSW1NSW1 +47589,2015-06-06 21:00:00,17523.760000000002,NSW1NSW1 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19:00:00,17925.879999999997,NSW1NSW1 +47612,2015-06-07 20:00:00,17286.010000000002,NSW1NSW1 +47613,2015-06-07 21:00:00,16825.28,NSW1NSW1 +47614,2015-06-07 22:00:00,16326.86,NSW1NSW1 +47615,2015-06-07 23:00:00,15695.48,NSW1NSW1 +47616,2015-06-08 00:00:00,14915.7,NSW1NSW1 +47617,2015-06-08 01:00:00,13998.77,NSW1NSW1 +47618,2015-06-08 02:00:00,13029.48,NSW1NSW1 +47619,2015-06-08 03:00:00,12259.98,NSW1NSW1 +47620,2015-06-08 04:00:00,11943.0,NSW1NSW1 +47621,2015-06-08 05:00:00,12123.77,NSW1NSW1 +47622,2015-06-08 06:00:00,12817.71,NSW1NSW1 +47623,2015-06-08 07:00:00,13660.46,NSW1NSW1 +47624,2015-06-08 08:00:00,14915.27,NSW1NSW1 +47625,2015-06-08 09:00:00,15656.71,NSW1NSW1 +47626,2015-06-08 10:00:00,15632.54,NSW1NSW1 +47627,2015-06-08 11:00:00,15048.92,NSW1NSW1 +47628,2015-06-08 12:00:00,14566.130000000001,NSW1NSW1 +47629,2015-06-08 13:00:00,14227.689999999999,NSW1NSW1 +47630,2015-06-08 14:00:00,14080.150000000001,NSW1NSW1 +47631,2015-06-08 15:00:00,14310.42,NSW1NSW1 +47632,2015-06-08 16:00:00,15004.310000000001,NSW1NSW1 +47633,2015-06-08 17:00:00,16904.32,NSW1NSW1 +47634,2015-06-08 18:00:00,18652.37,NSW1NSW1 +47635,2015-06-08 19:00:00,18042.809999999998,NSW1NSW1 +47636,2015-06-08 20:00:00,17345.440000000002,NSW1NSW1 +47637,2015-06-08 21:00:00,16674.739999999998,NSW1NSW1 +47638,2015-06-08 22:00:00,16028.4,NSW1NSW1 +47639,2015-06-08 23:00:00,15579.720000000001,NSW1NSW1 +47640,2015-06-09 00:00:00,15183.26,NSW1NSW1 +47641,2015-06-09 01:00:00,14649.48,NSW1NSW1 +47642,2015-06-09 02:00:00,13702.14,NSW1NSW1 +47643,2015-06-09 03:00:00,12677.880000000001,NSW1NSW1 +47644,2015-06-09 04:00:00,12335.67,NSW1NSW1 +47645,2015-06-09 05:00:00,12799.91,NSW1NSW1 +47646,2015-06-09 06:00:00,14788.52,NSW1NSW1 +47647,2015-06-09 07:00:00,17474.82,NSW1NSW1 +47648,2015-06-09 08:00:00,18229.010000000002,NSW1NSW1 +47649,2015-06-09 09:00:00,17525.5,NSW1NSW1 +47650,2015-06-09 10:00:00,17230.98,NSW1NSW1 +47651,2015-06-09 11:00:00,17193.309999999998,NSW1NSW1 +47652,2015-06-09 12:00:00,16799.86,NSW1NSW1 +47653,2015-06-09 13:00:00,16636.260000000002,NSW1NSW1 +47654,2015-06-09 14:00:00,16563.489999999998,NSW1NSW1 +47655,2015-06-09 15:00:00,16621.03,NSW1NSW1 +47656,2015-06-09 16:00:00,17118.59,NSW1NSW1 +47657,2015-06-09 17:00:00,18692.63,NSW1NSW1 +47658,2015-06-09 18:00:00,20418.28,NSW1NSW1 +47659,2015-06-09 19:00:00,19992.199999999997,NSW1NSW1 +47660,2015-06-09 20:00:00,19273.8,NSW1NSW1 +47661,2015-06-09 21:00:00,18347.66,NSW1NSW1 +47662,2015-06-09 22:00:00,17461.300000000003,NSW1NSW1 +47663,2015-06-09 23:00:00,16786.27,NSW1NSW1 +47664,2015-06-10 00:00:00,16384.94,NSW1NSW1 +47665,2015-06-10 01:00:00,15725.689999999999,NSW1NSW1 +47666,2015-06-10 02:00:00,14747.2,NSW1NSW1 +47667,2015-06-10 03:00:00,13633.5,NSW1NSW1 +47668,2015-06-10 04:00:00,13242.7,NSW1NSW1 +47669,2015-06-10 05:00:00,13860.11,NSW1NSW1 +47670,2015-06-10 06:00:00,15850.14,NSW1NSW1 +47671,2015-06-10 07:00:00,18615.04,NSW1NSW1 +47672,2015-06-10 08:00:00,19882.85,NSW1NSW1 +47673,2015-06-10 09:00:00,19553.71,NSW1NSW1 +47674,2015-06-10 10:00:00,19277.4,NSW1NSW1 +47675,2015-06-10 11:00:00,18880.75,NSW1NSW1 +47676,2015-06-10 12:00:00,18582.14,NSW1NSW1 +47677,2015-06-10 13:00:00,18386.89,NSW1NSW1 +47678,2015-06-10 14:00:00,18304.440000000002,NSW1NSW1 +47679,2015-06-10 15:00:00,18265.050000000003,NSW1NSW1 +47680,2015-06-10 16:00:00,19086.870000000003,NSW1NSW1 +47681,2015-06-10 17:00:00,20780.449999999997,NSW1NSW1 +47682,2015-06-10 18:00:00,22231.23,NSW1NSW1 +47683,2015-06-10 19:00:00,21645.14,NSW1NSW1 +47684,2015-06-10 20:00:00,20683.510000000002,NSW1NSW1 +47685,2015-06-10 21:00:00,19546.82,NSW1NSW1 +47686,2015-06-10 22:00:00,18445.32,NSW1NSW1 +47687,2015-06-10 23:00:00,17416.04,NSW1NSW1 +47688,2015-06-11 00:00:00,16813.93,NSW1NSW1 +47689,2015-06-11 01:00:00,15931.23,NSW1NSW1 +47690,2015-06-11 02:00:00,14893.13,NSW1NSW1 +47691,2015-06-11 03:00:00,13697.45,NSW1NSW1 +47692,2015-06-11 04:00:00,13268.48,NSW1NSW1 +47693,2015-06-11 05:00:00,13799.009999999998,NSW1NSW1 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00:00:00,16636.690000000002,NSW1NSW1 +47737,2015-06-13 01:00:00,15773.89,NSW1NSW1 +47738,2015-06-13 02:00:00,14598.39,NSW1NSW1 +47739,2015-06-13 03:00:00,13364.02,NSW1NSW1 +47740,2015-06-13 04:00:00,12803.63,NSW1NSW1 +47741,2015-06-13 05:00:00,12933.17,NSW1NSW1 +47742,2015-06-13 06:00:00,13647.49,NSW1NSW1 +47743,2015-06-13 07:00:00,14862.57,NSW1NSW1 +47744,2015-06-13 08:00:00,16553.08,NSW1NSW1 +47745,2015-06-13 09:00:00,17394.699999999997,NSW1NSW1 +47746,2015-06-13 10:00:00,16985.32,NSW1NSW1 +47747,2015-06-13 11:00:00,16187.7,NSW1NSW1 +47748,2015-06-13 12:00:00,15579.400000000001,NSW1NSW1 +47749,2015-06-13 13:00:00,15299.29,NSW1NSW1 +47750,2015-06-13 14:00:00,14987.64,NSW1NSW1 +47751,2015-06-13 15:00:00,15013.130000000001,NSW1NSW1 +47752,2015-06-13 16:00:00,15719.2,NSW1NSW1 +47753,2015-06-13 17:00:00,17598.73,NSW1NSW1 +47754,2015-06-13 18:00:00,18995.120000000003,NSW1NSW1 +47755,2015-06-13 19:00:00,18507.14,NSW1NSW1 +47756,2015-06-13 20:00:00,17788.39,NSW1NSW1 +47757,2015-06-13 21:00:00,17157.120000000003,NSW1NSW1 +47758,2015-06-13 22:00:00,16640.47,NSW1NSW1 +47759,2015-06-13 23:00:00,16315.400000000001,NSW1NSW1 +47760,2015-06-14 00:00:00,15694.759999999998,NSW1NSW1 +47761,2015-06-14 01:00:00,14574.45,NSW1NSW1 +47762,2015-06-14 02:00:00,13662.4,NSW1NSW1 +47763,2015-06-14 03:00:00,12815.44,NSW1NSW1 +47764,2015-06-14 04:00:00,12534.810000000001,NSW1NSW1 +47765,2015-06-14 05:00:00,12570.84,NSW1NSW1 +47766,2015-06-14 06:00:00,13142.970000000001,NSW1NSW1 +47767,2015-06-14 07:00:00,14281.84,NSW1NSW1 +47768,2015-06-14 08:00:00,15845.58,NSW1NSW1 +47769,2015-06-14 09:00:00,16738.22,NSW1NSW1 +47770,2015-06-14 10:00:00,16843.41,NSW1NSW1 +47771,2015-06-14 11:00:00,16228.82,NSW1NSW1 +47772,2015-06-14 12:00:00,15594.96,NSW1NSW1 +47773,2015-06-14 13:00:00,14995.67,NSW1NSW1 +47774,2015-06-14 14:00:00,14732.76,NSW1NSW1 +47775,2015-06-14 15:00:00,15022.77,NSW1NSW1 +47776,2015-06-14 16:00:00,15859.529999999999,NSW1NSW1 +47777,2015-06-14 17:00:00,17866.97,NSW1NSW1 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14:00:00,17878.760000000002,NSW1NSW1 +47799,2015-06-15 15:00:00,17865.08,NSW1NSW1 +47800,2015-06-15 16:00:00,18740.73,NSW1NSW1 +47801,2015-06-15 17:00:00,20457.1,NSW1NSW1 +47802,2015-06-15 18:00:00,21369.48,NSW1NSW1 +47803,2015-06-15 19:00:00,20584.63,NSW1NSW1 +47804,2015-06-15 20:00:00,19506.07,NSW1NSW1 +47805,2015-06-15 21:00:00,18617.489999999998,NSW1NSW1 +47806,2015-06-15 22:00:00,17583.59,NSW1NSW1 +47807,2015-06-15 23:00:00,16658.82,NSW1NSW1 +47808,2015-06-16 00:00:00,16175.38,NSW1NSW1 +47809,2015-06-16 01:00:00,15460.79,NSW1NSW1 +47810,2015-06-16 02:00:00,14514.84,NSW1NSW1 +47811,2015-06-16 03:00:00,13354.43,NSW1NSW1 +47812,2015-06-16 04:00:00,12864.529999999999,NSW1NSW1 +47813,2015-06-16 05:00:00,13239.46,NSW1NSW1 +47814,2015-06-16 06:00:00,15078.990000000002,NSW1NSW1 +47815,2015-06-16 07:00:00,17531.92,NSW1NSW1 +47816,2015-06-16 08:00:00,18625.37,NSW1NSW1 +47817,2015-06-16 09:00:00,18594.88,NSW1NSW1 +47818,2015-06-16 10:00:00,18676.07,NSW1NSW1 +47819,2015-06-16 11:00:00,18604.36,NSW1NSW1 +47820,2015-06-16 12:00:00,18658.21,NSW1NSW1 +47821,2015-06-16 13:00:00,18643.59,NSW1NSW1 +47822,2015-06-16 14:00:00,18549.25,NSW1NSW1 +47823,2015-06-16 15:00:00,18439.550000000003,NSW1NSW1 +47824,2015-06-16 16:00:00,18887.519999999997,NSW1NSW1 +47825,2015-06-16 17:00:00,20401.980000000003,NSW1NSW1 +47826,2015-06-16 18:00:00,21323.28,NSW1NSW1 +47827,2015-06-16 19:00:00,20535.46,NSW1NSW1 +47828,2015-06-16 20:00:00,19490.760000000002,NSW1NSW1 +47829,2015-06-16 21:00:00,18511.559999999998,NSW1NSW1 +47830,2015-06-16 22:00:00,17600.190000000002,NSW1NSW1 +47831,2015-06-16 23:00:00,16832.69,NSW1NSW1 +47832,2015-06-17 00:00:00,16341.66,NSW1NSW1 +47833,2015-06-17 01:00:00,15475.369999999999,NSW1NSW1 +47834,2015-06-17 02:00:00,14470.64,NSW1NSW1 +47835,2015-06-17 03:00:00,13265.279999999999,NSW1NSW1 +47836,2015-06-17 04:00:00,12784.009999999998,NSW1NSW1 +47837,2015-06-17 05:00:00,13338.7,NSW1NSW1 +47838,2015-06-17 06:00:00,15050.84,NSW1NSW1 +47839,2015-06-17 07:00:00,17569.53,NSW1NSW1 +47840,2015-06-17 08:00:00,18848.269999999997,NSW1NSW1 +47841,2015-06-17 09:00:00,18866.32,NSW1NSW1 +47842,2015-06-17 10:00:00,19010.14,NSW1NSW1 +47843,2015-06-17 11:00:00,18691.82,NSW1NSW1 +47844,2015-06-17 12:00:00,18498.46,NSW1NSW1 +47845,2015-06-17 13:00:00,18478.02,NSW1NSW1 +47846,2015-06-17 14:00:00,18351.78,NSW1NSW1 +47847,2015-06-17 15:00:00,18234.449999999997,NSW1NSW1 +47848,2015-06-17 16:00:00,18795.54,NSW1NSW1 +47849,2015-06-17 17:00:00,20070.21,NSW1NSW1 +47850,2015-06-17 18:00:00,20996.03,NSW1NSW1 +47851,2015-06-17 19:00:00,20432.260000000002,NSW1NSW1 +47852,2015-06-17 20:00:00,19558.769999999997,NSW1NSW1 +47853,2015-06-17 21:00:00,18777.81,NSW1NSW1 +47854,2015-06-17 22:00:00,17910.54,NSW1NSW1 +47855,2015-06-17 23:00:00,17200.29,NSW1NSW1 +47856,2015-06-18 00:00:00,16456.6,NSW1NSW1 +47857,2015-06-18 01:00:00,15663.099999999999,NSW1NSW1 +47858,2015-06-18 02:00:00,14627.84,NSW1NSW1 +47859,2015-06-18 03:00:00,13510.65,NSW1NSW1 +47860,2015-06-18 04:00:00,13139.65,NSW1NSW1 +47861,2015-06-18 05:00:00,13744.95,NSW1NSW1 +47862,2015-06-18 06:00:00,15608.21,NSW1NSW1 +47863,2015-06-18 07:00:00,18233.77,NSW1NSW1 +47864,2015-06-18 08:00:00,19474.31,NSW1NSW1 +47865,2015-06-18 09:00:00,18975.300000000003,NSW1NSW1 +47866,2015-06-18 10:00:00,18615.14,NSW1NSW1 +47867,2015-06-18 11:00:00,18251.58,NSW1NSW1 +47868,2015-06-18 12:00:00,17862.84,NSW1NSW1 +47869,2015-06-18 13:00:00,17785.33,NSW1NSW1 +47870,2015-06-18 14:00:00,17773.769999999997,NSW1NSW1 +47871,2015-06-18 15:00:00,17825.660000000003,NSW1NSW1 +47872,2015-06-18 16:00:00,18760.16,NSW1NSW1 +47873,2015-06-18 17:00:00,20520.95,NSW1NSW1 +47874,2015-06-18 18:00:00,21640.98,NSW1NSW1 +47875,2015-06-18 19:00:00,21215.95,NSW1NSW1 +47876,2015-06-18 20:00:00,20435.5,NSW1NSW1 +47877,2015-06-18 21:00:00,19581.39,NSW1NSW1 +47878,2015-06-18 22:00:00,18582.93,NSW1NSW1 +47879,2015-06-18 23:00:00,17722.87,NSW1NSW1 +47880,2015-06-19 00:00:00,17044.0,NSW1NSW1 +47881,2015-06-19 01:00:00,16198.57,NSW1NSW1 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22:00:00,19180.71,NSW1NSW1 +47903,2015-06-19 23:00:00,18315.370000000003,NSW1NSW1 +47904,2015-06-20 00:00:00,17531.67,NSW1NSW1 +47905,2015-06-20 01:00:00,16467.82,NSW1NSW1 +47906,2015-06-20 02:00:00,15225.279999999999,NSW1NSW1 +47907,2015-06-20 03:00:00,14009.35,NSW1NSW1 +47908,2015-06-20 04:00:00,13411.91,NSW1NSW1 +47909,2015-06-20 05:00:00,13575.03,NSW1NSW1 +47910,2015-06-20 06:00:00,14320.11,NSW1NSW1 +47911,2015-06-20 07:00:00,15749.02,NSW1NSW1 +47912,2015-06-20 08:00:00,17759.510000000002,NSW1NSW1 +47913,2015-06-20 09:00:00,18685.43,NSW1NSW1 +47914,2015-06-20 10:00:00,18460.09,NSW1NSW1 +47915,2015-06-20 11:00:00,17602.37,NSW1NSW1 +47916,2015-06-20 12:00:00,16655.03,NSW1NSW1 +47917,2015-06-20 13:00:00,15929.18,NSW1NSW1 +47918,2015-06-20 14:00:00,15748.08,NSW1NSW1 +47919,2015-06-20 15:00:00,15937.58,NSW1NSW1 +47920,2015-06-20 16:00:00,17009.48,NSW1NSW1 +47921,2015-06-20 17:00:00,19200.35,NSW1NSW1 +47922,2015-06-20 18:00:00,20917.67,NSW1NSW1 +47923,2015-06-20 19:00:00,20344.03,NSW1NSW1 +47924,2015-06-20 20:00:00,19585.58,NSW1NSW1 +47925,2015-06-20 21:00:00,18969.690000000002,NSW1NSW1 +47926,2015-06-20 22:00:00,18282.05,NSW1NSW1 +47927,2015-06-20 23:00:00,17530.34,NSW1NSW1 +47928,2015-06-21 00:00:00,16657.84,NSW1NSW1 +47929,2015-06-21 01:00:00,15457.26,NSW1NSW1 +47930,2015-06-21 02:00:00,14460.529999999999,NSW1NSW1 +47931,2015-06-21 03:00:00,13419.57,NSW1NSW1 +47932,2015-06-21 04:00:00,12954.98,NSW1NSW1 +47933,2015-06-21 05:00:00,13130.01,NSW1NSW1 +47934,2015-06-21 06:00:00,13693.05,NSW1NSW1 +47935,2015-06-21 07:00:00,14843.59,NSW1NSW1 +47936,2015-06-21 08:00:00,16691.940000000002,NSW1NSW1 +47937,2015-06-21 09:00:00,17861.54,NSW1NSW1 +47938,2015-06-21 10:00:00,17859.75,NSW1NSW1 +47939,2015-06-21 11:00:00,17280.949999999997,NSW1NSW1 +47940,2015-06-21 12:00:00,16856.190000000002,NSW1NSW1 +47941,2015-06-21 13:00:00,16546.739999999998,NSW1NSW1 +47942,2015-06-21 14:00:00,16361.52,NSW1NSW1 +47943,2015-06-21 15:00:00,16557.440000000002,NSW1NSW1 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13:00:00,17134.97,NSW1NSW1 +47966,2015-06-22 14:00:00,17204.89,NSW1NSW1 +47967,2015-06-22 15:00:00,17414.52,NSW1NSW1 +47968,2015-06-22 16:00:00,18199.66,NSW1NSW1 +47969,2015-06-22 17:00:00,20519.16,NSW1NSW1 +47970,2015-06-22 18:00:00,22548.56,NSW1NSW1 +47971,2015-06-22 19:00:00,22034.82,NSW1NSW1 +47972,2015-06-22 20:00:00,21079.79,NSW1NSW1 +47973,2015-06-22 21:00:00,20054.28,NSW1NSW1 +47974,2015-06-22 22:00:00,18759.41,NSW1NSW1 +47975,2015-06-22 23:00:00,17585.050000000003,NSW1NSW1 +47976,2015-06-23 00:00:00,16904.55,NSW1NSW1 +47977,2015-06-23 01:00:00,16085.48,NSW1NSW1 +47978,2015-06-23 02:00:00,15100.91,NSW1NSW1 +47979,2015-06-23 03:00:00,13851.83,NSW1NSW1 +47980,2015-06-23 04:00:00,13501.939999999999,NSW1NSW1 +47981,2015-06-23 05:00:00,14073.34,NSW1NSW1 +47982,2015-06-23 06:00:00,16163.06,NSW1NSW1 +47983,2015-06-23 07:00:00,19208.58,NSW1NSW1 +47984,2015-06-23 08:00:00,20566.03,NSW1NSW1 +47985,2015-06-23 09:00:00,19786.910000000003,NSW1NSW1 +47986,2015-06-23 10:00:00,18843.33,NSW1NSW1 +47987,2015-06-23 11:00:00,18101.07,NSW1NSW1 +47988,2015-06-23 12:00:00,17428.72,NSW1NSW1 +47989,2015-06-23 13:00:00,17051.739999999998,NSW1NSW1 +47990,2015-06-23 14:00:00,16939.449999999997,NSW1NSW1 +47991,2015-06-23 15:00:00,16956.64,NSW1NSW1 +47992,2015-06-23 16:00:00,17821.32,NSW1NSW1 +47993,2015-06-23 17:00:00,19794.48,NSW1NSW1 +47994,2015-06-23 18:00:00,21676.5,NSW1NSW1 +47995,2015-06-23 19:00:00,21256.85,NSW1NSW1 +47996,2015-06-23 20:00:00,20398.48,NSW1NSW1 +47997,2015-06-23 21:00:00,19334.85,NSW1NSW1 +47998,2015-06-23 22:00:00,18189.5,NSW1NSW1 +47999,2015-06-23 23:00:00,17203.1,NSW1NSW1 +48000,2015-06-24 00:00:00,16557.25,NSW1NSW1 +48001,2015-06-24 01:00:00,15780.029999999999,NSW1NSW1 +48002,2015-06-24 02:00:00,14713.189999999999,NSW1NSW1 +48003,2015-06-24 03:00:00,13438.47,NSW1NSW1 +48004,2015-06-24 04:00:00,12994.02,NSW1NSW1 +48005,2015-06-24 05:00:00,13603.029999999999,NSW1NSW1 +48006,2015-06-24 06:00:00,15604.24,NSW1NSW1 +48007,2015-06-24 07:00:00,18271.440000000002,NSW1NSW1 +48008,2015-06-24 08:00:00,19486.739999999998,NSW1NSW1 +48009,2015-06-24 09:00:00,18875.07,NSW1NSW1 +48010,2015-06-24 10:00:00,18457.9,NSW1NSW1 +48011,2015-06-24 11:00:00,17800.35,NSW1NSW1 +48012,2015-06-24 12:00:00,17426.31,NSW1NSW1 +48013,2015-06-24 13:00:00,17145.04,NSW1NSW1 +48014,2015-06-24 14:00:00,16935.43,NSW1NSW1 +48015,2015-06-24 15:00:00,17033.6,NSW1NSW1 +48016,2015-06-24 16:00:00,17722.309999999998,NSW1NSW1 +48017,2015-06-24 17:00:00,19419.79,NSW1NSW1 +48018,2015-06-24 18:00:00,20873.510000000002,NSW1NSW1 +48019,2015-06-24 19:00:00,20321.559999999998,NSW1NSW1 +48020,2015-06-24 20:00:00,19382.129999999997,NSW1NSW1 +48021,2015-06-24 21:00:00,18499.370000000003,NSW1NSW1 +48022,2015-06-24 22:00:00,17562.550000000003,NSW1NSW1 +48023,2015-06-24 23:00:00,16873.33,NSW1NSW1 +48024,2015-06-25 00:00:00,16376.57,NSW1NSW1 +48025,2015-06-25 01:00:00,15686.57,NSW1NSW1 +48026,2015-06-25 02:00:00,14647.46,NSW1NSW1 +48027,2015-06-25 03:00:00,13533.28,NSW1NSW1 +48028,2015-06-25 04:00:00,13195.279999999999,NSW1NSW1 +48029,2015-06-25 05:00:00,13750.3,NSW1NSW1 +48030,2015-06-25 06:00:00,15583.52,NSW1NSW1 +48031,2015-06-25 07:00:00,17901.07,NSW1NSW1 +48032,2015-06-25 08:00:00,19007.059999999998,NSW1NSW1 +48033,2015-06-25 09:00:00,18651.059999999998,NSW1NSW1 +48034,2015-06-25 10:00:00,18183.75,NSW1NSW1 +48035,2015-06-25 11:00:00,17714.78,NSW1NSW1 +48036,2015-06-25 12:00:00,17130.0,NSW1NSW1 +48037,2015-06-25 13:00:00,17160.5,NSW1NSW1 +48038,2015-06-25 14:00:00,17303.1,NSW1NSW1 +48039,2015-06-25 15:00:00,17497.08,NSW1NSW1 +48040,2015-06-25 16:00:00,18417.82,NSW1NSW1 +48041,2015-06-25 17:00:00,19827.23,NSW1NSW1 +48042,2015-06-25 18:00:00,21006.04,NSW1NSW1 +48043,2015-06-25 19:00:00,20513.8,NSW1NSW1 +48044,2015-06-25 20:00:00,19737.13,NSW1NSW1 +48045,2015-06-25 21:00:00,18891.989999999998,NSW1NSW1 +48046,2015-06-25 22:00:00,18060.230000000003,NSW1NSW1 +48047,2015-06-25 23:00:00,17240.11,NSW1NSW1 +48048,2015-06-26 00:00:00,16672.06,NSW1NSW1 +48049,2015-06-26 01:00:00,15840.759999999998,NSW1NSW1 +48050,2015-06-26 02:00:00,14881.71,NSW1NSW1 +48051,2015-06-26 03:00:00,13716.95,NSW1NSW1 +48052,2015-06-26 04:00:00,13236.46,NSW1NSW1 +48053,2015-06-26 05:00:00,13774.900000000001,NSW1NSW1 +48054,2015-06-26 06:00:00,15770.77,NSW1NSW1 +48055,2015-06-26 07:00:00,18332.22,NSW1NSW1 +48056,2015-06-26 08:00:00,19511.61,NSW1NSW1 +48057,2015-06-26 09:00:00,19002.11,NSW1NSW1 +48058,2015-06-26 10:00:00,18407.62,NSW1NSW1 +48059,2015-06-26 11:00:00,17846.980000000003,NSW1NSW1 +48060,2015-06-26 12:00:00,17242.699999999997,NSW1NSW1 +48061,2015-06-26 13:00:00,16920.699999999997,NSW1NSW1 +48062,2015-06-26 14:00:00,16782.77,NSW1NSW1 +48063,2015-06-26 15:00:00,16692.27,NSW1NSW1 +48064,2015-06-26 16:00:00,17255.08,NSW1NSW1 +48065,2015-06-26 17:00:00,19012.9,NSW1NSW1 +48066,2015-06-26 18:00:00,20556.18,NSW1NSW1 +48067,2015-06-26 19:00:00,20082.199999999997,NSW1NSW1 +48068,2015-06-26 20:00:00,19481.65,NSW1NSW1 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15:00:00,15464.82,NSW1NSW1 +48112,2015-06-28 16:00:00,16352.05,NSW1NSW1 +48113,2015-06-28 17:00:00,18364.629999999997,NSW1NSW1 +48114,2015-06-28 18:00:00,20466.84,NSW1NSW1 +48115,2015-06-28 19:00:00,20209.09,NSW1NSW1 +48116,2015-06-28 20:00:00,19533.91,NSW1NSW1 +48117,2015-06-28 21:00:00,18758.03,NSW1NSW1 +48118,2015-06-28 22:00:00,17660.949999999997,NSW1NSW1 +48119,2015-06-28 23:00:00,16721.16,NSW1NSW1 +48120,2015-06-29 00:00:00,15851.369999999999,NSW1NSW1 +48121,2015-06-29 01:00:00,14948.119999999999,NSW1NSW1 +48122,2015-06-29 02:00:00,14099.279999999999,NSW1NSW1 +48123,2015-06-29 03:00:00,13304.43,NSW1NSW1 +48124,2015-06-29 04:00:00,13159.869999999999,NSW1NSW1 +48125,2015-06-29 05:00:00,13899.98,NSW1NSW1 +48126,2015-06-29 06:00:00,15796.16,NSW1NSW1 +48127,2015-06-29 07:00:00,18231.809999999998,NSW1NSW1 +48128,2015-06-29 08:00:00,19811.95,NSW1NSW1 +48129,2015-06-29 09:00:00,19991.5,NSW1NSW1 +48130,2015-06-29 10:00:00,19389.300000000003,NSW1NSW1 +48131,2015-06-29 11:00:00,18566.12,NSW1NSW1 +48132,2015-06-29 12:00:00,17767.15,NSW1NSW1 +48133,2015-06-29 13:00:00,17333.449999999997,NSW1NSW1 +48134,2015-06-29 14:00:00,17239.12,NSW1NSW1 +48135,2015-06-29 15:00:00,17265.11,NSW1NSW1 +48136,2015-06-29 16:00:00,17920.739999999998,NSW1NSW1 +48137,2015-06-29 17:00:00,19957.980000000003,NSW1NSW1 +48138,2015-06-29 18:00:00,21815.440000000002,NSW1NSW1 +48139,2015-06-29 19:00:00,21497.42,NSW1NSW1 +48140,2015-06-29 20:00:00,20578.879999999997,NSW1NSW1 +48141,2015-06-29 21:00:00,19889.9,NSW1NSW1 +48142,2015-06-29 22:00:00,18747.269999999997,NSW1NSW1 +48143,2015-06-29 23:00:00,17902.17,NSW1NSW1 +48144,2015-06-30 00:00:00,17147.03,NSW1NSW1 +48145,2015-06-30 01:00:00,16333.14,NSW1NSW1 +48146,2015-06-30 02:00:00,15309.42,NSW1NSW1 +48147,2015-06-30 03:00:00,14240.1,NSW1NSW1 +48148,2015-06-30 04:00:00,13735.630000000001,NSW1NSW1 +48149,2015-06-30 05:00:00,14298.95,NSW1NSW1 +48150,2015-06-30 06:00:00,16124.21,NSW1NSW1 +48151,2015-06-30 07:00:00,18508.96,NSW1NSW1 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02:00:00,15208.66,NSW1NSW1 +48195,2015-07-02 03:00:00,14082.55,NSW1NSW1 +48196,2015-07-02 04:00:00,13651.93,NSW1NSW1 +48197,2015-07-02 05:00:00,14129.119999999999,NSW1NSW1 +48198,2015-07-02 06:00:00,15879.19,NSW1NSW1 +48199,2015-07-02 07:00:00,18424.510000000002,NSW1NSW1 +48200,2015-07-02 08:00:00,20244.54,NSW1NSW1 +48201,2015-07-02 09:00:00,20459.09,NSW1NSW1 +48202,2015-07-02 10:00:00,19743.34,NSW1NSW1 +48203,2015-07-02 11:00:00,18887.12,NSW1NSW1 +48204,2015-07-02 12:00:00,18262.57,NSW1NSW1 +48205,2015-07-02 13:00:00,17897.7,NSW1NSW1 +48206,2015-07-02 14:00:00,17532.73,NSW1NSW1 +48207,2015-07-02 15:00:00,17646.199999999997,NSW1NSW1 +48208,2015-07-02 16:00:00,18574.0,NSW1NSW1 +48209,2015-07-02 17:00:00,20867.58,NSW1NSW1 +48210,2015-07-02 18:00:00,22886.65,NSW1NSW1 +48211,2015-07-02 19:00:00,22623.73,NSW1NSW1 +48212,2015-07-02 20:00:00,21704.72,NSW1NSW1 +48213,2015-07-02 21:00:00,20925.72,NSW1NSW1 +48214,2015-07-02 22:00:00,19759.11,NSW1NSW1 +48215,2015-07-02 23:00:00,18717.410000000003,NSW1NSW1 +48216,2015-07-03 00:00:00,17836.33,NSW1NSW1 +48217,2015-07-03 01:00:00,16921.54,NSW1NSW1 +48218,2015-07-03 02:00:00,15901.529999999999,NSW1NSW1 +48219,2015-07-03 03:00:00,14744.18,NSW1NSW1 +48220,2015-07-03 04:00:00,14259.52,NSW1NSW1 +48221,2015-07-03 05:00:00,14903.04,NSW1NSW1 +48222,2015-07-03 06:00:00,16879.12,NSW1NSW1 +48223,2015-07-03 07:00:00,19365.800000000003,NSW1NSW1 +48224,2015-07-03 08:00:00,20965.61,NSW1NSW1 +48225,2015-07-03 09:00:00,21115.21,NSW1NSW1 +48226,2015-07-03 10:00:00,20365.010000000002,NSW1NSW1 +48227,2015-07-03 11:00:00,19330.379999999997,NSW1NSW1 +48228,2015-07-03 12:00:00,18377.870000000003,NSW1NSW1 +48229,2015-07-03 13:00:00,17791.260000000002,NSW1NSW1 +48230,2015-07-03 14:00:00,17580.16,NSW1NSW1 +48231,2015-07-03 15:00:00,17660.46,NSW1NSW1 +48232,2015-07-03 16:00:00,18479.6,NSW1NSW1 +48233,2015-07-03 17:00:00,20614.98,NSW1NSW1 +48234,2015-07-03 18:00:00,22486.059999999998,NSW1NSW1 +48235,2015-07-03 19:00:00,22119.3,NSW1NSW1 +48236,2015-07-03 20:00:00,21423.190000000002,NSW1NSW1 +48237,2015-07-03 21:00:00,20684.0,NSW1NSW1 +48238,2015-07-03 22:00:00,19815.41,NSW1NSW1 +48239,2015-07-03 23:00:00,19001.52,NSW1NSW1 +48240,2015-07-04 00:00:00,18340.79,NSW1NSW1 +48241,2015-07-04 01:00:00,17240.29,NSW1NSW1 +48242,2015-07-04 02:00:00,15854.09,NSW1NSW1 +48243,2015-07-04 03:00:00,14513.75,NSW1NSW1 +48244,2015-07-04 04:00:00,13826.82,NSW1NSW1 +48245,2015-07-04 05:00:00,13960.900000000001,NSW1NSW1 +48246,2015-07-04 06:00:00,14708.720000000001,NSW1NSW1 +48247,2015-07-04 07:00:00,16101.84,NSW1NSW1 +48248,2015-07-04 08:00:00,18379.04,NSW1NSW1 +48249,2015-07-04 09:00:00,19902.059999999998,NSW1NSW1 +48250,2015-07-04 10:00:00,19579.559999999998,NSW1NSW1 +48251,2015-07-04 11:00:00,18463.34,NSW1NSW1 +48252,2015-07-04 12:00:00,17236.690000000002,NSW1NSW1 +48253,2015-07-04 13:00:00,16403.07,NSW1NSW1 +48254,2015-07-04 14:00:00,15954.97,NSW1NSW1 +48255,2015-07-04 15:00:00,16078.93,NSW1NSW1 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12:00:00,16265.759999999998,NSW1NSW1 +48277,2015-07-05 13:00:00,15645.66,NSW1NSW1 +48278,2015-07-05 14:00:00,15369.65,NSW1NSW1 +48279,2015-07-05 15:00:00,15646.599999999999,NSW1NSW1 +48280,2015-07-05 16:00:00,16787.75,NSW1NSW1 +48281,2015-07-05 17:00:00,19120.69,NSW1NSW1 +48282,2015-07-05 18:00:00,21338.97,NSW1NSW1 +48283,2015-07-05 19:00:00,21171.07,NSW1NSW1 +48284,2015-07-05 20:00:00,20404.56,NSW1NSW1 +48285,2015-07-05 21:00:00,19650.37,NSW1NSW1 +48286,2015-07-05 22:00:00,18609.02,NSW1NSW1 +48287,2015-07-05 23:00:00,17376.68,NSW1NSW1 +48288,2015-07-06 00:00:00,16352.619999999999,NSW1NSW1 +48289,2015-07-06 01:00:00,15350.33,NSW1NSW1 +48290,2015-07-06 02:00:00,14458.34,NSW1NSW1 +48291,2015-07-06 03:00:00,13626.73,NSW1NSW1 +48292,2015-07-06 04:00:00,13361.06,NSW1NSW1 +48293,2015-07-06 05:00:00,14074.85,NSW1NSW1 +48294,2015-07-06 06:00:00,16147.57,NSW1NSW1 +48295,2015-07-06 07:00:00,18921.05,NSW1NSW1 +48296,2015-07-06 08:00:00,20738.78,NSW1NSW1 +48297,2015-07-06 09:00:00,20903.25,NSW1NSW1 +48298,2015-07-06 10:00:00,20245.77,NSW1NSW1 +48299,2015-07-06 11:00:00,19225.690000000002,NSW1NSW1 +48300,2015-07-06 12:00:00,18403.050000000003,NSW1NSW1 +48301,2015-07-06 13:00:00,17990.589999999997,NSW1NSW1 +48302,2015-07-06 14:00:00,17733.15,NSW1NSW1 +48303,2015-07-06 15:00:00,17873.33,NSW1NSW1 +48304,2015-07-06 16:00:00,18722.44,NSW1NSW1 +48305,2015-07-06 17:00:00,21055.96,NSW1NSW1 +48306,2015-07-06 18:00:00,23296.76,NSW1NSW1 +48307,2015-07-06 19:00:00,22950.83,NSW1NSW1 +48308,2015-07-06 20:00:00,22006.66,NSW1NSW1 +48309,2015-07-06 21:00:00,21269.04,NSW1NSW1 +48310,2015-07-06 22:00:00,19975.35,NSW1NSW1 +48311,2015-07-06 23:00:00,18694.21,NSW1NSW1 +48312,2015-07-07 00:00:00,17872.11,NSW1NSW1 +48313,2015-07-07 01:00:00,16917.47,NSW1NSW1 +48314,2015-07-07 02:00:00,15882.16,NSW1NSW1 +48315,2015-07-07 03:00:00,14632.54,NSW1NSW1 +48316,2015-07-07 04:00:00,14221.1,NSW1NSW1 +48317,2015-07-07 05:00:00,14813.02,NSW1NSW1 +48318,2015-07-07 06:00:00,16856.21,NSW1NSW1 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04:00:00,14203.73,NSW1NSW1 +48341,2015-07-08 05:00:00,14691.849999999999,NSW1NSW1 +48342,2015-07-08 06:00:00,16642.99,NSW1NSW1 +48343,2015-07-08 07:00:00,19241.65,NSW1NSW1 +48344,2015-07-08 08:00:00,20806.19,NSW1NSW1 +48345,2015-07-08 09:00:00,20706.39,NSW1NSW1 +48346,2015-07-08 10:00:00,19839.83,NSW1NSW1 +48347,2015-07-08 11:00:00,18963.42,NSW1NSW1 +48348,2015-07-08 12:00:00,18325.440000000002,NSW1NSW1 +48349,2015-07-08 13:00:00,18068.85,NSW1NSW1 +48350,2015-07-08 14:00:00,17995.96,NSW1NSW1 +48351,2015-07-08 15:00:00,18223.47,NSW1NSW1 +48352,2015-07-08 16:00:00,18901.489999999998,NSW1NSW1 +48353,2015-07-08 17:00:00,20862.78,NSW1NSW1 +48354,2015-07-08 18:00:00,22973.77,NSW1NSW1 +48355,2015-07-08 19:00:00,22687.09,NSW1NSW1 +48356,2015-07-08 20:00:00,21816.25,NSW1NSW1 +48357,2015-07-08 21:00:00,20979.85,NSW1NSW1 +48358,2015-07-08 22:00:00,20052.41,NSW1NSW1 +48359,2015-07-08 23:00:00,18903.739999999998,NSW1NSW1 +48360,2015-07-09 00:00:00,18013.059999999998,NSW1NSW1 +48361,2015-07-09 01:00:00,16982.09,NSW1NSW1 +48362,2015-07-09 02:00:00,15920.3,NSW1NSW1 +48363,2015-07-09 03:00:00,14738.18,NSW1NSW1 +48364,2015-07-09 04:00:00,14198.16,NSW1NSW1 +48365,2015-07-09 05:00:00,14734.0,NSW1NSW1 +48366,2015-07-09 06:00:00,16644.23,NSW1NSW1 +48367,2015-07-09 07:00:00,19160.239999999998,NSW1NSW1 +48368,2015-07-09 08:00:00,20835.489999999998,NSW1NSW1 +48369,2015-07-09 09:00:00,20756.57,NSW1NSW1 +48370,2015-07-09 10:00:00,19829.77,NSW1NSW1 +48371,2015-07-09 11:00:00,18807.190000000002,NSW1NSW1 +48372,2015-07-09 12:00:00,18018.38,NSW1NSW1 +48373,2015-07-09 13:00:00,17471.809999999998,NSW1NSW1 +48374,2015-07-09 14:00:00,17258.18,NSW1NSW1 +48375,2015-07-09 15:00:00,17390.61,NSW1NSW1 +48376,2015-07-09 16:00:00,18153.379999999997,NSW1NSW1 +48377,2015-07-09 17:00:00,20156.190000000002,NSW1NSW1 +48378,2015-07-09 18:00:00,22422.239999999998,NSW1NSW1 +48379,2015-07-09 19:00:00,22270.45,NSW1NSW1 +48380,2015-07-09 20:00:00,21529.69,NSW1NSW1 +48381,2015-07-09 21:00:00,20782.85,NSW1NSW1 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19:00:00,21845.17,NSW1NSW1 +48404,2015-07-10 20:00:00,21071.010000000002,NSW1NSW1 +48405,2015-07-10 21:00:00,20135.9,NSW1NSW1 +48406,2015-07-10 22:00:00,19184.019999999997,NSW1NSW1 +48407,2015-07-10 23:00:00,18438.57,NSW1NSW1 +48408,2015-07-11 00:00:00,17697.04,NSW1NSW1 +48409,2015-07-11 01:00:00,16526.489999999998,NSW1NSW1 +48410,2015-07-11 02:00:00,15255.55,NSW1NSW1 +48411,2015-07-11 03:00:00,13960.74,NSW1NSW1 +48412,2015-07-11 04:00:00,13341.52,NSW1NSW1 +48413,2015-07-11 05:00:00,13428.89,NSW1NSW1 +48414,2015-07-11 06:00:00,14257.779999999999,NSW1NSW1 +48415,2015-07-11 07:00:00,15615.02,NSW1NSW1 +48416,2015-07-11 08:00:00,17663.260000000002,NSW1NSW1 +48417,2015-07-11 09:00:00,18722.25,NSW1NSW1 +48418,2015-07-11 10:00:00,18393.33,NSW1NSW1 +48419,2015-07-11 11:00:00,17415.56,NSW1NSW1 +48420,2015-07-11 12:00:00,16494.75,NSW1NSW1 +48421,2015-07-11 13:00:00,15976.56,NSW1NSW1 +48422,2015-07-11 14:00:00,15512.8,NSW1NSW1 +48423,2015-07-11 15:00:00,15753.54,NSW1NSW1 +48424,2015-07-11 16:00:00,16602.760000000002,NSW1NSW1 +48425,2015-07-11 17:00:00,18595.809999999998,NSW1NSW1 +48426,2015-07-11 18:00:00,20231.83,NSW1NSW1 +48427,2015-07-11 19:00:00,19752.6,NSW1NSW1 +48428,2015-07-11 20:00:00,18875.370000000003,NSW1NSW1 +48429,2015-07-11 21:00:00,18390.42,NSW1NSW1 +48430,2015-07-11 22:00:00,18024.53,NSW1NSW1 +48431,2015-07-11 23:00:00,17408.71,NSW1NSW1 +48432,2015-07-12 00:00:00,16548.88,NSW1NSW1 +48433,2015-07-12 01:00:00,15345.81,NSW1NSW1 +48434,2015-07-12 02:00:00,14283.400000000001,NSW1NSW1 +48435,2015-07-12 03:00:00,13285.2,NSW1NSW1 +48436,2015-07-12 04:00:00,12780.349999999999,NSW1NSW1 +48437,2015-07-12 05:00:00,12818.61,NSW1NSW1 +48438,2015-07-12 06:00:00,13382.05,NSW1NSW1 +48439,2015-07-12 07:00:00,14590.07,NSW1NSW1 +48440,2015-07-12 08:00:00,16579.34,NSW1NSW1 +48441,2015-07-12 09:00:00,18258.9,NSW1NSW1 +48442,2015-07-12 10:00:00,18832.18,NSW1NSW1 +48443,2015-07-12 11:00:00,18346.809999999998,NSW1NSW1 +48444,2015-07-12 12:00:00,17798.96,NSW1NSW1 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09:00:00,21665.25,NSW1NSW1 +48466,2015-07-13 10:00:00,21615.79,NSW1NSW1 +48467,2015-07-13 11:00:00,20749.870000000003,NSW1NSW1 +48468,2015-07-13 12:00:00,19661.1,NSW1NSW1 +48469,2015-07-13 13:00:00,18904.38,NSW1NSW1 +48470,2015-07-13 14:00:00,18430.93,NSW1NSW1 +48471,2015-07-13 15:00:00,18305.62,NSW1NSW1 +48472,2015-07-13 16:00:00,18951.52,NSW1NSW1 +48473,2015-07-13 17:00:00,21058.47,NSW1NSW1 +48474,2015-07-13 18:00:00,23469.65,NSW1NSW1 +48475,2015-07-13 19:00:00,23144.28,NSW1NSW1 +48476,2015-07-13 20:00:00,21955.59,NSW1NSW1 +48477,2015-07-13 21:00:00,20861.83,NSW1NSW1 +48478,2015-07-13 22:00:00,19300.379999999997,NSW1NSW1 +48479,2015-07-13 23:00:00,18112.61,NSW1NSW1 +48480,2015-07-14 00:00:00,17357.75,NSW1NSW1 +48481,2015-07-14 01:00:00,16503.92,NSW1NSW1 +48482,2015-07-14 02:00:00,15505.380000000001,NSW1NSW1 +48483,2015-07-14 03:00:00,14310.03,NSW1NSW1 +48484,2015-07-14 04:00:00,13697.36,NSW1NSW1 +48485,2015-07-14 05:00:00,14195.880000000001,NSW1NSW1 +48486,2015-07-14 06:00:00,16193.920000000002,NSW1NSW1 +48487,2015-07-14 07:00:00,19273.059999999998,NSW1NSW1 +48488,2015-07-14 08:00:00,20512.07,NSW1NSW1 +48489,2015-07-14 09:00:00,19626.57,NSW1NSW1 +48490,2015-07-14 10:00:00,18885.690000000002,NSW1NSW1 +48491,2015-07-14 11:00:00,18259.48,NSW1NSW1 +48492,2015-07-14 12:00:00,17566.06,NSW1NSW1 +48493,2015-07-14 13:00:00,17188.019999999997,NSW1NSW1 +48494,2015-07-14 14:00:00,17137.95,NSW1NSW1 +48495,2015-07-14 15:00:00,17335.54,NSW1NSW1 +48496,2015-07-14 16:00:00,18317.9,NSW1NSW1 +48497,2015-07-14 17:00:00,20481.11,NSW1NSW1 +48498,2015-07-14 18:00:00,22880.58,NSW1NSW1 +48499,2015-07-14 19:00:00,22845.809999999998,NSW1NSW1 +48500,2015-07-14 20:00:00,21888.9,NSW1NSW1 +48501,2015-07-14 21:00:00,20848.34,NSW1NSW1 +48502,2015-07-14 22:00:00,19542.230000000003,NSW1NSW1 +48503,2015-07-14 23:00:00,18220.260000000002,NSW1NSW1 +48504,2015-07-15 00:00:00,17359.22,NSW1NSW1 +48505,2015-07-15 01:00:00,16549.52,NSW1NSW1 +48506,2015-07-15 02:00:00,15650.51,NSW1NSW1 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23:00:00,18361.800000000003,NSW1NSW1 +48528,2015-07-16 00:00:00,17435.37,NSW1NSW1 +48529,2015-07-16 01:00:00,16453.57,NSW1NSW1 +48530,2015-07-16 02:00:00,15456.86,NSW1NSW1 +48531,2015-07-16 03:00:00,14235.02,NSW1NSW1 +48532,2015-07-16 04:00:00,13780.91,NSW1NSW1 +48533,2015-07-16 05:00:00,14386.17,NSW1NSW1 +48534,2015-07-16 06:00:00,16419.51,NSW1NSW1 +48535,2015-07-16 07:00:00,19436.64,NSW1NSW1 +48536,2015-07-16 08:00:00,20954.22,NSW1NSW1 +48537,2015-07-16 09:00:00,20741.45,NSW1NSW1 +48538,2015-07-16 10:00:00,20771.21,NSW1NSW1 +48539,2015-07-16 11:00:00,20702.57,NSW1NSW1 +48540,2015-07-16 12:00:00,20218.12,NSW1NSW1 +48541,2015-07-16 13:00:00,19607.53,NSW1NSW1 +48542,2015-07-16 14:00:00,19282.25,NSW1NSW1 +48543,2015-07-16 15:00:00,19298.08,NSW1NSW1 +48544,2015-07-16 16:00:00,19791.71,NSW1NSW1 +48545,2015-07-16 17:00:00,21791.07,NSW1NSW1 +48546,2015-07-16 18:00:00,24175.71,NSW1NSW1 +48547,2015-07-16 19:00:00,23993.11,NSW1NSW1 +48548,2015-07-16 20:00:00,23037.3,NSW1NSW1 +48549,2015-07-16 21:00:00,21956.72,NSW1NSW1 +48550,2015-07-16 22:00:00,20594.75,NSW1NSW1 +48551,2015-07-16 23:00:00,19204.15,NSW1NSW1 +48552,2015-07-17 00:00:00,18261.739999999998,NSW1NSW1 +48553,2015-07-17 01:00:00,17247.14,NSW1NSW1 +48554,2015-07-17 02:00:00,16054.25,NSW1NSW1 +48555,2015-07-17 03:00:00,14679.09,NSW1NSW1 +48556,2015-07-17 04:00:00,14033.57,NSW1NSW1 +48557,2015-07-17 05:00:00,14533.24,NSW1NSW1 +48558,2015-07-17 06:00:00,16817.0,NSW1NSW1 +48559,2015-07-17 07:00:00,20209.24,NSW1NSW1 +48560,2015-07-17 08:00:00,22363.16,NSW1NSW1 +48561,2015-07-17 09:00:00,22655.91,NSW1NSW1 +48562,2015-07-17 10:00:00,22181.29,NSW1NSW1 +48563,2015-07-17 11:00:00,21704.010000000002,NSW1NSW1 +48564,2015-07-17 12:00:00,21209.42,NSW1NSW1 +48565,2015-07-17 13:00:00,20526.93,NSW1NSW1 +48566,2015-07-17 14:00:00,19950.13,NSW1NSW1 +48567,2015-07-17 15:00:00,19742.15,NSW1NSW1 +48568,2015-07-17 16:00:00,20398.65,NSW1NSW1 +48569,2015-07-17 17:00:00,21944.449999999997,NSW1NSW1 +48570,2015-07-17 18:00:00,23606.54,NSW1NSW1 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10:00:00,19882.88,NSW1NSW1 +48635,2015-07-20 11:00:00,18976.67,NSW1NSW1 +48636,2015-07-20 12:00:00,18183.95,NSW1NSW1 +48637,2015-07-20 13:00:00,17939.29,NSW1NSW1 +48638,2015-07-20 14:00:00,17884.010000000002,NSW1NSW1 +48639,2015-07-20 15:00:00,17993.019999999997,NSW1NSW1 +48640,2015-07-20 16:00:00,18888.48,NSW1NSW1 +48641,2015-07-20 17:00:00,20803.870000000003,NSW1NSW1 +48642,2015-07-20 18:00:00,23000.66,NSW1NSW1 +48643,2015-07-20 19:00:00,22623.39,NSW1NSW1 +48644,2015-07-20 20:00:00,21757.83,NSW1NSW1 +48645,2015-07-20 21:00:00,20786.82,NSW1NSW1 +48646,2015-07-20 22:00:00,19536.760000000002,NSW1NSW1 +48647,2015-07-20 23:00:00,18281.27,NSW1NSW1 +48648,2015-07-21 00:00:00,17477.27,NSW1NSW1 +48649,2015-07-21 01:00:00,16622.739999999998,NSW1NSW1 +48650,2015-07-21 02:00:00,15641.99,NSW1NSW1 +48651,2015-07-21 03:00:00,14512.5,NSW1NSW1 +48652,2015-07-21 04:00:00,13901.189999999999,NSW1NSW1 +48653,2015-07-21 05:00:00,14393.48,NSW1NSW1 +48654,2015-07-21 06:00:00,16679.29,NSW1NSW1 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17:00:00,19279.21,NSW1NSW1 +48738,2015-07-24 18:00:00,20444.949999999997,NSW1NSW1 +48739,2015-07-24 19:00:00,19765.510000000002,NSW1NSW1 +48740,2015-07-24 20:00:00,19004.300000000003,NSW1NSW1 +48741,2015-07-24 21:00:00,18228.82,NSW1NSW1 +48742,2015-07-24 22:00:00,17481.9,NSW1NSW1 +48743,2015-07-24 23:00:00,16994.93,NSW1NSW1 +48744,2015-07-25 00:00:00,16514.760000000002,NSW1NSW1 +48745,2015-07-25 01:00:00,15515.369999999999,NSW1NSW1 +48746,2015-07-25 02:00:00,14426.48,NSW1NSW1 +48747,2015-07-25 03:00:00,13207.42,NSW1NSW1 +48748,2015-07-25 04:00:00,12586.74,NSW1NSW1 +48749,2015-07-25 05:00:00,12642.56,NSW1NSW1 +48750,2015-07-25 06:00:00,13381.349999999999,NSW1NSW1 +48751,2015-07-25 07:00:00,14718.96,NSW1NSW1 +48752,2015-07-25 08:00:00,16381.140000000001,NSW1NSW1 +48753,2015-07-25 09:00:00,16976.23,NSW1NSW1 +48754,2015-07-25 10:00:00,16529.42,NSW1NSW1 +48755,2015-07-25 11:00:00,15686.98,NSW1NSW1 +48756,2015-07-25 12:00:00,15078.79,NSW1NSW1 +48757,2015-07-25 13:00:00,14585.05,NSW1NSW1 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11:00:00,15598.8,NSW1NSW1 +48780,2015-07-26 12:00:00,14958.26,NSW1NSW1 +48781,2015-07-26 13:00:00,14537.380000000001,NSW1NSW1 +48782,2015-07-26 14:00:00,14338.529999999999,NSW1NSW1 +48783,2015-07-26 15:00:00,14528.36,NSW1NSW1 +48784,2015-07-26 16:00:00,15461.06,NSW1NSW1 +48785,2015-07-26 17:00:00,17202.480000000003,NSW1NSW1 +48786,2015-07-26 18:00:00,19490.75,NSW1NSW1 +48787,2015-07-26 19:00:00,19407.84,NSW1NSW1 +48788,2015-07-26 20:00:00,18696.01,NSW1NSW1 +48789,2015-07-26 21:00:00,17875.27,NSW1NSW1 +48790,2015-07-26 22:00:00,17001.92,NSW1NSW1 +48791,2015-07-26 23:00:00,15965.380000000001,NSW1NSW1 +48792,2015-07-27 00:00:00,15292.43,NSW1NSW1 +48793,2015-07-27 01:00:00,14596.3,NSW1NSW1 +48794,2015-07-27 02:00:00,13826.970000000001,NSW1NSW1 +48795,2015-07-27 03:00:00,12994.23,NSW1NSW1 +48796,2015-07-27 04:00:00,12905.92,NSW1NSW1 +48797,2015-07-27 05:00:00,13589.64,NSW1NSW1 +48798,2015-07-27 06:00:00,15824.289999999999,NSW1NSW1 +48799,2015-07-27 07:00:00,19136.6,NSW1NSW1 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05:00:00,14533.92,NSW1NSW1 +48822,2015-07-28 06:00:00,16938.59,NSW1NSW1 +48823,2015-07-28 07:00:00,20260.199999999997,NSW1NSW1 +48824,2015-07-28 08:00:00,21492.440000000002,NSW1NSW1 +48825,2015-07-28 09:00:00,20553.129999999997,NSW1NSW1 +48826,2015-07-28 10:00:00,19529.45,NSW1NSW1 +48827,2015-07-28 11:00:00,18479.230000000003,NSW1NSW1 +48828,2015-07-28 12:00:00,17669.300000000003,NSW1NSW1 +48829,2015-07-28 13:00:00,17343.019999999997,NSW1NSW1 +48830,2015-07-28 14:00:00,17246.04,NSW1NSW1 +48831,2015-07-28 15:00:00,17258.92,NSW1NSW1 +48832,2015-07-28 16:00:00,18055.019999999997,NSW1NSW1 +48833,2015-07-28 17:00:00,20143.239999999998,NSW1NSW1 +48834,2015-07-28 18:00:00,22932.11,NSW1NSW1 +48835,2015-07-28 19:00:00,22942.97,NSW1NSW1 +48836,2015-07-28 20:00:00,22217.57,NSW1NSW1 +48837,2015-07-28 21:00:00,21292.42,NSW1NSW1 +48838,2015-07-28 22:00:00,19908.54,NSW1NSW1 +48839,2015-07-28 23:00:00,18703.300000000003,NSW1NSW1 +48840,2015-07-29 00:00:00,17842.29,NSW1NSW1 +48841,2015-07-29 01:00:00,16943.96,NSW1NSW1 +48842,2015-07-29 02:00:00,15943.35,NSW1NSW1 +48843,2015-07-29 03:00:00,14728.279999999999,NSW1NSW1 +48844,2015-07-29 04:00:00,14176.82,NSW1NSW1 +48845,2015-07-29 05:00:00,14819.23,NSW1NSW1 +48846,2015-07-29 06:00:00,17059.29,NSW1NSW1 +48847,2015-07-29 07:00:00,20395.98,NSW1NSW1 +48848,2015-07-29 08:00:00,21649.760000000002,NSW1NSW1 +48849,2015-07-29 09:00:00,20727.260000000002,NSW1NSW1 +48850,2015-07-29 10:00:00,19581.31,NSW1NSW1 +48851,2015-07-29 11:00:00,18521.02,NSW1NSW1 +48852,2015-07-29 12:00:00,17712.79,NSW1NSW1 +48853,2015-07-29 13:00:00,17202.41,NSW1NSW1 +48854,2015-07-29 14:00:00,17016.28,NSW1NSW1 +48855,2015-07-29 15:00:00,17024.199999999997,NSW1NSW1 +48856,2015-07-29 16:00:00,17758.62,NSW1NSW1 +48857,2015-07-29 17:00:00,19712.29,NSW1NSW1 +48858,2015-07-29 18:00:00,22255.03,NSW1NSW1 +48859,2015-07-29 19:00:00,22275.33,NSW1NSW1 +48860,2015-07-29 20:00:00,21624.89,NSW1NSW1 +48861,2015-07-29 21:00:00,20795.160000000003,NSW1NSW1 +48862,2015-07-29 22:00:00,19397.08,NSW1NSW1 +48863,2015-07-29 23:00:00,18297.82,NSW1NSW1 +48864,2015-07-30 00:00:00,17473.05,NSW1NSW1 +48865,2015-07-30 01:00:00,16574.32,NSW1NSW1 +48866,2015-07-30 02:00:00,15525.619999999999,NSW1NSW1 +48867,2015-07-30 03:00:00,14307.51,NSW1NSW1 +48868,2015-07-30 04:00:00,13750.05,NSW1NSW1 +48869,2015-07-30 05:00:00,14250.02,NSW1NSW1 +48870,2015-07-30 06:00:00,16372.279999999999,NSW1NSW1 +48871,2015-07-30 07:00:00,19538.4,NSW1NSW1 +48872,2015-07-30 08:00:00,20742.83,NSW1NSW1 +48873,2015-07-30 09:00:00,19692.17,NSW1NSW1 +48874,2015-07-30 10:00:00,18622.449999999997,NSW1NSW1 +48875,2015-07-30 11:00:00,17617.42,NSW1NSW1 +48876,2015-07-30 12:00:00,16874.83,NSW1NSW1 +48877,2015-07-30 13:00:00,16563.91,NSW1NSW1 +48878,2015-07-30 14:00:00,16415.3,NSW1NSW1 +48879,2015-07-30 15:00:00,16458.79,NSW1NSW1 +48880,2015-07-30 16:00:00,17260.07,NSW1NSW1 +48881,2015-07-30 17:00:00,18941.03,NSW1NSW1 +48882,2015-07-30 18:00:00,21250.65,NSW1NSW1 +48883,2015-07-30 19:00:00,21189.190000000002,NSW1NSW1 +48884,2015-07-30 20:00:00,20579.77,NSW1NSW1 +48885,2015-07-30 21:00:00,19568.67,NSW1NSW1 +48886,2015-07-30 22:00:00,18423.309999999998,NSW1NSW1 +48887,2015-07-30 23:00:00,17457.059999999998,NSW1NSW1 +48888,2015-07-31 00:00:00,16746.15,NSW1NSW1 +48889,2015-07-31 01:00:00,15895.42,NSW1NSW1 +48890,2015-07-31 02:00:00,14812.42,NSW1NSW1 +48891,2015-07-31 03:00:00,13727.41,NSW1NSW1 +48892,2015-07-31 04:00:00,13267.689999999999,NSW1NSW1 +48893,2015-07-31 05:00:00,13808.75,NSW1NSW1 +48894,2015-07-31 06:00:00,15859.77,NSW1NSW1 +48895,2015-07-31 07:00:00,18714.61,NSW1NSW1 +48896,2015-07-31 08:00:00,19726.86,NSW1NSW1 +48897,2015-07-31 09:00:00,18948.050000000003,NSW1NSW1 +48898,2015-07-31 10:00:00,18056.18,NSW1NSW1 +48899,2015-07-31 11:00:00,17247.23,NSW1NSW1 +48900,2015-07-31 12:00:00,16580.12,NSW1NSW1 +48901,2015-07-31 13:00:00,16093.95,NSW1NSW1 +48902,2015-07-31 14:00:00,15886.650000000001,NSW1NSW1 +48903,2015-07-31 15:00:00,15760.869999999999,NSW1NSW1 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10:00:00,15647.26,NSW1NSW1 +48947,2015-08-02 11:00:00,14886.91,NSW1NSW1 +48948,2015-08-02 12:00:00,14599.4,NSW1NSW1 +48949,2015-08-02 13:00:00,14342.8,NSW1NSW1 +48950,2015-08-02 14:00:00,14084.15,NSW1NSW1 +48951,2015-08-02 15:00:00,14174.01,NSW1NSW1 +48952,2015-08-02 16:00:00,14660.39,NSW1NSW1 +48953,2015-08-02 17:00:00,15655.59,NSW1NSW1 +48954,2015-08-02 18:00:00,17685.1,NSW1NSW1 +48955,2015-08-02 19:00:00,17554.82,NSW1NSW1 +48956,2015-08-02 20:00:00,16816.510000000002,NSW1NSW1 +48957,2015-08-02 21:00:00,16155.16,NSW1NSW1 +48958,2015-08-02 22:00:00,15554.529999999999,NSW1NSW1 +48959,2015-08-02 23:00:00,15048.02,NSW1NSW1 +48960,2015-08-03 00:00:00,14447.74,NSW1NSW1 +48961,2015-08-03 01:00:00,13751.94,NSW1NSW1 +48962,2015-08-03 02:00:00,13030.99,NSW1NSW1 +48963,2015-08-03 03:00:00,12368.82,NSW1NSW1 +48964,2015-08-03 04:00:00,12143.310000000001,NSW1NSW1 +48965,2015-08-03 05:00:00,12788.5,NSW1NSW1 +48966,2015-08-03 06:00:00,14897.91,NSW1NSW1 +48967,2015-08-03 07:00:00,17691.77,NSW1NSW1 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02:00:00,15379.96,NSW1NSW1 +49011,2015-08-05 03:00:00,14190.29,NSW1NSW1 +49012,2015-08-05 04:00:00,13727.42,NSW1NSW1 +49013,2015-08-05 05:00:00,14239.34,NSW1NSW1 +49014,2015-08-05 06:00:00,16494.18,NSW1NSW1 +49015,2015-08-05 07:00:00,19807.64,NSW1NSW1 +49016,2015-08-05 08:00:00,21078.440000000002,NSW1NSW1 +49017,2015-08-05 09:00:00,20438.46,NSW1NSW1 +49018,2015-08-05 10:00:00,19997.239999999998,NSW1NSW1 +49019,2015-08-05 11:00:00,19647.6,NSW1NSW1 +49020,2015-08-05 12:00:00,19237.769999999997,NSW1NSW1 +49021,2015-08-05 13:00:00,19042.79,NSW1NSW1 +49022,2015-08-05 14:00:00,18791.92,NSW1NSW1 +49023,2015-08-05 15:00:00,18647.690000000002,NSW1NSW1 +49024,2015-08-05 16:00:00,19156.940000000002,NSW1NSW1 +49025,2015-08-05 17:00:00,20790.67,NSW1NSW1 +49026,2015-08-05 18:00:00,23305.629999999997,NSW1NSW1 +49027,2015-08-05 19:00:00,23203.08,NSW1NSW1 +49028,2015-08-05 20:00:00,22403.63,NSW1NSW1 +49029,2015-08-05 21:00:00,21310.03,NSW1NSW1 +49030,2015-08-05 22:00:00,19720.52,NSW1NSW1 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17:00:00,19021.45,NSW1NSW1 +49074,2015-08-07 18:00:00,21326.21,NSW1NSW1 +49075,2015-08-07 19:00:00,21346.46,NSW1NSW1 +49076,2015-08-07 20:00:00,20766.16,NSW1NSW1 +49077,2015-08-07 21:00:00,20125.72,NSW1NSW1 +49078,2015-08-07 22:00:00,19378.62,NSW1NSW1 +49079,2015-08-07 23:00:00,18573.059999999998,NSW1NSW1 +49080,2015-08-08 00:00:00,17839.15,NSW1NSW1 +49081,2015-08-08 01:00:00,16843.870000000003,NSW1NSW1 +49082,2015-08-08 02:00:00,15627.79,NSW1NSW1 +49083,2015-08-08 03:00:00,14327.46,NSW1NSW1 +49084,2015-08-08 04:00:00,13654.939999999999,NSW1NSW1 +49085,2015-08-08 05:00:00,13673.81,NSW1NSW1 +49086,2015-08-08 06:00:00,14476.82,NSW1NSW1 +49087,2015-08-08 07:00:00,16078.47,NSW1NSW1 +49088,2015-08-08 08:00:00,18062.199999999997,NSW1NSW1 +49089,2015-08-08 09:00:00,18532.72,NSW1NSW1 +49090,2015-08-08 10:00:00,17828.440000000002,NSW1NSW1 +49091,2015-08-08 11:00:00,16798.56,NSW1NSW1 +49092,2015-08-08 12:00:00,16026.61,NSW1NSW1 +49093,2015-08-08 13:00:00,15531.07,NSW1NSW1 +49094,2015-08-08 14:00:00,15240.74,NSW1NSW1 +49095,2015-08-08 15:00:00,15283.67,NSW1NSW1 +49096,2015-08-08 16:00:00,16063.35,NSW1NSW1 +49097,2015-08-08 17:00:00,17681.879999999997,NSW1NSW1 +49098,2015-08-08 18:00:00,20112.1,NSW1NSW1 +49099,2015-08-08 19:00:00,20064.620000000003,NSW1NSW1 +49100,2015-08-08 20:00:00,19348.02,NSW1NSW1 +49101,2015-08-08 21:00:00,18798.25,NSW1NSW1 +49102,2015-08-08 22:00:00,18215.97,NSW1NSW1 +49103,2015-08-08 23:00:00,17540.42,NSW1NSW1 +49104,2015-08-09 00:00:00,16616.81,NSW1NSW1 +49105,2015-08-09 01:00:00,15470.189999999999,NSW1NSW1 +49106,2015-08-09 02:00:00,14426.130000000001,NSW1NSW1 +49107,2015-08-09 03:00:00,13455.59,NSW1NSW1 +49108,2015-08-09 04:00:00,13098.45,NSW1NSW1 +49109,2015-08-09 05:00:00,13207.89,NSW1NSW1 +49110,2015-08-09 06:00:00,13925.55,NSW1NSW1 +49111,2015-08-09 07:00:00,15204.35,NSW1NSW1 +49112,2015-08-09 08:00:00,16909.93,NSW1NSW1 +49113,2015-08-09 09:00:00,17656.449999999997,NSW1NSW1 +49114,2015-08-09 10:00:00,17226.21,NSW1NSW1 +49115,2015-08-09 11:00:00,16232.89,NSW1NSW1 +49116,2015-08-09 12:00:00,15417.91,NSW1NSW1 +49117,2015-08-09 13:00:00,14934.79,NSW1NSW1 +49118,2015-08-09 14:00:00,14670.630000000001,NSW1NSW1 +49119,2015-08-09 15:00:00,14920.44,NSW1NSW1 +49120,2015-08-09 16:00:00,15770.54,NSW1NSW1 +49121,2015-08-09 17:00:00,17527.77,NSW1NSW1 +49122,2015-08-09 18:00:00,20140.739999999998,NSW1NSW1 +49123,2015-08-09 19:00:00,20332.129999999997,NSW1NSW1 +49124,2015-08-09 20:00:00,19561.629999999997,NSW1NSW1 +49125,2015-08-09 21:00:00,18670.78,NSW1NSW1 +49126,2015-08-09 22:00:00,17487.65,NSW1NSW1 +49127,2015-08-09 23:00:00,16290.59,NSW1NSW1 +49128,2015-08-10 00:00:00,15457.36,NSW1NSW1 +49129,2015-08-10 01:00:00,14709.16,NSW1NSW1 +49130,2015-08-10 02:00:00,13873.720000000001,NSW1NSW1 +49131,2015-08-10 03:00:00,13069.58,NSW1NSW1 +49132,2015-08-10 04:00:00,12826.21,NSW1NSW1 +49133,2015-08-10 05:00:00,13517.7,NSW1NSW1 +49134,2015-08-10 06:00:00,15750.73,NSW1NSW1 +49135,2015-08-10 07:00:00,18789.47,NSW1NSW1 +49136,2015-08-10 08:00:00,19857.41,NSW1NSW1 +49137,2015-08-10 09:00:00,19101.75,NSW1NSW1 +49138,2015-08-10 10:00:00,18197.09,NSW1NSW1 +49139,2015-08-10 11:00:00,17358.269999999997,NSW1NSW1 +49140,2015-08-10 12:00:00,16780.760000000002,NSW1NSW1 +49141,2015-08-10 13:00:00,16467.79,NSW1NSW1 +49142,2015-08-10 14:00:00,16174.61,NSW1NSW1 +49143,2015-08-10 15:00:00,16119.130000000001,NSW1NSW1 +49144,2015-08-10 16:00:00,16670.589999999997,NSW1NSW1 +49145,2015-08-10 17:00:00,18223.55,NSW1NSW1 +49146,2015-08-10 18:00:00,20680.56,NSW1NSW1 +49147,2015-08-10 19:00:00,20779.85,NSW1NSW1 +49148,2015-08-10 20:00:00,19909.059999999998,NSW1NSW1 +49149,2015-08-10 21:00:00,18912.46,NSW1NSW1 +49150,2015-08-10 22:00:00,17699.36,NSW1NSW1 +49151,2015-08-10 23:00:00,16767.33,NSW1NSW1 +49152,2015-08-11 00:00:00,16380.37,NSW1NSW1 +49153,2015-08-11 01:00:00,15489.19,NSW1NSW1 +49154,2015-08-11 02:00:00,14512.83,NSW1NSW1 +49155,2015-08-11 03:00:00,13539.12,NSW1NSW1 +49156,2015-08-11 04:00:00,13159.470000000001,NSW1NSW1 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02:00:00,14992.26,NSW1NSW1 +49179,2015-08-12 03:00:00,13814.07,NSW1NSW1 +49180,2015-08-12 04:00:00,13442.53,NSW1NSW1 +49181,2015-08-12 05:00:00,14021.029999999999,NSW1NSW1 +49182,2015-08-12 06:00:00,16283.86,NSW1NSW1 +49183,2015-08-12 07:00:00,19406.190000000002,NSW1NSW1 +49184,2015-08-12 08:00:00,20330.5,NSW1NSW1 +49185,2015-08-12 09:00:00,19571.16,NSW1NSW1 +49186,2015-08-12 10:00:00,18749.07,NSW1NSW1 +49187,2015-08-12 11:00:00,18443.96,NSW1NSW1 +49188,2015-08-12 12:00:00,18635.03,NSW1NSW1 +49189,2015-08-12 13:00:00,18501.55,NSW1NSW1 +49190,2015-08-12 14:00:00,17510.38,NSW1NSW1 +49191,2015-08-12 15:00:00,17313.57,NSW1NSW1 +49192,2015-08-12 16:00:00,18152.71,NSW1NSW1 +49193,2015-08-12 17:00:00,19908.379999999997,NSW1NSW1 +49194,2015-08-12 18:00:00,22398.68,NSW1NSW1 +49195,2015-08-12 19:00:00,22363.449999999997,NSW1NSW1 +49196,2015-08-12 20:00:00,21586.41,NSW1NSW1 +49197,2015-08-12 21:00:00,20569.019999999997,NSW1NSW1 +49198,2015-08-12 22:00:00,19151.7,NSW1NSW1 +49199,2015-08-12 23:00:00,17951.38,NSW1NSW1 +49200,2015-08-13 00:00:00,17239.559999999998,NSW1NSW1 +49201,2015-08-13 01:00:00,16353.369999999999,NSW1NSW1 +49202,2015-08-13 02:00:00,15207.64,NSW1NSW1 +49203,2015-08-13 03:00:00,14037.849999999999,NSW1NSW1 +49204,2015-08-13 04:00:00,13551.6,NSW1NSW1 +49205,2015-08-13 05:00:00,14165.43,NSW1NSW1 +49206,2015-08-13 06:00:00,16329.830000000002,NSW1NSW1 +49207,2015-08-13 07:00:00,19398.870000000003,NSW1NSW1 +49208,2015-08-13 08:00:00,20153.61,NSW1NSW1 +49209,2015-08-13 09:00:00,19181.15,NSW1NSW1 +49210,2015-08-13 10:00:00,18384.61,NSW1NSW1 +49211,2015-08-13 11:00:00,17531.379999999997,NSW1NSW1 +49212,2015-08-13 12:00:00,16863.64,NSW1NSW1 +49213,2015-08-13 13:00:00,16435.15,NSW1NSW1 +49214,2015-08-13 14:00:00,16245.759999999998,NSW1NSW1 +49215,2015-08-13 15:00:00,16261.369999999999,NSW1NSW1 +49216,2015-08-13 16:00:00,16944.2,NSW1NSW1 +49217,2015-08-13 17:00:00,18531.07,NSW1NSW1 +49218,2015-08-13 18:00:00,21223.84,NSW1NSW1 +49219,2015-08-13 19:00:00,21451.16,NSW1NSW1 +49220,2015-08-13 20:00:00,20784.480000000003,NSW1NSW1 +49221,2015-08-13 21:00:00,19985.08,NSW1NSW1 +49222,2015-08-13 22:00:00,18954.85,NSW1NSW1 +49223,2015-08-13 23:00:00,17904.629999999997,NSW1NSW1 +49224,2015-08-14 00:00:00,17102.98,NSW1NSW1 +49225,2015-08-14 01:00:00,16214.97,NSW1NSW1 +49226,2015-08-14 02:00:00,15303.52,NSW1NSW1 +49227,2015-08-14 03:00:00,14154.86,NSW1NSW1 +49228,2015-08-14 04:00:00,13749.869999999999,NSW1NSW1 +49229,2015-08-14 05:00:00,14370.48,NSW1NSW1 +49230,2015-08-14 06:00:00,16538.19,NSW1NSW1 +49231,2015-08-14 07:00:00,19578.08,NSW1NSW1 +49232,2015-08-14 08:00:00,20555.83,NSW1NSW1 +49233,2015-08-14 09:00:00,19587.65,NSW1NSW1 +49234,2015-08-14 10:00:00,18724.47,NSW1NSW1 +49235,2015-08-14 11:00:00,17786.43,NSW1NSW1 +49236,2015-08-14 12:00:00,17099.96,NSW1NSW1 +49237,2015-08-14 13:00:00,16619.15,NSW1NSW1 +49238,2015-08-14 14:00:00,16354.869999999999,NSW1NSW1 +49239,2015-08-14 15:00:00,16255.15,NSW1NSW1 +49240,2015-08-14 16:00:00,16845.0,NSW1NSW1 +49241,2015-08-14 17:00:00,18166.96,NSW1NSW1 +49242,2015-08-14 18:00:00,20246.879999999997,NSW1NSW1 +49243,2015-08-14 19:00:00,20332.2,NSW1NSW1 +49244,2015-08-14 20:00:00,19809.15,NSW1NSW1 +49245,2015-08-14 21:00:00,19239.73,NSW1NSW1 +49246,2015-08-14 22:00:00,18490.739999999998,NSW1NSW1 +49247,2015-08-14 23:00:00,17811.629999999997,NSW1NSW1 +49248,2015-08-15 00:00:00,17317.0,NSW1NSW1 +49249,2015-08-15 01:00:00,16338.07,NSW1NSW1 +49250,2015-08-15 02:00:00,15127.029999999999,NSW1NSW1 +49251,2015-08-15 03:00:00,13988.26,NSW1NSW1 +49252,2015-08-15 04:00:00,13402.02,NSW1NSW1 +49253,2015-08-15 05:00:00,13443.150000000001,NSW1NSW1 +49254,2015-08-15 06:00:00,14342.16,NSW1NSW1 +49255,2015-08-15 07:00:00,15920.01,NSW1NSW1 +49256,2015-08-15 08:00:00,17537.48,NSW1NSW1 +49257,2015-08-15 09:00:00,17984.34,NSW1NSW1 +49258,2015-08-15 10:00:00,17370.39,NSW1NSW1 +49259,2015-08-15 11:00:00,16544.47,NSW1NSW1 +49260,2015-08-15 12:00:00,15984.3,NSW1NSW1 +49261,2015-08-15 13:00:00,15731.36,NSW1NSW1 +49262,2015-08-15 14:00:00,15651.25,NSW1NSW1 +49263,2015-08-15 15:00:00,15769.52,NSW1NSW1 +49264,2015-08-15 16:00:00,16204.93,NSW1NSW1 +49265,2015-08-15 17:00:00,17435.74,NSW1NSW1 +49266,2015-08-15 18:00:00,19225.41,NSW1NSW1 +49267,2015-08-15 19:00:00,19038.190000000002,NSW1NSW1 +49268,2015-08-15 20:00:00,18220.24,NSW1NSW1 +49269,2015-08-15 21:00:00,17571.02,NSW1NSW1 +49270,2015-08-15 22:00:00,16888.22,NSW1NSW1 +49271,2015-08-15 23:00:00,16367.83,NSW1NSW1 +49272,2015-08-16 00:00:00,15680.85,NSW1NSW1 +49273,2015-08-16 01:00:00,14705.42,NSW1NSW1 +49274,2015-08-16 02:00:00,13931.28,NSW1NSW1 +49275,2015-08-16 03:00:00,13044.560000000001,NSW1NSW1 +49276,2015-08-16 04:00:00,12701.73,NSW1NSW1 +49277,2015-08-16 05:00:00,12751.78,NSW1NSW1 +49278,2015-08-16 06:00:00,13370.06,NSW1NSW1 +49279,2015-08-16 07:00:00,14411.529999999999,NSW1NSW1 +49280,2015-08-16 08:00:00,15689.73,NSW1NSW1 +49281,2015-08-16 09:00:00,16234.7,NSW1NSW1 +49282,2015-08-16 10:00:00,15835.49,NSW1NSW1 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07:00:00,18291.54,NSW1NSW1 +49304,2015-08-17 08:00:00,19116.11,NSW1NSW1 +49305,2015-08-17 09:00:00,18417.3,NSW1NSW1 +49306,2015-08-17 10:00:00,17825.25,NSW1NSW1 +49307,2015-08-17 11:00:00,17223.54,NSW1NSW1 +49308,2015-08-17 12:00:00,16773.07,NSW1NSW1 +49309,2015-08-17 13:00:00,16416.77,NSW1NSW1 +49310,2015-08-17 14:00:00,16312.51,NSW1NSW1 +49311,2015-08-17 15:00:00,16250.41,NSW1NSW1 +49312,2015-08-17 16:00:00,16803.449999999997,NSW1NSW1 +49313,2015-08-17 17:00:00,18283.23,NSW1NSW1 +49314,2015-08-17 18:00:00,20550.41,NSW1NSW1 +49315,2015-08-17 19:00:00,20589.05,NSW1NSW1 +49316,2015-08-17 20:00:00,19803.34,NSW1NSW1 +49317,2015-08-17 21:00:00,18772.0,NSW1NSW1 +49318,2015-08-17 22:00:00,17696.47,NSW1NSW1 +49319,2015-08-17 23:00:00,16897.16,NSW1NSW1 +49320,2015-08-18 00:00:00,16316.259999999998,NSW1NSW1 +49321,2015-08-18 01:00:00,15630.01,NSW1NSW1 +49322,2015-08-18 02:00:00,14728.39,NSW1NSW1 +49323,2015-08-18 03:00:00,13735.52,NSW1NSW1 +49324,2015-08-18 04:00:00,13456.28,NSW1NSW1 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01:00:00,16352.8,NSW1NSW1 +49346,2015-08-19 02:00:00,15372.16,NSW1NSW1 +49347,2015-08-19 03:00:00,14181.32,NSW1NSW1 +49348,2015-08-19 04:00:00,13755.36,NSW1NSW1 +49349,2015-08-19 05:00:00,14272.369999999999,NSW1NSW1 +49350,2015-08-19 06:00:00,16440.35,NSW1NSW1 +49351,2015-08-19 07:00:00,19299.93,NSW1NSW1 +49352,2015-08-19 08:00:00,19960.81,NSW1NSW1 +49353,2015-08-19 09:00:00,19035.08,NSW1NSW1 +49354,2015-08-19 10:00:00,18134.77,NSW1NSW1 +49355,2015-08-19 11:00:00,17467.78,NSW1NSW1 +49356,2015-08-19 12:00:00,17029.4,NSW1NSW1 +49357,2015-08-19 13:00:00,16785.17,NSW1NSW1 +49358,2015-08-19 14:00:00,16762.67,NSW1NSW1 +49359,2015-08-19 15:00:00,16676.29,NSW1NSW1 +49360,2015-08-19 16:00:00,17113.86,NSW1NSW1 +49361,2015-08-19 17:00:00,18446.23,NSW1NSW1 +49362,2015-08-19 18:00:00,20840.8,NSW1NSW1 +49363,2015-08-19 19:00:00,21024.57,NSW1NSW1 +49364,2015-08-19 20:00:00,20376.22,NSW1NSW1 +49365,2015-08-19 21:00:00,19512.08,NSW1NSW1 +49366,2015-08-19 22:00:00,18206.879999999997,NSW1NSW1 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19:00:00,20098.11,NSW1NSW1 +49388,2015-08-20 20:00:00,19440.989999999998,NSW1NSW1 +49389,2015-08-20 21:00:00,18792.010000000002,NSW1NSW1 +49390,2015-08-20 22:00:00,17764.86,NSW1NSW1 +49391,2015-08-20 23:00:00,17001.92,NSW1NSW1 +49392,2015-08-21 00:00:00,16424.17,NSW1NSW1 +49393,2015-08-21 01:00:00,15609.470000000001,NSW1NSW1 +49394,2015-08-21 02:00:00,14696.880000000001,NSW1NSW1 +49395,2015-08-21 03:00:00,13612.970000000001,NSW1NSW1 +49396,2015-08-21 04:00:00,13211.189999999999,NSW1NSW1 +49397,2015-08-21 05:00:00,13708.060000000001,NSW1NSW1 +49398,2015-08-21 06:00:00,15793.38,NSW1NSW1 +49399,2015-08-21 07:00:00,18364.86,NSW1NSW1 +49400,2015-08-21 08:00:00,18885.89,NSW1NSW1 +49401,2015-08-21 09:00:00,18046.82,NSW1NSW1 +49402,2015-08-21 10:00:00,17399.64,NSW1NSW1 +49403,2015-08-21 11:00:00,16703.69,NSW1NSW1 +49404,2015-08-21 12:00:00,16142.060000000001,NSW1NSW1 +49405,2015-08-21 13:00:00,15962.07,NSW1NSW1 +49406,2015-08-21 14:00:00,15805.43,NSW1NSW1 +49407,2015-08-21 15:00:00,15850.650000000001,NSW1NSW1 +49408,2015-08-21 16:00:00,16348.32,NSW1NSW1 +49409,2015-08-21 17:00:00,17234.87,NSW1NSW1 +49410,2015-08-21 18:00:00,18706.03,NSW1NSW1 +49411,2015-08-21 19:00:00,18504.440000000002,NSW1NSW1 +49412,2015-08-21 20:00:00,17665.7,NSW1NSW1 +49413,2015-08-21 21:00:00,17203.16,NSW1NSW1 +49414,2015-08-21 22:00:00,16676.15,NSW1NSW1 +49415,2015-08-21 23:00:00,16241.16,NSW1NSW1 +49416,2015-08-22 00:00:00,15866.54,NSW1NSW1 +49417,2015-08-22 01:00:00,15113.279999999999,NSW1NSW1 +49418,2015-08-22 02:00:00,13968.09,NSW1NSW1 +49419,2015-08-22 03:00:00,12875.17,NSW1NSW1 +49420,2015-08-22 04:00:00,12267.53,NSW1NSW1 +49421,2015-08-22 05:00:00,12283.64,NSW1NSW1 +49422,2015-08-22 06:00:00,13015.4,NSW1NSW1 +49423,2015-08-22 07:00:00,14139.029999999999,NSW1NSW1 +49424,2015-08-22 08:00:00,15274.35,NSW1NSW1 +49425,2015-08-22 09:00:00,15703.34,NSW1NSW1 +49426,2015-08-22 10:00:00,15206.32,NSW1NSW1 +49427,2015-08-22 11:00:00,14521.84,NSW1NSW1 +49428,2015-08-22 12:00:00,14058.77,NSW1NSW1 +49429,2015-08-22 13:00:00,13727.67,NSW1NSW1 +49430,2015-08-22 14:00:00,13523.509999999998,NSW1NSW1 +49431,2015-08-22 15:00:00,13618.310000000001,NSW1NSW1 +49432,2015-08-22 16:00:00,14122.64,NSW1NSW1 +49433,2015-08-22 17:00:00,14825.779999999999,NSW1NSW1 +49434,2015-08-22 18:00:00,16167.74,NSW1NSW1 +49435,2015-08-22 19:00:00,16062.35,NSW1NSW1 +49436,2015-08-22 20:00:00,15272.380000000001,NSW1NSW1 +49437,2015-08-22 21:00:00,14882.869999999999,NSW1NSW1 +49438,2015-08-22 22:00:00,14524.14,NSW1NSW1 +49439,2015-08-22 23:00:00,14350.619999999999,NSW1NSW1 +49440,2015-08-23 00:00:00,13817.92,NSW1NSW1 +49441,2015-08-23 01:00:00,12996.61,NSW1NSW1 +49442,2015-08-23 02:00:00,12221.7,NSW1NSW1 +49443,2015-08-23 03:00:00,11502.48,NSW1NSW1 +49444,2015-08-23 04:00:00,11262.86,NSW1NSW1 +49445,2015-08-23 05:00:00,11335.85,NSW1NSW1 +49446,2015-08-23 06:00:00,11809.16,NSW1NSW1 +49447,2015-08-23 07:00:00,12589.060000000001,NSW1NSW1 +49448,2015-08-23 08:00:00,13948.32,NSW1NSW1 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00:00:00,15615.34,NSW1NSW1 +49513,2015-08-26 01:00:00,14910.75,NSW1NSW1 +49514,2015-08-26 02:00:00,13926.93,NSW1NSW1 +49515,2015-08-26 03:00:00,12746.75,NSW1NSW1 +49516,2015-08-26 04:00:00,12356.24,NSW1NSW1 +49517,2015-08-26 05:00:00,12827.279999999999,NSW1NSW1 +49518,2015-08-26 06:00:00,14625.56,NSW1NSW1 +49519,2015-08-26 07:00:00,16954.77,NSW1NSW1 +49520,2015-08-26 08:00:00,17782.690000000002,NSW1NSW1 +49521,2015-08-26 09:00:00,17483.37,NSW1NSW1 +49522,2015-08-26 10:00:00,17149.02,NSW1NSW1 +49523,2015-08-26 11:00:00,16792.410000000003,NSW1NSW1 +49524,2015-08-26 12:00:00,16477.97,NSW1NSW1 +49525,2015-08-26 13:00:00,16317.66,NSW1NSW1 +49526,2015-08-26 14:00:00,16268.42,NSW1NSW1 +49527,2015-08-26 15:00:00,16187.130000000001,NSW1NSW1 +49528,2015-08-26 16:00:00,16731.300000000003,NSW1NSW1 +49529,2015-08-26 17:00:00,17740.16,NSW1NSW1 +49530,2015-08-26 18:00:00,19319.41,NSW1NSW1 +49531,2015-08-26 19:00:00,19227.36,NSW1NSW1 +49532,2015-08-26 20:00:00,18368.82,NSW1NSW1 +49533,2015-08-26 21:00:00,17502.239999999998,NSW1NSW1 +49534,2015-08-26 22:00:00,16630.9,NSW1NSW1 +49535,2015-08-26 23:00:00,16071.31,NSW1NSW1 +49536,2015-08-27 00:00:00,15631.89,NSW1NSW1 +49537,2015-08-27 01:00:00,14886.599999999999,NSW1NSW1 +49538,2015-08-27 02:00:00,13984.6,NSW1NSW1 +49539,2015-08-27 03:00:00,12998.9,NSW1NSW1 +49540,2015-08-27 04:00:00,12572.119999999999,NSW1NSW1 +49541,2015-08-27 05:00:00,13073.84,NSW1NSW1 +49542,2015-08-27 06:00:00,14941.12,NSW1NSW1 +49543,2015-08-27 07:00:00,17244.300000000003,NSW1NSW1 +49544,2015-08-27 08:00:00,17968.59,NSW1NSW1 +49545,2015-08-27 09:00:00,17727.62,NSW1NSW1 +49546,2015-08-27 10:00:00,17625.12,NSW1NSW1 +49547,2015-08-27 11:00:00,17192.07,NSW1NSW1 +49548,2015-08-27 12:00:00,16862.93,NSW1NSW1 +49549,2015-08-27 13:00:00,16580.61,NSW1NSW1 +49550,2015-08-27 14:00:00,16592.73,NSW1NSW1 +49551,2015-08-27 15:00:00,16425.260000000002,NSW1NSW1 +49552,2015-08-27 16:00:00,16661.309999999998,NSW1NSW1 +49553,2015-08-27 17:00:00,17528.16,NSW1NSW1 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14:00:00,15909.3,NSW1NSW1 +49575,2015-08-28 15:00:00,15906.470000000001,NSW1NSW1 +49576,2015-08-28 16:00:00,16318.17,NSW1NSW1 +49577,2015-08-28 17:00:00,17379.809999999998,NSW1NSW1 +49578,2015-08-28 18:00:00,18878.0,NSW1NSW1 +49579,2015-08-28 19:00:00,18911.77,NSW1NSW1 +49580,2015-08-28 20:00:00,18189.91,NSW1NSW1 +49581,2015-08-28 21:00:00,17608.260000000002,NSW1NSW1 +49582,2015-08-28 22:00:00,17052.0,NSW1NSW1 +49583,2015-08-28 23:00:00,16525.64,NSW1NSW1 +49584,2015-08-29 00:00:00,16095.310000000001,NSW1NSW1 +49585,2015-08-29 01:00:00,15325.17,NSW1NSW1 +49586,2015-08-29 02:00:00,14153.41,NSW1NSW1 +49587,2015-08-29 03:00:00,13051.72,NSW1NSW1 +49588,2015-08-29 04:00:00,12525.49,NSW1NSW1 +49589,2015-08-29 05:00:00,12519.49,NSW1NSW1 +49590,2015-08-29 06:00:00,13258.189999999999,NSW1NSW1 +49591,2015-08-29 07:00:00,14515.369999999999,NSW1NSW1 +49592,2015-08-29 08:00:00,15759.3,NSW1NSW1 +49593,2015-08-29 09:00:00,16091.91,NSW1NSW1 +49594,2015-08-29 10:00:00,15554.84,NSW1NSW1 +49595,2015-08-29 11:00:00,14890.91,NSW1NSW1 +49596,2015-08-29 12:00:00,14240.33,NSW1NSW1 +49597,2015-08-29 13:00:00,13930.400000000001,NSW1NSW1 +49598,2015-08-29 14:00:00,13764.31,NSW1NSW1 +49599,2015-08-29 15:00:00,13903.61,NSW1NSW1 +49600,2015-08-29 16:00:00,14417.05,NSW1NSW1 +49601,2015-08-29 17:00:00,15303.82,NSW1NSW1 +49602,2015-08-29 18:00:00,17385.15,NSW1NSW1 +49603,2015-08-29 19:00:00,17768.02,NSW1NSW1 +49604,2015-08-29 20:00:00,17196.04,NSW1NSW1 +49605,2015-08-29 21:00:00,16993.8,NSW1NSW1 +49606,2015-08-29 22:00:00,16513.089999999997,NSW1NSW1 +49607,2015-08-29 23:00:00,16024.07,NSW1NSW1 +49608,2015-08-30 00:00:00,15400.47,NSW1NSW1 +49609,2015-08-30 01:00:00,14500.61,NSW1NSW1 +49610,2015-08-30 02:00:00,13583.97,NSW1NSW1 +49611,2015-08-30 03:00:00,12774.92,NSW1NSW1 +49612,2015-08-30 04:00:00,12389.21,NSW1NSW1 +49613,2015-08-30 05:00:00,12462.42,NSW1NSW1 +49614,2015-08-30 06:00:00,12904.06,NSW1NSW1 +49615,2015-08-30 07:00:00,14053.81,NSW1NSW1 +49616,2015-08-30 08:00:00,15293.9,NSW1NSW1 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05:00:00,13297.69,NSW1NSW1 +49638,2015-08-31 06:00:00,15368.98,NSW1NSW1 +49639,2015-08-31 07:00:00,17775.91,NSW1NSW1 +49640,2015-08-31 08:00:00,18378.73,NSW1NSW1 +49641,2015-08-31 09:00:00,17615.15,NSW1NSW1 +49642,2015-08-31 10:00:00,17117.739999999998,NSW1NSW1 +49643,2015-08-31 11:00:00,16586.63,NSW1NSW1 +49644,2015-08-31 12:00:00,16152.45,NSW1NSW1 +49645,2015-08-31 13:00:00,16053.98,NSW1NSW1 +49646,2015-08-31 14:00:00,16040.119999999999,NSW1NSW1 +49647,2015-08-31 15:00:00,16027.24,NSW1NSW1 +49648,2015-08-31 16:00:00,16505.34,NSW1NSW1 +49649,2015-08-31 17:00:00,17480.18,NSW1NSW1 +49650,2015-08-31 18:00:00,19499.07,NSW1NSW1 +49651,2015-08-31 19:00:00,19862.83,NSW1NSW1 +49652,2015-08-31 20:00:00,19146.98,NSW1NSW1 +49653,2015-08-31 21:00:00,18223.57,NSW1NSW1 +49654,2015-08-31 22:00:00,17238.64,NSW1NSW1 +49655,2015-08-31 23:00:00,16528.36,NSW1NSW1 +49656,2015-09-01 00:00:00,16230.529999999999,NSW1NSW1 +49657,2015-09-01 01:00:00,15508.95,NSW1NSW1 +49658,2015-09-01 02:00:00,14700.56,NSW1NSW1 +49659,2015-09-01 03:00:00,13720.060000000001,NSW1NSW1 +49660,2015-09-01 04:00:00,13286.24,NSW1NSW1 +49661,2015-09-01 05:00:00,13830.49,NSW1NSW1 +49662,2015-09-01 06:00:00,15874.3,NSW1NSW1 +49663,2015-09-01 07:00:00,18379.510000000002,NSW1NSW1 +49664,2015-09-01 08:00:00,18852.66,NSW1NSW1 +49665,2015-09-01 09:00:00,17932.64,NSW1NSW1 +49666,2015-09-01 10:00:00,17236.52,NSW1NSW1 +49667,2015-09-01 11:00:00,16588.85,NSW1NSW1 +49668,2015-09-01 12:00:00,16049.54,NSW1NSW1 +49669,2015-09-01 13:00:00,15873.48,NSW1NSW1 +49670,2015-09-01 14:00:00,15624.05,NSW1NSW1 +49671,2015-09-01 15:00:00,15658.48,NSW1NSW1 +49672,2015-09-01 16:00:00,16142.63,NSW1NSW1 +49673,2015-09-01 17:00:00,17264.39,NSW1NSW1 +49674,2015-09-01 18:00:00,19480.27,NSW1NSW1 +49675,2015-09-01 19:00:00,20038.79,NSW1NSW1 +49676,2015-09-01 20:00:00,19388.489999999998,NSW1NSW1 +49677,2015-09-01 21:00:00,18594.17,NSW1NSW1 +49678,2015-09-01 22:00:00,17624.010000000002,NSW1NSW1 +49679,2015-09-01 23:00:00,16898.48,NSW1NSW1 +49680,2015-09-02 00:00:00,16358.189999999999,NSW1NSW1 +49681,2015-09-02 01:00:00,15631.880000000001,NSW1NSW1 +49682,2015-09-02 02:00:00,14647.49,NSW1NSW1 +49683,2015-09-02 03:00:00,13711.560000000001,NSW1NSW1 +49684,2015-09-02 04:00:00,13297.130000000001,NSW1NSW1 +49685,2015-09-02 05:00:00,13845.33,NSW1NSW1 +49686,2015-09-02 06:00:00,15838.68,NSW1NSW1 +49687,2015-09-02 07:00:00,18358.690000000002,NSW1NSW1 +49688,2015-09-02 08:00:00,18962.28,NSW1NSW1 +49689,2015-09-02 09:00:00,18402.019999999997,NSW1NSW1 +49690,2015-09-02 10:00:00,17931.49,NSW1NSW1 +49691,2015-09-02 11:00:00,17118.83,NSW1NSW1 +49692,2015-09-02 12:00:00,16439.72,NSW1NSW1 +49693,2015-09-02 13:00:00,16007.099999999999,NSW1NSW1 +49694,2015-09-02 14:00:00,15792.05,NSW1NSW1 +49695,2015-09-02 15:00:00,15846.810000000001,NSW1NSW1 +49696,2015-09-02 16:00:00,16329.94,NSW1NSW1 +49697,2015-09-02 17:00:00,17364.2,NSW1NSW1 +49698,2015-09-02 18:00:00,19343.489999999998,NSW1NSW1 +49699,2015-09-02 19:00:00,19613.39,NSW1NSW1 +49700,2015-09-02 20:00:00,18879.010000000002,NSW1NSW1 +49701,2015-09-02 21:00:00,17963.62,NSW1NSW1 +49702,2015-09-02 22:00:00,17004.81,NSW1NSW1 +49703,2015-09-02 23:00:00,16331.52,NSW1NSW1 +49704,2015-09-03 00:00:00,15927.369999999999,NSW1NSW1 +49705,2015-09-03 01:00:00,15167.48,NSW1NSW1 +49706,2015-09-03 02:00:00,14124.43,NSW1NSW1 +49707,2015-09-03 03:00:00,13036.25,NSW1NSW1 +49708,2015-09-03 04:00:00,12542.08,NSW1NSW1 +49709,2015-09-03 05:00:00,12994.380000000001,NSW1NSW1 +49710,2015-09-03 06:00:00,14919.39,NSW1NSW1 +49711,2015-09-03 07:00:00,17191.9,NSW1NSW1 +49712,2015-09-03 08:00:00,17541.559999999998,NSW1NSW1 +49713,2015-09-03 09:00:00,17248.3,NSW1NSW1 +49714,2015-09-03 10:00:00,17177.309999999998,NSW1NSW1 +49715,2015-09-03 11:00:00,17014.440000000002,NSW1NSW1 +49716,2015-09-03 12:00:00,16704.64,NSW1NSW1 +49717,2015-09-03 13:00:00,16489.010000000002,NSW1NSW1 +49718,2015-09-03 14:00:00,16411.72,NSW1NSW1 +49719,2015-09-03 15:00:00,16426.879999999997,NSW1NSW1 +49720,2015-09-03 16:00:00,16769.61,NSW1NSW1 +49721,2015-09-03 17:00:00,17706.91,NSW1NSW1 +49722,2015-09-03 18:00:00,19507.48,NSW1NSW1 +49723,2015-09-03 19:00:00,19587.870000000003,NSW1NSW1 +49724,2015-09-03 20:00:00,18909.36,NSW1NSW1 +49725,2015-09-03 21:00:00,18146.72,NSW1NSW1 +49726,2015-09-03 22:00:00,17236.379999999997,NSW1NSW1 +49727,2015-09-03 23:00:00,16675.47,NSW1NSW1 +49728,2015-09-04 00:00:00,16148.29,NSW1NSW1 +49729,2015-09-04 01:00:00,15430.57,NSW1NSW1 +49730,2015-09-04 02:00:00,14460.2,NSW1NSW1 +49731,2015-09-04 03:00:00,13443.91,NSW1NSW1 +49732,2015-09-04 04:00:00,12991.560000000001,NSW1NSW1 +49733,2015-09-04 05:00:00,13470.83,NSW1NSW1 +49734,2015-09-04 06:00:00,15286.23,NSW1NSW1 +49735,2015-09-04 07:00:00,17534.309999999998,NSW1NSW1 +49736,2015-09-04 08:00:00,18294.61,NSW1NSW1 +49737,2015-09-04 09:00:00,17999.98,NSW1NSW1 +49738,2015-09-04 10:00:00,17716.199999999997,NSW1NSW1 +49739,2015-09-04 11:00:00,17217.1,NSW1NSW1 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11:00:00,15094.509999999998,NSW1NSW1 +50100,2015-09-19 12:00:00,14783.060000000001,NSW1NSW1 +50101,2015-09-19 13:00:00,14497.43,NSW1NSW1 +50102,2015-09-19 14:00:00,14215.83,NSW1NSW1 +50103,2015-09-19 15:00:00,14207.7,NSW1NSW1 +50104,2015-09-19 16:00:00,14533.369999999999,NSW1NSW1 +50105,2015-09-19 17:00:00,15094.75,NSW1NSW1 +50106,2015-09-19 18:00:00,16371.77,NSW1NSW1 +50107,2015-09-19 19:00:00,16612.35,NSW1NSW1 +50108,2015-09-19 20:00:00,15896.279999999999,NSW1NSW1 +50109,2015-09-19 21:00:00,15348.64,NSW1NSW1 +50110,2015-09-19 22:00:00,15010.669999999998,NSW1NSW1 +50111,2015-09-19 23:00:00,14672.83,NSW1NSW1 +50112,2015-09-20 00:00:00,14165.74,NSW1NSW1 +50113,2015-09-20 01:00:00,13400.77,NSW1NSW1 +50114,2015-09-20 02:00:00,12659.65,NSW1NSW1 +50115,2015-09-20 03:00:00,11875.91,NSW1NSW1 +50116,2015-09-20 04:00:00,11574.73,NSW1NSW1 +50117,2015-09-20 05:00:00,11669.6,NSW1NSW1 +50118,2015-09-20 06:00:00,12021.880000000001,NSW1NSW1 +50119,2015-09-20 07:00:00,12637.98,NSW1NSW1 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04:00:00,11655.380000000001,NSW1NSW1 +50141,2015-09-21 05:00:00,12266.36,NSW1NSW1 +50142,2015-09-21 06:00:00,13838.07,NSW1NSW1 +50143,2015-09-21 07:00:00,15371.06,NSW1NSW1 +50144,2015-09-21 08:00:00,16173.619999999999,NSW1NSW1 +50145,2015-09-21 09:00:00,16128.74,NSW1NSW1 +50146,2015-09-21 10:00:00,15949.880000000001,NSW1NSW1 +50147,2015-09-21 11:00:00,15742.74,NSW1NSW1 +50148,2015-09-21 12:00:00,15519.16,NSW1NSW1 +50149,2015-09-21 13:00:00,15528.7,NSW1NSW1 +50150,2015-09-21 14:00:00,15612.09,NSW1NSW1 +50151,2015-09-21 15:00:00,15755.009999999998,NSW1NSW1 +50152,2015-09-21 16:00:00,15947.900000000001,NSW1NSW1 +50153,2015-09-21 17:00:00,16462.33,NSW1NSW1 +50154,2015-09-21 18:00:00,17648.06,NSW1NSW1 +50155,2015-09-21 19:00:00,17780.809999999998,NSW1NSW1 +50156,2015-09-21 20:00:00,16943.93,NSW1NSW1 +50157,2015-09-21 21:00:00,16199.21,NSW1NSW1 +50158,2015-09-21 22:00:00,15560.16,NSW1NSW1 +50159,2015-09-21 23:00:00,15132.630000000001,NSW1NSW1 +50160,2015-09-22 00:00:00,14836.470000000001,NSW1NSW1 +50161,2015-09-22 01:00:00,14282.41,NSW1NSW1 +50162,2015-09-22 02:00:00,13295.44,NSW1NSW1 +50163,2015-09-22 03:00:00,12249.990000000002,NSW1NSW1 +50164,2015-09-22 04:00:00,11776.52,NSW1NSW1 +50165,2015-09-22 05:00:00,12334.720000000001,NSW1NSW1 +50166,2015-09-22 06:00:00,13845.46,NSW1NSW1 +50167,2015-09-22 07:00:00,15355.84,NSW1NSW1 +50168,2015-09-22 08:00:00,16087.92,NSW1NSW1 +50169,2015-09-22 09:00:00,16044.689999999999,NSW1NSW1 +50170,2015-09-22 10:00:00,16107.89,NSW1NSW1 +50171,2015-09-22 11:00:00,15951.14,NSW1NSW1 +50172,2015-09-22 12:00:00,15839.490000000002,NSW1NSW1 +50173,2015-09-22 13:00:00,15746.97,NSW1NSW1 +50174,2015-09-22 14:00:00,15791.380000000001,NSW1NSW1 +50175,2015-09-22 15:00:00,15915.71,NSW1NSW1 +50176,2015-09-22 16:00:00,16210.34,NSW1NSW1 +50177,2015-09-22 17:00:00,17140.18,NSW1NSW1 +50178,2015-09-22 18:00:00,18553.89,NSW1NSW1 +50179,2015-09-22 19:00:00,18801.17,NSW1NSW1 +50180,2015-09-22 20:00:00,17948.32,NSW1NSW1 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18:00:00,19403.06,NSW1NSW1 +50203,2015-09-23 19:00:00,20134.66,NSW1NSW1 +50204,2015-09-23 20:00:00,19299.28,NSW1NSW1 +50205,2015-09-23 21:00:00,18423.2,NSW1NSW1 +50206,2015-09-23 22:00:00,17475.190000000002,NSW1NSW1 +50207,2015-09-23 23:00:00,16524.870000000003,NSW1NSW1 +50208,2015-09-24 00:00:00,15991.29,NSW1NSW1 +50209,2015-09-24 01:00:00,15221.869999999999,NSW1NSW1 +50210,2015-09-24 02:00:00,14379.33,NSW1NSW1 +50211,2015-09-24 03:00:00,13320.1,NSW1NSW1 +50212,2015-09-24 04:00:00,12884.82,NSW1NSW1 +50213,2015-09-24 05:00:00,13329.19,NSW1NSW1 +50214,2015-09-24 06:00:00,15019.919999999998,NSW1NSW1 +50215,2015-09-24 07:00:00,16978.18,NSW1NSW1 +50216,2015-09-24 08:00:00,17650.739999999998,NSW1NSW1 +50217,2015-09-24 09:00:00,17586.3,NSW1NSW1 +50218,2015-09-24 10:00:00,17340.09,NSW1NSW1 +50219,2015-09-24 11:00:00,16882.510000000002,NSW1NSW1 +50220,2015-09-24 12:00:00,16622.85,NSW1NSW1 +50221,2015-09-24 13:00:00,16552.03,NSW1NSW1 +50222,2015-09-24 14:00:00,16278.05,NSW1NSW1 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11:00:00,17361.519999999997,NSW1NSW1 +50244,2015-09-25 12:00:00,16978.84,NSW1NSW1 +50245,2015-09-25 13:00:00,16824.53,NSW1NSW1 +50246,2015-09-25 14:00:00,16671.91,NSW1NSW1 +50247,2015-09-25 15:00:00,16729.47,NSW1NSW1 +50248,2015-09-25 16:00:00,17030.84,NSW1NSW1 +50249,2015-09-25 17:00:00,17906.489999999998,NSW1NSW1 +50250,2015-09-25 18:00:00,19314.83,NSW1NSW1 +50251,2015-09-25 19:00:00,19509.96,NSW1NSW1 +50252,2015-09-25 20:00:00,18592.2,NSW1NSW1 +50253,2015-09-25 21:00:00,17882.43,NSW1NSW1 +50254,2015-09-25 22:00:00,17168.309999999998,NSW1NSW1 +50255,2015-09-25 23:00:00,16518.78,NSW1NSW1 +50256,2015-09-26 00:00:00,16089.41,NSW1NSW1 +50257,2015-09-26 01:00:00,15195.79,NSW1NSW1 +50258,2015-09-26 02:00:00,14232.95,NSW1NSW1 +50259,2015-09-26 03:00:00,13000.64,NSW1NSW1 +50260,2015-09-26 04:00:00,12535.650000000001,NSW1NSW1 +50261,2015-09-26 05:00:00,12597.68,NSW1NSW1 +50262,2015-09-26 06:00:00,13171.3,NSW1NSW1 +50263,2015-09-26 07:00:00,14223.32,NSW1NSW1 +50264,2015-09-26 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05:00:00,11865.93,NSW1NSW1 +51102,2015-10-31 06:00:00,12657.48,NSW1NSW1 +51103,2015-10-31 07:00:00,13939.06,NSW1NSW1 +51104,2015-10-31 08:00:00,14843.02,NSW1NSW1 +51105,2015-10-31 09:00:00,15070.71,NSW1NSW1 +51106,2015-10-31 10:00:00,14921.49,NSW1NSW1 +51107,2015-10-31 11:00:00,14783.310000000001,NSW1NSW1 +51108,2015-10-31 12:00:00,14641.58,NSW1NSW1 +51109,2015-10-31 13:00:00,14387.18,NSW1NSW1 +51110,2015-10-31 14:00:00,14370.8,NSW1NSW1 +51111,2015-10-31 15:00:00,14659.74,NSW1NSW1 +51112,2015-10-31 16:00:00,14799.25,NSW1NSW1 +51113,2015-10-31 17:00:00,14820.83,NSW1NSW1 +51114,2015-10-31 18:00:00,14859.95,NSW1NSW1 +51115,2015-10-31 19:00:00,14905.81,NSW1NSW1 +51116,2015-10-31 20:00:00,14432.84,NSW1NSW1 +51117,2015-10-31 21:00:00,14051.880000000001,NSW1NSW1 +51118,2015-10-31 22:00:00,13816.84,NSW1NSW1 +51119,2015-10-31 23:00:00,13393.15,NSW1NSW1 +51120,2015-11-01 00:00:00,12964.58,NSW1NSW1 +51121,2015-11-01 01:00:00,12270.630000000001,NSW1NSW1 +51122,2015-11-01 02:00:00,11585.08,NSW1NSW1 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21:00:00,15521.5,NSW1NSW1 +51166,2015-11-02 22:00:00,14896.36,NSW1NSW1 +51167,2015-11-02 23:00:00,14221.89,NSW1NSW1 +51168,2015-11-03 00:00:00,13694.470000000001,NSW1NSW1 +51169,2015-11-03 01:00:00,12917.97,NSW1NSW1 +51170,2015-11-03 02:00:00,11952.33,NSW1NSW1 +51171,2015-11-03 03:00:00,11579.19,NSW1NSW1 +51172,2015-11-03 04:00:00,11955.279999999999,NSW1NSW1 +51173,2015-11-03 05:00:00,13228.599999999999,NSW1NSW1 +51174,2015-11-03 06:00:00,15183.28,NSW1NSW1 +51175,2015-11-03 07:00:00,16399.0,NSW1NSW1 +51176,2015-11-03 08:00:00,16719.64,NSW1NSW1 +51177,2015-11-03 09:00:00,16994.440000000002,NSW1NSW1 +51178,2015-11-03 10:00:00,16973.11,NSW1NSW1 +51179,2015-11-03 11:00:00,16857.17,NSW1NSW1 +51180,2015-11-03 12:00:00,16538.010000000002,NSW1NSW1 +51181,2015-11-03 13:00:00,16451.79,NSW1NSW1 +51182,2015-11-03 14:00:00,14768.11,NSW1NSW1 +51183,2015-11-03 15:00:00,14711.25,NSW1NSW1 +51184,2015-11-03 16:00:00,15443.52,NSW1NSW1 +51185,2015-11-03 17:00:00,16555.47,NSW1NSW1 +51186,2015-11-03 18:00:00,16533.03,NSW1NSW1 +51187,2015-11-03 19:00:00,16332.21,NSW1NSW1 +51188,2015-11-03 20:00:00,15575.32,NSW1NSW1 +51189,2015-11-03 21:00:00,14865.27,NSW1NSW1 +51190,2015-11-03 22:00:00,14487.91,NSW1NSW1 +51191,2015-11-03 23:00:00,13653.599999999999,NSW1NSW1 +51192,2015-11-04 00:00:00,13494.69,NSW1NSW1 +51193,2015-11-04 01:00:00,12735.34,NSW1NSW1 +51194,2015-11-04 02:00:00,11660.72,NSW1NSW1 +51195,2015-11-04 03:00:00,11257.68,NSW1NSW1 +51196,2015-11-04 04:00:00,11686.11,NSW1NSW1 +51197,2015-11-04 05:00:00,13040.52,NSW1NSW1 +51198,2015-11-04 06:00:00,14946.29,NSW1NSW1 +51199,2015-11-04 07:00:00,16170.16,NSW1NSW1 +51200,2015-11-04 08:00:00,16480.7,NSW1NSW1 +51201,2015-11-04 09:00:00,16709.089999999997,NSW1NSW1 +51202,2015-11-04 10:00:00,16862.62,NSW1NSW1 +51203,2015-11-04 11:00:00,16727.33,NSW1NSW1 +51204,2015-11-04 12:00:00,16489.47,NSW1NSW1 +51205,2015-11-04 13:00:00,16383.86,NSW1NSW1 +51206,2015-11-04 14:00:00,16253.46,NSW1NSW1 +51207,2015-11-04 15:00:00,16349.84,NSW1NSW1 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12:00:00,16428.559999999998,NSW1NSW1 +51229,2015-11-05 13:00:00,16378.52,NSW1NSW1 +51230,2015-11-05 14:00:00,16240.939999999999,NSW1NSW1 +51231,2015-11-05 15:00:00,16376.84,NSW1NSW1 +51232,2015-11-05 16:00:00,16510.67,NSW1NSW1 +51233,2015-11-05 17:00:00,16823.09,NSW1NSW1 +51234,2015-11-05 18:00:00,16767.08,NSW1NSW1 +51235,2015-11-05 19:00:00,16569.52,NSW1NSW1 +51236,2015-11-05 20:00:00,15781.39,NSW1NSW1 +51237,2015-11-05 21:00:00,14981.71,NSW1NSW1 +51238,2015-11-05 22:00:00,14700.3,NSW1NSW1 +51239,2015-11-05 23:00:00,14325.95,NSW1NSW1 +51240,2015-11-06 00:00:00,13918.82,NSW1NSW1 +51241,2015-11-06 01:00:00,12969.09,NSW1NSW1 +51242,2015-11-06 02:00:00,11886.32,NSW1NSW1 +51243,2015-11-06 03:00:00,11495.560000000001,NSW1NSW1 +51244,2015-11-06 04:00:00,11859.74,NSW1NSW1 +51245,2015-11-06 05:00:00,13184.14,NSW1NSW1 +51246,2015-11-06 06:00:00,15024.970000000001,NSW1NSW1 +51247,2015-11-06 07:00:00,16101.99,NSW1NSW1 +51248,2015-11-06 08:00:00,16351.77,NSW1NSW1 +51249,2015-11-06 09:00:00,16680.71,NSW1NSW1 +51250,2015-11-06 10:00:00,16933.76,NSW1NSW1 +51251,2015-11-06 11:00:00,16921.29,NSW1NSW1 +51252,2015-11-06 12:00:00,16828.57,NSW1NSW1 +51253,2015-11-06 13:00:00,16681.989999999998,NSW1NSW1 +51254,2015-11-06 14:00:00,16203.08,NSW1NSW1 +51255,2015-11-06 15:00:00,16314.7,NSW1NSW1 +51256,2015-11-06 16:00:00,16367.5,NSW1NSW1 +51257,2015-11-06 17:00:00,16039.65,NSW1NSW1 +51258,2015-11-06 18:00:00,15775.65,NSW1NSW1 +51259,2015-11-06 19:00:00,15869.64,NSW1NSW1 +51260,2015-11-06 20:00:00,15372.46,NSW1NSW1 +51261,2015-11-06 21:00:00,14710.130000000001,NSW1NSW1 +51262,2015-11-06 22:00:00,14324.2,NSW1NSW1 +51263,2015-11-06 23:00:00,14268.74,NSW1NSW1 +51264,2015-11-07 00:00:00,13699.99,NSW1NSW1 +51265,2015-11-07 01:00:00,12784.48,NSW1NSW1 +51266,2015-11-07 02:00:00,11768.099999999999,NSW1NSW1 +51267,2015-11-07 03:00:00,11302.54,NSW1NSW1 +51268,2015-11-07 04:00:00,11309.59,NSW1NSW1 +51269,2015-11-07 05:00:00,11738.29,NSW1NSW1 +51270,2015-11-07 06:00:00,12629.9,NSW1NSW1 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03:00:00,10826.04,NSW1NSW1 +51292,2015-11-08 04:00:00,10827.3,NSW1NSW1 +51293,2015-11-08 05:00:00,11084.09,NSW1NSW1 +51294,2015-11-08 06:00:00,11643.939999999999,NSW1NSW1 +51295,2015-11-08 07:00:00,12583.150000000001,NSW1NSW1 +51296,2015-11-08 08:00:00,13409.94,NSW1NSW1 +51297,2015-11-08 09:00:00,13909.19,NSW1NSW1 +51298,2015-11-08 10:00:00,14094.75,NSW1NSW1 +51299,2015-11-08 11:00:00,13945.94,NSW1NSW1 +51300,2015-11-08 12:00:00,13691.43,NSW1NSW1 +51301,2015-11-08 13:00:00,13521.47,NSW1NSW1 +51302,2015-11-08 14:00:00,13539.369999999999,NSW1NSW1 +51303,2015-11-08 15:00:00,13760.439999999999,NSW1NSW1 +51304,2015-11-08 16:00:00,14090.16,NSW1NSW1 +51305,2015-11-08 17:00:00,14645.47,NSW1NSW1 +51306,2015-11-08 18:00:00,14791.74,NSW1NSW1 +51307,2015-11-08 19:00:00,14952.41,NSW1NSW1 +51308,2015-11-08 20:00:00,14666.79,NSW1NSW1 +51309,2015-11-08 21:00:00,14010.56,NSW1NSW1 +51310,2015-11-08 22:00:00,13521.900000000001,NSW1NSW1 +51311,2015-11-08 23:00:00,13159.5,NSW1NSW1 +51312,2015-11-09 00:00:00,12715.150000000001,NSW1NSW1 +51313,2015-11-09 01:00:00,12008.56,NSW1NSW1 +51314,2015-11-09 02:00:00,11323.24,NSW1NSW1 +51315,2015-11-09 03:00:00,11148.73,NSW1NSW1 +51316,2015-11-09 04:00:00,11551.48,NSW1NSW1 +51317,2015-11-09 05:00:00,12856.6,NSW1NSW1 +51318,2015-11-09 06:00:00,14751.82,NSW1NSW1 +51319,2015-11-09 07:00:00,15658.25,NSW1NSW1 +51320,2015-11-09 08:00:00,15773.470000000001,NSW1NSW1 +51321,2015-11-09 09:00:00,15934.74,NSW1NSW1 +51322,2015-11-09 10:00:00,16046.86,NSW1NSW1 +51323,2015-11-09 11:00:00,15856.9,NSW1NSW1 +51324,2015-11-09 12:00:00,15855.98,NSW1NSW1 +51325,2015-11-09 13:00:00,15902.560000000001,NSW1NSW1 +51326,2015-11-09 14:00:00,15907.11,NSW1NSW1 +51327,2015-11-09 15:00:00,16270.029999999999,NSW1NSW1 +51328,2015-11-09 16:00:00,16488.22,NSW1NSW1 +51329,2015-11-09 17:00:00,16662.510000000002,NSW1NSW1 +51330,2015-11-09 18:00:00,16483.800000000003,NSW1NSW1 +51331,2015-11-09 19:00:00,16401.73,NSW1NSW1 +51332,2015-11-09 20:00:00,15840.73,NSW1NSW1 +51333,2015-11-09 21:00:00,14969.27,NSW1NSW1 +51334,2015-11-09 22:00:00,14440.029999999999,NSW1NSW1 +51335,2015-11-09 23:00:00,14168.349999999999,NSW1NSW1 +51336,2015-11-10 00:00:00,13685.34,NSW1NSW1 +51337,2015-11-10 01:00:00,12905.650000000001,NSW1NSW1 +51338,2015-11-10 02:00:00,11983.41,NSW1NSW1 +51339,2015-11-10 03:00:00,11669.73,NSW1NSW1 +51340,2015-11-10 04:00:00,12096.869999999999,NSW1NSW1 +51341,2015-11-10 05:00:00,13309.279999999999,NSW1NSW1 +51342,2015-11-10 06:00:00,15085.54,NSW1NSW1 +51343,2015-11-10 07:00:00,15869.599999999999,NSW1NSW1 +51344,2015-11-10 08:00:00,16078.5,NSW1NSW1 +51345,2015-11-10 09:00:00,16413.03,NSW1NSW1 +51346,2015-11-10 10:00:00,16398.989999999998,NSW1NSW1 +51347,2015-11-10 11:00:00,16465.29,NSW1NSW1 +51348,2015-11-10 12:00:00,16606.61,NSW1NSW1 +51349,2015-11-10 13:00:00,16905.05,NSW1NSW1 +51350,2015-11-10 14:00:00,17067.629999999997,NSW1NSW1 +51351,2015-11-10 15:00:00,17443.85,NSW1NSW1 +51352,2015-11-10 16:00:00,17559.9,NSW1NSW1 +51353,2015-11-10 17:00:00,17328.28,NSW1NSW1 +51354,2015-11-10 18:00:00,16872.989999999998,NSW1NSW1 +51355,2015-11-10 19:00:00,16862.66,NSW1NSW1 +51356,2015-11-10 20:00:00,16133.630000000001,NSW1NSW1 +51357,2015-11-10 21:00:00,15255.89,NSW1NSW1 +51358,2015-11-10 22:00:00,14729.189999999999,NSW1NSW1 +51359,2015-11-10 23:00:00,14290.73,NSW1NSW1 +51360,2015-11-11 00:00:00,13897.64,NSW1NSW1 +51361,2015-11-11 01:00:00,12977.64,NSW1NSW1 +51362,2015-11-11 02:00:00,11940.58,NSW1NSW1 +51363,2015-11-11 03:00:00,11695.11,NSW1NSW1 +51364,2015-11-11 04:00:00,12099.75,NSW1NSW1 +51365,2015-11-11 05:00:00,13328.09,NSW1NSW1 +51366,2015-11-11 06:00:00,15150.509999999998,NSW1NSW1 +51367,2015-11-11 07:00:00,16211.67,NSW1NSW1 +51368,2015-11-11 08:00:00,16434.86,NSW1NSW1 +51369,2015-11-11 09:00:00,16715.199999999997,NSW1NSW1 +51370,2015-11-11 10:00:00,16723.52,NSW1NSW1 +51371,2015-11-11 11:00:00,16753.63,NSW1NSW1 +51372,2015-11-11 12:00:00,16586.02,NSW1NSW1 +51373,2015-11-11 13:00:00,16611.9,NSW1NSW1 +51374,2015-11-11 14:00:00,16562.67,NSW1NSW1 +51375,2015-11-11 15:00:00,16798.239999999998,NSW1NSW1 +51376,2015-11-11 16:00:00,16916.47,NSW1NSW1 +51377,2015-11-11 17:00:00,16906.58,NSW1NSW1 +51378,2015-11-11 18:00:00,16817.02,NSW1NSW1 +51379,2015-11-11 19:00:00,16755.86,NSW1NSW1 +51380,2015-11-11 20:00:00,16020.23,NSW1NSW1 +51381,2015-11-11 21:00:00,15213.24,NSW1NSW1 +51382,2015-11-11 22:00:00,14811.57,NSW1NSW1 +51383,2015-11-11 23:00:00,14490.04,NSW1NSW1 +51384,2015-11-12 00:00:00,14008.060000000001,NSW1NSW1 +51385,2015-11-12 01:00:00,13119.509999999998,NSW1NSW1 +51386,2015-11-12 02:00:00,12122.36,NSW1NSW1 +51387,2015-11-12 03:00:00,11853.77,NSW1NSW1 +51388,2015-11-12 04:00:00,12231.880000000001,NSW1NSW1 +51389,2015-11-12 05:00:00,13443.130000000001,NSW1NSW1 +51390,2015-11-12 06:00:00,15252.130000000001,NSW1NSW1 +51391,2015-11-12 07:00:00,16210.150000000001,NSW1NSW1 +51392,2015-11-12 08:00:00,16553.120000000003,NSW1NSW1 +51393,2015-11-12 09:00:00,16765.48,NSW1NSW1 +51394,2015-11-12 10:00:00,16932.75,NSW1NSW1 +51395,2015-11-12 11:00:00,16953.85,NSW1NSW1 +51396,2015-11-12 12:00:00,17022.8,NSW1NSW1 +51397,2015-11-12 13:00:00,17178.97,NSW1NSW1 +51398,2015-11-12 14:00:00,17032.309999999998,NSW1NSW1 +51399,2015-11-12 15:00:00,17011.68,NSW1NSW1 +51400,2015-11-12 16:00:00,16997.92,NSW1NSW1 +51401,2015-11-12 17:00:00,16973.440000000002,NSW1NSW1 +51402,2015-11-12 18:00:00,16658.4,NSW1NSW1 +51403,2015-11-12 19:00:00,16603.28,NSW1NSW1 +51404,2015-11-12 20:00:00,16030.21,NSW1NSW1 +51405,2015-11-12 21:00:00,15149.529999999999,NSW1NSW1 +51406,2015-11-12 22:00:00,14800.48,NSW1NSW1 +51407,2015-11-12 23:00:00,14324.25,NSW1NSW1 +51408,2015-11-13 00:00:00,13839.720000000001,NSW1NSW1 +51409,2015-11-13 01:00:00,12954.21,NSW1NSW1 +51410,2015-11-13 02:00:00,12020.380000000001,NSW1NSW1 +51411,2015-11-13 03:00:00,11723.83,NSW1NSW1 +51412,2015-11-13 04:00:00,12018.11,NSW1NSW1 +51413,2015-11-13 05:00:00,13207.61,NSW1NSW1 +51414,2015-11-13 06:00:00,15109.6,NSW1NSW1 +51415,2015-11-13 07:00:00,16027.88,NSW1NSW1 +51416,2015-11-13 08:00:00,16425.6,NSW1NSW1 +51417,2015-11-13 09:00:00,16805.25,NSW1NSW1 +51418,2015-11-13 10:00:00,17010.14,NSW1NSW1 +51419,2015-11-13 11:00:00,17076.769999999997,NSW1NSW1 +51420,2015-11-13 12:00:00,17084.35,NSW1NSW1 +51421,2015-11-13 13:00:00,17385.120000000003,NSW1NSW1 +51422,2015-11-13 14:00:00,17102.03,NSW1NSW1 +51423,2015-11-13 15:00:00,17177.0,NSW1NSW1 +51424,2015-11-13 16:00:00,17169.35,NSW1NSW1 +51425,2015-11-13 17:00:00,16888.52,NSW1NSW1 +51426,2015-11-13 18:00:00,16365.119999999999,NSW1NSW1 +51427,2015-11-13 19:00:00,15731.240000000002,NSW1NSW1 +51428,2015-11-13 20:00:00,15226.55,NSW1NSW1 +51429,2015-11-13 21:00:00,14644.869999999999,NSW1NSW1 +51430,2015-11-13 22:00:00,14504.7,NSW1NSW1 +51431,2015-11-13 23:00:00,14252.69,NSW1NSW1 +51432,2015-11-14 00:00:00,13610.3,NSW1NSW1 +51433,2015-11-14 01:00:00,12601.09,NSW1NSW1 +51434,2015-11-14 02:00:00,11669.78,NSW1NSW1 +51435,2015-11-14 03:00:00,11301.51,NSW1NSW1 +51436,2015-11-14 04:00:00,11257.220000000001,NSW1NSW1 +51437,2015-11-14 05:00:00,11787.06,NSW1NSW1 +51438,2015-11-14 06:00:00,12718.35,NSW1NSW1 +51439,2015-11-14 07:00:00,13990.13,NSW1NSW1 +51440,2015-11-14 08:00:00,15054.91,NSW1NSW1 +51441,2015-11-14 09:00:00,15348.259999999998,NSW1NSW1 +51442,2015-11-14 10:00:00,15233.779999999999,NSW1NSW1 +51443,2015-11-14 11:00:00,15066.93,NSW1NSW1 +51444,2015-11-14 12:00:00,14833.33,NSW1NSW1 +51445,2015-11-14 13:00:00,14622.39,NSW1NSW1 +51446,2015-11-14 14:00:00,14490.970000000001,NSW1NSW1 +51447,2015-11-14 15:00:00,14582.84,NSW1NSW1 +51448,2015-11-14 16:00:00,14798.439999999999,NSW1NSW1 +51449,2015-11-14 17:00:00,15042.48,NSW1NSW1 +51450,2015-11-14 18:00:00,15027.14,NSW1NSW1 +51451,2015-11-14 19:00:00,14947.970000000001,NSW1NSW1 +51452,2015-11-14 20:00:00,14467.119999999999,NSW1NSW1 +51453,2015-11-14 21:00:00,13959.25,NSW1NSW1 +51454,2015-11-14 22:00:00,13658.619999999999,NSW1NSW1 +51455,2015-11-14 23:00:00,13227.869999999999,NSW1NSW1 +51456,2015-11-15 00:00:00,12722.68,NSW1NSW1 +51457,2015-11-15 01:00:00,12089.54,NSW1NSW1 +51458,2015-11-15 02:00:00,11283.6,NSW1NSW1 +51459,2015-11-15 03:00:00,10985.619999999999,NSW1NSW1 +51460,2015-11-15 04:00:00,11041.57,NSW1NSW1 +51461,2015-11-15 05:00:00,11226.79,NSW1NSW1 +51462,2015-11-15 06:00:00,11902.060000000001,NSW1NSW1 +51463,2015-11-15 07:00:00,12901.29,NSW1NSW1 +51464,2015-11-15 08:00:00,13778.029999999999,NSW1NSW1 +51465,2015-11-15 09:00:00,14276.18,NSW1NSW1 +51466,2015-11-15 10:00:00,14207.45,NSW1NSW1 +51467,2015-11-15 11:00:00,14051.76,NSW1NSW1 +51468,2015-11-15 12:00:00,13767.33,NSW1NSW1 +51469,2015-11-15 13:00:00,13624.72,NSW1NSW1 +51470,2015-11-15 14:00:00,13564.17,NSW1NSW1 +51471,2015-11-15 15:00:00,13709.150000000001,NSW1NSW1 +51472,2015-11-15 16:00:00,14004.74,NSW1NSW1 +51473,2015-11-15 17:00:00,14525.57,NSW1NSW1 +51474,2015-11-15 18:00:00,14794.83,NSW1NSW1 +51475,2015-11-15 19:00:00,14995.74,NSW1NSW1 +51476,2015-11-15 20:00:00,14815.7,NSW1NSW1 +51477,2015-11-15 21:00:00,14123.310000000001,NSW1NSW1 +51478,2015-11-15 22:00:00,13782.32,NSW1NSW1 +51479,2015-11-15 23:00:00,13328.16,NSW1NSW1 +51480,2015-11-16 00:00:00,12946.220000000001,NSW1NSW1 +51481,2015-11-16 01:00:00,12282.54,NSW1NSW1 +51482,2015-11-16 02:00:00,11590.66,NSW1NSW1 +51483,2015-11-16 03:00:00,11366.419999999998,NSW1NSW1 +51484,2015-11-16 04:00:00,11721.85,NSW1NSW1 +51485,2015-11-16 05:00:00,13037.060000000001,NSW1NSW1 +51486,2015-11-16 06:00:00,15025.25,NSW1NSW1 +51487,2015-11-16 07:00:00,15911.24,NSW1NSW1 +51488,2015-11-16 08:00:00,15965.900000000001,NSW1NSW1 +51489,2015-11-16 09:00:00,15977.77,NSW1NSW1 +51490,2015-11-16 10:00:00,15866.32,NSW1NSW1 +51491,2015-11-16 11:00:00,15660.029999999999,NSW1NSW1 +51492,2015-11-16 12:00:00,15643.0,NSW1NSW1 +51493,2015-11-16 13:00:00,15692.67,NSW1NSW1 +51494,2015-11-16 14:00:00,15701.26,NSW1NSW1 +51495,2015-11-16 15:00:00,15978.51,NSW1NSW1 +51496,2015-11-16 16:00:00,16326.38,NSW1NSW1 +51497,2015-11-16 17:00:00,16468.15,NSW1NSW1 +51498,2015-11-16 18:00:00,16162.57,NSW1NSW1 +51499,2015-11-16 19:00:00,16170.04,NSW1NSW1 +51500,2015-11-16 20:00:00,15841.150000000001,NSW1NSW1 +51501,2015-11-16 21:00:00,15050.45,NSW1NSW1 +51502,2015-11-16 22:00:00,14579.650000000001,NSW1NSW1 +51503,2015-11-16 23:00:00,14214.41,NSW1NSW1 +51504,2015-11-17 00:00:00,13958.23,NSW1NSW1 +51505,2015-11-17 01:00:00,13100.25,NSW1NSW1 +51506,2015-11-17 02:00:00,12144.849999999999,NSW1NSW1 +51507,2015-11-17 03:00:00,11748.98,NSW1NSW1 +51508,2015-11-17 04:00:00,12138.48,NSW1NSW1 +51509,2015-11-17 05:00:00,13265.31,NSW1NSW1 +51510,2015-11-17 06:00:00,14952.470000000001,NSW1NSW1 +51511,2015-11-17 07:00:00,15771.19,NSW1NSW1 +51512,2015-11-17 08:00:00,15844.599999999999,NSW1NSW1 +51513,2015-11-17 09:00:00,16048.21,NSW1NSW1 +51514,2015-11-17 10:00:00,16113.529999999999,NSW1NSW1 +51515,2015-11-17 11:00:00,16067.61,NSW1NSW1 +51516,2015-11-17 12:00:00,16140.66,NSW1NSW1 +51517,2015-11-17 13:00:00,16389.28,NSW1NSW1 +51518,2015-11-17 14:00:00,16512.65,NSW1NSW1 +51519,2015-11-17 15:00:00,16906.940000000002,NSW1NSW1 +51520,2015-11-17 16:00:00,17301.66,NSW1NSW1 +51521,2015-11-17 17:00:00,17307.76,NSW1NSW1 +51522,2015-11-17 18:00:00,16914.64,NSW1NSW1 +51523,2015-11-17 19:00:00,16840.77,NSW1NSW1 +51524,2015-11-17 20:00:00,16435.92,NSW1NSW1 +51525,2015-11-17 21:00:00,15599.66,NSW1NSW1 +51526,2015-11-17 22:00:00,15104.31,NSW1NSW1 +51527,2015-11-17 23:00:00,14548.24,NSW1NSW1 +51528,2015-11-18 00:00:00,13981.599999999999,NSW1NSW1 +51529,2015-11-18 01:00:00,13054.6,NSW1NSW1 +51530,2015-11-18 02:00:00,11959.779999999999,NSW1NSW1 +51531,2015-11-18 03:00:00,11564.11,NSW1NSW1 +51532,2015-11-18 04:00:00,11877.65,NSW1NSW1 +51533,2015-11-18 05:00:00,13145.44,NSW1NSW1 +51534,2015-11-18 06:00:00,14855.52,NSW1NSW1 +51535,2015-11-18 07:00:00,15674.650000000001,NSW1NSW1 +51536,2015-11-18 08:00:00,16109.36,NSW1NSW1 +51537,2015-11-18 09:00:00,16655.65,NSW1NSW1 +51538,2015-11-18 10:00:00,17164.07,NSW1NSW1 +51539,2015-11-18 11:00:00,17613.6,NSW1NSW1 +51540,2015-11-18 12:00:00,17997.940000000002,NSW1NSW1 +51541,2015-11-18 13:00:00,18663.7,NSW1NSW1 +51542,2015-11-18 14:00:00,19283.18,NSW1NSW1 +51543,2015-11-18 15:00:00,20298.27,NSW1NSW1 +51544,2015-11-18 16:00:00,21107.41,NSW1NSW1 +51545,2015-11-18 17:00:00,21160.15,NSW1NSW1 +51546,2015-11-18 18:00:00,20519.67,NSW1NSW1 +51547,2015-11-18 19:00:00,19691.75,NSW1NSW1 +51548,2015-11-18 20:00:00,18494.489999999998,NSW1NSW1 +51549,2015-11-18 21:00:00,17073.22,NSW1NSW1 +51550,2015-11-18 22:00:00,16146.51,NSW1NSW1 +51551,2015-11-18 23:00:00,15327.69,NSW1NSW1 +51552,2015-11-19 00:00:00,14498.35,NSW1NSW1 +51553,2015-11-19 01:00:00,13510.86,NSW1NSW1 +51554,2015-11-19 02:00:00,12495.439999999999,NSW1NSW1 +51555,2015-11-19 03:00:00,12246.09,NSW1NSW1 +51556,2015-11-19 04:00:00,12676.2,NSW1NSW1 +51557,2015-11-19 05:00:00,13781.150000000001,NSW1NSW1 +51558,2015-11-19 06:00:00,15703.560000000001,NSW1NSW1 +51559,2015-11-19 07:00:00,16936.47,NSW1NSW1 +51560,2015-11-19 08:00:00,17585.199999999997,NSW1NSW1 +51561,2015-11-19 09:00:00,18208.760000000002,NSW1NSW1 +51562,2015-11-19 10:00:00,18658.2,NSW1NSW1 +51563,2015-11-19 11:00:00,19292.059999999998,NSW1NSW1 +51564,2015-11-19 12:00:00,19752.74,NSW1NSW1 +51565,2015-11-19 13:00:00,20409.36,NSW1NSW1 +51566,2015-11-19 14:00:00,21175.91,NSW1NSW1 +51567,2015-11-19 15:00:00,22155.85,NSW1NSW1 +51568,2015-11-19 16:00:00,23033.11,NSW1NSW1 +51569,2015-11-19 17:00:00,23306.269999999997,NSW1NSW1 +51570,2015-11-19 18:00:00,23011.03,NSW1NSW1 +51571,2015-11-19 19:00:00,22238.04,NSW1NSW1 +51572,2015-11-19 20:00:00,21157.370000000003,NSW1NSW1 +51573,2015-11-19 21:00:00,19293.339999999997,NSW1NSW1 +51574,2015-11-19 22:00:00,17776.04,NSW1NSW1 +51575,2015-11-19 23:00:00,16512.33,NSW1NSW1 +51576,2015-11-20 00:00:00,15331.970000000001,NSW1NSW1 +51577,2015-11-20 01:00:00,14214.09,NSW1NSW1 +51578,2015-11-20 02:00:00,13190.21,NSW1NSW1 +51579,2015-11-20 03:00:00,13024.91,NSW1NSW1 +51580,2015-11-20 04:00:00,13358.779999999999,NSW1NSW1 +51581,2015-11-20 05:00:00,14558.35,NSW1NSW1 +51582,2015-11-20 06:00:00,16445.89,NSW1NSW1 +51583,2015-11-20 07:00:00,18119.980000000003,NSW1NSW1 +51584,2015-11-20 08:00:00,19298.85,NSW1NSW1 +51585,2015-11-20 09:00:00,20379.66,NSW1NSW1 +51586,2015-11-20 10:00:00,21435.59,NSW1NSW1 +51587,2015-11-20 11:00:00,22257.64,NSW1NSW1 +51588,2015-11-20 12:00:00,23277.81,NSW1NSW1 +51589,2015-11-20 13:00:00,23379.35,NSW1NSW1 +51590,2015-11-20 14:00:00,23932.64,NSW1NSW1 +51591,2015-11-20 15:00:00,24920.87,NSW1NSW1 +51592,2015-11-20 16:00:00,25173.22,NSW1NSW1 +51593,2015-11-20 17:00:00,24310.17,NSW1NSW1 +51594,2015-11-20 18:00:00,23352.82,NSW1NSW1 +51595,2015-11-20 19:00:00,21984.86,NSW1NSW1 +51596,2015-11-20 20:00:00,20536.84,NSW1NSW1 +51597,2015-11-20 21:00:00,18663.879999999997,NSW1NSW1 +51598,2015-11-20 22:00:00,17236.14,NSW1NSW1 +51599,2015-11-20 23:00:00,16116.259999999998,NSW1NSW1 +51600,2015-11-21 00:00:00,15173.07,NSW1NSW1 +51601,2015-11-21 01:00:00,13930.1,NSW1NSW1 +51602,2015-11-21 02:00:00,12896.900000000001,NSW1NSW1 +51603,2015-11-21 03:00:00,12483.83,NSW1NSW1 +51604,2015-11-21 04:00:00,12545.94,NSW1NSW1 +51605,2015-11-21 05:00:00,12840.25,NSW1NSW1 +51606,2015-11-21 06:00:00,13768.0,NSW1NSW1 +51607,2015-11-21 07:00:00,14907.91,NSW1NSW1 +51608,2015-11-21 08:00:00,15742.869999999999,NSW1NSW1 +51609,2015-11-21 09:00:00,15984.76,NSW1NSW1 +51610,2015-11-21 10:00:00,15701.36,NSW1NSW1 +51611,2015-11-21 11:00:00,15492.98,NSW1NSW1 +51612,2015-11-21 12:00:00,15324.0,NSW1NSW1 +51613,2015-11-21 13:00:00,15138.04,NSW1NSW1 +51614,2015-11-21 14:00:00,14907.27,NSW1NSW1 +51615,2015-11-21 15:00:00,15137.85,NSW1NSW1 +51616,2015-11-21 16:00:00,15260.1,NSW1NSW1 +51617,2015-11-21 17:00:00,15254.7,NSW1NSW1 +51618,2015-11-21 18:00:00,15069.46,NSW1NSW1 +51619,2015-11-21 19:00:00,14930.45,NSW1NSW1 +51620,2015-11-21 20:00:00,14762.02,NSW1NSW1 +51621,2015-11-21 21:00:00,14284.380000000001,NSW1NSW1 +51622,2015-11-21 22:00:00,13999.599999999999,NSW1NSW1 +51623,2015-11-21 23:00:00,13566.95,NSW1NSW1 +51624,2015-11-22 00:00:00,12981.869999999999,NSW1NSW1 +51625,2015-11-22 01:00:00,12273.75,NSW1NSW1 +51626,2015-11-22 02:00:00,11595.08,NSW1NSW1 +51627,2015-11-22 03:00:00,11389.49,NSW1NSW1 +51628,2015-11-22 04:00:00,11471.21,NSW1NSW1 +51629,2015-11-22 05:00:00,11595.05,NSW1NSW1 +51630,2015-11-22 06:00:00,12211.43,NSW1NSW1 +51631,2015-11-22 07:00:00,13210.91,NSW1NSW1 +51632,2015-11-22 08:00:00,14233.42,NSW1NSW1 +51633,2015-11-22 09:00:00,14715.26,NSW1NSW1 +51634,2015-11-22 10:00:00,14653.970000000001,NSW1NSW1 +51635,2015-11-22 11:00:00,14597.04,NSW1NSW1 +51636,2015-11-22 12:00:00,14480.95,NSW1NSW1 +51637,2015-11-22 13:00:00,14313.77,NSW1NSW1 +51638,2015-11-22 14:00:00,14233.54,NSW1NSW1 +51639,2015-11-22 15:00:00,14243.44,NSW1NSW1 +51640,2015-11-22 16:00:00,14522.81,NSW1NSW1 +51641,2015-11-22 17:00:00,15028.810000000001,NSW1NSW1 +51642,2015-11-22 18:00:00,15264.32,NSW1NSW1 +51643,2015-11-22 19:00:00,15523.58,NSW1NSW1 +51644,2015-11-22 20:00:00,15323.99,NSW1NSW1 +51645,2015-11-22 21:00:00,14573.66,NSW1NSW1 +51646,2015-11-22 22:00:00,14100.16,NSW1NSW1 +51647,2015-11-22 23:00:00,13543.080000000002,NSW1NSW1 +51648,2015-11-23 00:00:00,13078.64,NSW1NSW1 +51649,2015-11-23 01:00:00,12487.16,NSW1NSW1 +51650,2015-11-23 02:00:00,11845.560000000001,NSW1NSW1 +51651,2015-11-23 03:00:00,11690.869999999999,NSW1NSW1 +51652,2015-11-23 04:00:00,12045.21,NSW1NSW1 +51653,2015-11-23 05:00:00,13330.759999999998,NSW1NSW1 +51654,2015-11-23 06:00:00,15216.01,NSW1NSW1 +51655,2015-11-23 07:00:00,16297.54,NSW1NSW1 +51656,2015-11-23 08:00:00,16675.0,NSW1NSW1 +51657,2015-11-23 09:00:00,16996.6,NSW1NSW1 +51658,2015-11-23 10:00:00,17172.77,NSW1NSW1 +51659,2015-11-23 11:00:00,17204.23,NSW1NSW1 +51660,2015-11-23 12:00:00,17230.809999999998,NSW1NSW1 +51661,2015-11-23 13:00:00,17406.2,NSW1NSW1 +51662,2015-11-23 14:00:00,17500.63,NSW1NSW1 +51663,2015-11-23 15:00:00,17780.940000000002,NSW1NSW1 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09:00:00,17373.11,NSW1NSW1 +51706,2015-11-25 10:00:00,17716.75,NSW1NSW1 +51707,2015-11-25 11:00:00,18042.14,NSW1NSW1 +51708,2015-11-25 12:00:00,18437.14,NSW1NSW1 +51709,2015-11-25 13:00:00,18964.08,NSW1NSW1 +51710,2015-11-25 14:00:00,19471.0,NSW1NSW1 +51711,2015-11-25 15:00:00,20038.11,NSW1NSW1 +51712,2015-11-25 16:00:00,20783.08,NSW1NSW1 +51713,2015-11-25 17:00:00,20843.059999999998,NSW1NSW1 +51714,2015-11-25 18:00:00,20089.15,NSW1NSW1 +51715,2015-11-25 19:00:00,19321.22,NSW1NSW1 +51716,2015-11-25 20:00:00,18566.09,NSW1NSW1 +51717,2015-11-25 21:00:00,17191.07,NSW1NSW1 +51718,2015-11-25 22:00:00,16048.17,NSW1NSW1 +51719,2015-11-25 23:00:00,15138.599999999999,NSW1NSW1 +51720,2015-11-26 00:00:00,14286.65,NSW1NSW1 +51721,2015-11-26 01:00:00,13340.31,NSW1NSW1 +51722,2015-11-26 02:00:00,12374.45,NSW1NSW1 +51723,2015-11-26 03:00:00,12139.78,NSW1NSW1 +51724,2015-11-26 04:00:00,12597.8,NSW1NSW1 +51725,2015-11-26 05:00:00,13843.09,NSW1NSW1 +51726,2015-11-26 06:00:00,15916.78,NSW1NSW1 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10:00:00,18916.370000000003,NSW1NSW1 +52043,2015-12-09 11:00:00,19448.91,NSW1NSW1 +52044,2015-12-09 12:00:00,19936.92,NSW1NSW1 +52045,2015-12-09 13:00:00,20613.059999999998,NSW1NSW1 +52046,2015-12-09 14:00:00,21116.32,NSW1NSW1 +52047,2015-12-09 15:00:00,21993.62,NSW1NSW1 +52048,2015-12-09 16:00:00,22538.83,NSW1NSW1 +52049,2015-12-09 17:00:00,22251.5,NSW1NSW1 +52050,2015-12-09 18:00:00,21315.55,NSW1NSW1 +52051,2015-12-09 19:00:00,20503.89,NSW1NSW1 +52052,2015-12-09 20:00:00,19483.84,NSW1NSW1 +52053,2015-12-09 21:00:00,18160.17,NSW1NSW1 +52054,2015-12-09 22:00:00,16923.98,NSW1NSW1 +52055,2015-12-09 23:00:00,15912.29,NSW1NSW1 +52056,2015-12-10 00:00:00,14961.61,NSW1NSW1 +52057,2015-12-10 01:00:00,14042.74,NSW1NSW1 +52058,2015-12-10 02:00:00,13051.630000000001,NSW1NSW1 +52059,2015-12-10 03:00:00,12851.560000000001,NSW1NSW1 +52060,2015-12-10 04:00:00,13217.98,NSW1NSW1 +52061,2015-12-10 05:00:00,14355.96,NSW1NSW1 +52062,2015-12-10 06:00:00,16172.11,NSW1NSW1 +52063,2015-12-10 07:00:00,17428.22,NSW1NSW1 +52064,2015-12-10 08:00:00,17937.13,NSW1NSW1 +52065,2015-12-10 09:00:00,18228.42,NSW1NSW1 +52066,2015-12-10 10:00:00,18433.260000000002,NSW1NSW1 +52067,2015-12-10 11:00:00,18484.66,NSW1NSW1 +52068,2015-12-10 12:00:00,18719.010000000002,NSW1NSW1 +52069,2015-12-10 13:00:00,19171.690000000002,NSW1NSW1 +52070,2015-12-10 14:00:00,19520.17,NSW1NSW1 +52071,2015-12-10 15:00:00,19816.3,NSW1NSW1 +52072,2015-12-10 16:00:00,20050.6,NSW1NSW1 +52073,2015-12-10 17:00:00,19749.64,NSW1NSW1 +52074,2015-12-10 18:00:00,19136.309999999998,NSW1NSW1 +52075,2015-12-10 19:00:00,18786.44,NSW1NSW1 +52076,2015-12-10 20:00:00,18440.18,NSW1NSW1 +52077,2015-12-10 21:00:00,17314.760000000002,NSW1NSW1 +52078,2015-12-10 22:00:00,16399.23,NSW1NSW1 +52079,2015-12-10 23:00:00,15582.86,NSW1NSW1 +52080,2015-12-11 00:00:00,14805.869999999999,NSW1NSW1 +52081,2015-12-11 01:00:00,13890.67,NSW1NSW1 +52082,2015-12-11 02:00:00,12943.279999999999,NSW1NSW1 +52083,2015-12-11 03:00:00,12673.84,NSW1NSW1 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01:00:00,13357.39,NSW1NSW1 +52106,2015-12-12 02:00:00,12489.08,NSW1NSW1 +52107,2015-12-12 03:00:00,12216.45,NSW1NSW1 +52108,2015-12-12 04:00:00,12302.24,NSW1NSW1 +52109,2015-12-12 05:00:00,12580.130000000001,NSW1NSW1 +52110,2015-12-12 06:00:00,13397.529999999999,NSW1NSW1 +52111,2015-12-12 07:00:00,14484.04,NSW1NSW1 +52112,2015-12-12 08:00:00,15428.66,NSW1NSW1 +52113,2015-12-12 09:00:00,15634.67,NSW1NSW1 +52114,2015-12-12 10:00:00,15458.54,NSW1NSW1 +52115,2015-12-12 11:00:00,15258.14,NSW1NSW1 +52116,2015-12-12 12:00:00,15000.970000000001,NSW1NSW1 +52117,2015-12-12 13:00:00,14763.47,NSW1NSW1 +52118,2015-12-12 14:00:00,14808.1,NSW1NSW1 +52119,2015-12-12 15:00:00,14991.53,NSW1NSW1 +52120,2015-12-12 16:00:00,14961.74,NSW1NSW1 +52121,2015-12-12 17:00:00,15093.37,NSW1NSW1 +52122,2015-12-12 18:00:00,14979.17,NSW1NSW1 +52123,2015-12-12 19:00:00,14947.439999999999,NSW1NSW1 +52124,2015-12-12 20:00:00,14924.01,NSW1NSW1 +52125,2015-12-12 21:00:00,14465.92,NSW1NSW1 +52126,2015-12-12 22:00:00,14239.56,NSW1NSW1 +52127,2015-12-12 23:00:00,13679.21,NSW1NSW1 +52128,2015-12-13 00:00:00,13082.39,NSW1NSW1 +52129,2015-12-13 01:00:00,12430.6,NSW1NSW1 +52130,2015-12-13 02:00:00,11704.91,NSW1NSW1 +52131,2015-12-13 03:00:00,11509.64,NSW1NSW1 +52132,2015-12-13 04:00:00,11585.89,NSW1NSW1 +52133,2015-12-13 05:00:00,11696.17,NSW1NSW1 +52134,2015-12-13 06:00:00,12254.95,NSW1NSW1 +52135,2015-12-13 07:00:00,13279.16,NSW1NSW1 +52136,2015-12-13 08:00:00,14200.15,NSW1NSW1 +52137,2015-12-13 09:00:00,14787.77,NSW1NSW1 +52138,2015-12-13 10:00:00,14638.48,NSW1NSW1 +52139,2015-12-13 11:00:00,14367.84,NSW1NSW1 +52140,2015-12-13 12:00:00,14183.09,NSW1NSW1 +52141,2015-12-13 13:00:00,14253.98,NSW1NSW1 +52142,2015-12-13 14:00:00,14570.5,NSW1NSW1 +52143,2015-12-13 15:00:00,14795.79,NSW1NSW1 +52144,2015-12-13 16:00:00,15024.86,NSW1NSW1 +52145,2015-12-13 17:00:00,15461.56,NSW1NSW1 +52146,2015-12-13 18:00:00,15671.55,NSW1NSW1 +52147,2015-12-13 19:00:00,15755.01,NSW1NSW1 +52148,2015-12-13 20:00:00,15860.34,NSW1NSW1 +52149,2015-12-13 21:00:00,15147.48,NSW1NSW1 +52150,2015-12-13 22:00:00,14576.79,NSW1NSW1 +52151,2015-12-13 23:00:00,13878.880000000001,NSW1NSW1 +52152,2015-12-14 00:00:00,13335.41,NSW1NSW1 +52153,2015-12-14 01:00:00,12769.71,NSW1NSW1 +52154,2015-12-14 02:00:00,12108.470000000001,NSW1NSW1 +52155,2015-12-14 03:00:00,12021.81,NSW1NSW1 +52156,2015-12-14 04:00:00,12468.779999999999,NSW1NSW1 +52157,2015-12-14 05:00:00,13567.310000000001,NSW1NSW1 +52158,2015-12-14 06:00:00,15340.74,NSW1NSW1 +52159,2015-12-14 07:00:00,16706.879999999997,NSW1NSW1 +52160,2015-12-14 08:00:00,17299.39,NSW1NSW1 +52161,2015-12-14 09:00:00,17779.22,NSW1NSW1 +52162,2015-12-14 10:00:00,18144.489999999998,NSW1NSW1 +52163,2015-12-14 11:00:00,18505.96,NSW1NSW1 +52164,2015-12-14 12:00:00,18988.010000000002,NSW1NSW1 +52165,2015-12-14 13:00:00,19459.18,NSW1NSW1 +52166,2015-12-14 14:00:00,19936.16,NSW1NSW1 +52167,2015-12-14 15:00:00,20481.59,NSW1NSW1 +52168,2015-12-14 16:00:00,20642.16,NSW1NSW1 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11:00:00,17893.56,NSW1NSW1 +52212,2015-12-16 12:00:00,17631.5,NSW1NSW1 +52213,2015-12-16 13:00:00,17442.42,NSW1NSW1 +52214,2015-12-16 14:00:00,17202.42,NSW1NSW1 +52215,2015-12-16 15:00:00,17013.82,NSW1NSW1 +52216,2015-12-16 16:00:00,17027.129999999997,NSW1NSW1 +52217,2015-12-16 17:00:00,16975.739999999998,NSW1NSW1 +52218,2015-12-16 18:00:00,16650.21,NSW1NSW1 +52219,2015-12-16 19:00:00,16435.47,NSW1NSW1 +52220,2015-12-16 20:00:00,16414.68,NSW1NSW1 +52221,2015-12-16 21:00:00,15762.41,NSW1NSW1 +52222,2015-12-16 22:00:00,15285.77,NSW1NSW1 +52223,2015-12-16 23:00:00,14799.91,NSW1NSW1 +52224,2015-12-17 00:00:00,14158.73,NSW1NSW1 +52225,2015-12-17 01:00:00,13143.33,NSW1NSW1 +52226,2015-12-17 02:00:00,12289.14,NSW1NSW1 +52227,2015-12-17 03:00:00,12107.32,NSW1NSW1 +52228,2015-12-17 04:00:00,12493.85,NSW1NSW1 +52229,2015-12-17 05:00:00,13572.73,NSW1NSW1 +52230,2015-12-17 06:00:00,15094.380000000001,NSW1NSW1 +52231,2015-12-17 07:00:00,16322.78,NSW1NSW1 +52232,2015-12-17 08:00:00,17063.550000000003,NSW1NSW1 +52233,2015-12-17 09:00:00,17372.64,NSW1NSW1 +52234,2015-12-17 10:00:00,17588.37,NSW1NSW1 +52235,2015-12-17 11:00:00,17785.53,NSW1NSW1 +52236,2015-12-17 12:00:00,17856.86,NSW1NSW1 +52237,2015-12-17 13:00:00,18052.86,NSW1NSW1 +52238,2015-12-17 14:00:00,18316.36,NSW1NSW1 +52239,2015-12-17 15:00:00,18567.67,NSW1NSW1 +52240,2015-12-17 16:00:00,18745.02,NSW1NSW1 +52241,2015-12-17 17:00:00,18736.300000000003,NSW1NSW1 +52242,2015-12-17 18:00:00,18338.84,NSW1NSW1 +52243,2015-12-17 19:00:00,17918.45,NSW1NSW1 +52244,2015-12-17 20:00:00,17690.5,NSW1NSW1 +52245,2015-12-17 21:00:00,16877.65,NSW1NSW1 +52246,2015-12-17 22:00:00,16250.779999999999,NSW1NSW1 +52247,2015-12-17 23:00:00,15508.83,NSW1NSW1 +52248,2015-12-18 00:00:00,14701.16,NSW1NSW1 +52249,2015-12-18 01:00:00,13777.37,NSW1NSW1 +52250,2015-12-18 02:00:00,12849.34,NSW1NSW1 +52251,2015-12-18 03:00:00,12567.99,NSW1NSW1 +52252,2015-12-18 04:00:00,12848.08,NSW1NSW1 +52253,2015-12-18 05:00:00,13804.759999999998,NSW1NSW1 +52254,2015-12-18 06:00:00,15449.82,NSW1NSW1 +52255,2015-12-18 07:00:00,16816.949999999997,NSW1NSW1 +52256,2015-12-18 08:00:00,17661.8,NSW1NSW1 +52257,2015-12-18 09:00:00,18288.75,NSW1NSW1 +52258,2015-12-18 10:00:00,18744.47,NSW1NSW1 +52259,2015-12-18 11:00:00,19094.71,NSW1NSW1 +52260,2015-12-18 12:00:00,19454.61,NSW1NSW1 +52261,2015-12-18 13:00:00,19972.489999999998,NSW1NSW1 +52262,2015-12-18 14:00:00,20513.870000000003,NSW1NSW1 +52263,2015-12-18 15:00:00,21045.019999999997,NSW1NSW1 +52264,2015-12-18 16:00:00,21264.91,NSW1NSW1 +52265,2015-12-18 17:00:00,20976.65,NSW1NSW1 +52266,2015-12-18 18:00:00,20091.510000000002,NSW1NSW1 +52267,2015-12-18 19:00:00,19325.99,NSW1NSW1 +52268,2015-12-18 20:00:00,18732.5,NSW1NSW1 +52269,2015-12-18 21:00:00,17747.15,NSW1NSW1 +52270,2015-12-18 22:00:00,17030.25,NSW1NSW1 +52271,2015-12-18 23:00:00,16021.720000000001,NSW1NSW1 +52272,2015-12-19 00:00:00,15102.65,NSW1NSW1 +52273,2015-12-19 01:00:00,13921.349999999999,NSW1NSW1 +52274,2015-12-19 02:00:00,12923.73,NSW1NSW1 +52275,2015-12-19 03:00:00,12522.07,NSW1NSW1 +52276,2015-12-19 04:00:00,12446.71,NSW1NSW1 +52277,2015-12-19 05:00:00,12757.66,NSW1NSW1 +52278,2015-12-19 06:00:00,13660.96,NSW1NSW1 +52279,2015-12-19 07:00:00,15090.85,NSW1NSW1 +52280,2015-12-19 08:00:00,16384.58,NSW1NSW1 +52281,2015-12-19 09:00:00,17362.129999999997,NSW1NSW1 +52282,2015-12-19 10:00:00,17936.33,NSW1NSW1 +52283,2015-12-19 11:00:00,18693.18,NSW1NSW1 +52284,2015-12-19 12:00:00,19463.59,NSW1NSW1 +52285,2015-12-19 13:00:00,20061.37,NSW1NSW1 +52286,2015-12-19 14:00:00,20366.09,NSW1NSW1 +52287,2015-12-19 15:00:00,20710.489999999998,NSW1NSW1 +52288,2015-12-19 16:00:00,20778.230000000003,NSW1NSW1 +52289,2015-12-19 17:00:00,20452.61,NSW1NSW1 +52290,2015-12-19 18:00:00,19509.83,NSW1NSW1 +52291,2015-12-19 19:00:00,18577.989999999998,NSW1NSW1 +52292,2015-12-19 20:00:00,18132.87,NSW1NSW1 +52293,2015-12-19 21:00:00,17151.83,NSW1NSW1 +52294,2015-12-19 22:00:00,16272.599999999999,NSW1NSW1 +52295,2015-12-19 23:00:00,15092.14,NSW1NSW1 +52296,2015-12-20 00:00:00,14140.599999999999,NSW1NSW1 +52297,2015-12-20 01:00:00,13409.6,NSW1NSW1 +52298,2015-12-20 02:00:00,12644.91,NSW1NSW1 +52299,2015-12-20 03:00:00,12380.35,NSW1NSW1 +52300,2015-12-20 04:00:00,12281.7,NSW1NSW1 +52301,2015-12-20 05:00:00,12276.14,NSW1NSW1 +52302,2015-12-20 06:00:00,12970.32,NSW1NSW1 +52303,2015-12-20 07:00:00,14071.91,NSW1NSW1 +52304,2015-12-20 08:00:00,15225.65,NSW1NSW1 +52305,2015-12-20 09:00:00,16057.77,NSW1NSW1 +52306,2015-12-20 10:00:00,16801.879999999997,NSW1NSW1 +52307,2015-12-20 11:00:00,17718.45,NSW1NSW1 +52308,2015-12-20 12:00:00,18688.43,NSW1NSW1 +52309,2015-12-20 13:00:00,19540.66,NSW1NSW1 +52310,2015-12-20 14:00:00,20210.629999999997,NSW1NSW1 +52311,2015-12-20 15:00:00,20970.510000000002,NSW1NSW1 +52312,2015-12-20 16:00:00,21490.809999999998,NSW1NSW1 +52313,2015-12-20 17:00:00,21843.72,NSW1NSW1 +52314,2015-12-20 18:00:00,21431.86,NSW1NSW1 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16:00:00,18464.18,NSW1NSW1 +52337,2015-12-21 17:00:00,18176.89,NSW1NSW1 +52338,2015-12-21 18:00:00,17600.43,NSW1NSW1 +52339,2015-12-21 19:00:00,17184.0,NSW1NSW1 +52340,2015-12-21 20:00:00,16599.72,NSW1NSW1 +52341,2015-12-21 21:00:00,15850.58,NSW1NSW1 +52342,2015-12-21 22:00:00,15240.89,NSW1NSW1 +52343,2015-12-21 23:00:00,14798.82,NSW1NSW1 +52344,2015-12-22 00:00:00,14176.38,NSW1NSW1 +52345,2015-12-22 01:00:00,13222.369999999999,NSW1NSW1 +52346,2015-12-22 02:00:00,12333.76,NSW1NSW1 +52347,2015-12-22 03:00:00,12049.56,NSW1NSW1 +52348,2015-12-22 04:00:00,12356.77,NSW1NSW1 +52349,2015-12-22 05:00:00,13399.23,NSW1NSW1 +52350,2015-12-22 06:00:00,14823.29,NSW1NSW1 +52351,2015-12-22 07:00:00,16060.8,NSW1NSW1 +52352,2015-12-22 08:00:00,16770.08,NSW1NSW1 +52353,2015-12-22 09:00:00,17023.199999999997,NSW1NSW1 +52354,2015-12-22 10:00:00,17083.98,NSW1NSW1 +52355,2015-12-22 11:00:00,17152.199999999997,NSW1NSW1 +52356,2015-12-22 12:00:00,16951.48,NSW1NSW1 +52357,2015-12-22 13:00:00,16741.43,NSW1NSW1 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08:00:00,15472.189999999999,NSW1NSW1 +52401,2015-12-24 09:00:00,15765.439999999999,NSW1NSW1 +52402,2015-12-24 10:00:00,15858.84,NSW1NSW1 +52403,2015-12-24 11:00:00,15604.25,NSW1NSW1 +52404,2015-12-24 12:00:00,15321.98,NSW1NSW1 +52405,2015-12-24 13:00:00,15068.900000000001,NSW1NSW1 +52406,2015-12-24 14:00:00,15098.3,NSW1NSW1 +52407,2015-12-24 15:00:00,15315.01,NSW1NSW1 +52408,2015-12-24 16:00:00,15509.14,NSW1NSW1 +52409,2015-12-24 17:00:00,15316.89,NSW1NSW1 +52410,2015-12-24 18:00:00,14859.32,NSW1NSW1 +52411,2015-12-24 19:00:00,14564.68,NSW1NSW1 +52412,2015-12-24 20:00:00,14664.029999999999,NSW1NSW1 +52413,2015-12-24 21:00:00,14548.23,NSW1NSW1 +52414,2015-12-24 22:00:00,14467.1,NSW1NSW1 +52415,2015-12-24 23:00:00,14077.08,NSW1NSW1 +52416,2015-12-25 00:00:00,13396.09,NSW1NSW1 +52417,2015-12-25 01:00:00,12407.14,NSW1NSW1 +52418,2015-12-25 02:00:00,11309.880000000001,NSW1NSW1 +52419,2015-12-25 03:00:00,10829.029999999999,NSW1NSW1 +52420,2015-12-25 04:00:00,10770.84,NSW1NSW1 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23:00:00,13384.5,NSW1NSW1 +52464,2015-12-27 00:00:00,12733.310000000001,NSW1NSW1 +52465,2015-12-27 01:00:00,11996.349999999999,NSW1NSW1 +52466,2015-12-27 02:00:00,11206.68,NSW1NSW1 +52467,2015-12-27 03:00:00,10929.09,NSW1NSW1 +52468,2015-12-27 04:00:00,10929.220000000001,NSW1NSW1 +52469,2015-12-27 05:00:00,11076.17,NSW1NSW1 +52470,2015-12-27 06:00:00,11564.41,NSW1NSW1 +52471,2015-12-27 07:00:00,12498.369999999999,NSW1NSW1 +52472,2015-12-27 08:00:00,13315.25,NSW1NSW1 +52473,2015-12-27 09:00:00,13718.74,NSW1NSW1 +52474,2015-12-27 10:00:00,13602.26,NSW1NSW1 +52475,2015-12-27 11:00:00,13383.96,NSW1NSW1 +52476,2015-12-27 12:00:00,12985.07,NSW1NSW1 +52477,2015-12-27 13:00:00,12776.25,NSW1NSW1 +52478,2015-12-27 14:00:00,12749.98,NSW1NSW1 +52479,2015-12-27 15:00:00,12985.01,NSW1NSW1 +52480,2015-12-27 16:00:00,13089.47,NSW1NSW1 +52481,2015-12-27 17:00:00,13297.14,NSW1NSW1 +52482,2015-12-27 18:00:00,13386.7,NSW1NSW1 +52483,2015-12-27 19:00:00,13472.3,NSW1NSW1 +52484,2015-12-27 20:00:00,13767.53,NSW1NSW1 +52485,2015-12-27 21:00:00,13394.26,NSW1NSW1 +52486,2015-12-27 22:00:00,13061.73,NSW1NSW1 +52487,2015-12-27 23:00:00,12607.119999999999,NSW1NSW1 +52488,2015-12-28 00:00:00,12143.64,NSW1NSW1 +52489,2015-12-28 01:00:00,11507.57,NSW1NSW1 +52490,2015-12-28 02:00:00,10903.33,NSW1NSW1 +52491,2015-12-28 03:00:00,10726.25,NSW1NSW1 +52492,2015-12-28 04:00:00,10865.57,NSW1NSW1 +52493,2015-12-28 05:00:00,11024.99,NSW1NSW1 +52494,2015-12-28 06:00:00,11543.49,NSW1NSW1 +52495,2015-12-28 07:00:00,12289.830000000002,NSW1NSW1 +52496,2015-12-28 08:00:00,12932.099999999999,NSW1NSW1 +52497,2015-12-28 09:00:00,13501.59,NSW1NSW1 +52498,2015-12-28 10:00:00,13500.220000000001,NSW1NSW1 +52499,2015-12-28 11:00:00,13274.57,NSW1NSW1 +52500,2015-12-28 12:00:00,13077.91,NSW1NSW1 +52501,2015-12-28 13:00:00,12988.79,NSW1NSW1 +52502,2015-12-28 14:00:00,13070.7,NSW1NSW1 +52503,2015-12-28 15:00:00,13128.42,NSW1NSW1 +52504,2015-12-28 16:00:00,13535.060000000001,NSW1NSW1 +52505,2015-12-28 17:00:00,13933.46,NSW1NSW1 +52506,2015-12-28 18:00:00,13915.68,NSW1NSW1 +52507,2015-12-28 19:00:00,13776.220000000001,NSW1NSW1 +52508,2015-12-28 20:00:00,13977.73,NSW1NSW1 +52509,2015-12-28 21:00:00,13674.2,NSW1NSW1 +52510,2015-12-28 22:00:00,13642.630000000001,NSW1NSW1 +52511,2015-12-28 23:00:00,13401.48,NSW1NSW1 +52512,2015-12-29 00:00:00,13060.76,NSW1NSW1 +52513,2015-12-29 01:00:00,12231.869999999999,NSW1NSW1 +52514,2015-12-29 02:00:00,11416.79,NSW1NSW1 +52515,2015-12-29 03:00:00,11072.92,NSW1NSW1 +52516,2015-12-29 04:00:00,11212.04,NSW1NSW1 +52517,2015-12-29 05:00:00,11690.09,NSW1NSW1 +52518,2015-12-29 06:00:00,12573.05,NSW1NSW1 +52519,2015-12-29 07:00:00,13468.46,NSW1NSW1 +52520,2015-12-29 08:00:00,14297.22,NSW1NSW1 +52521,2015-12-29 09:00:00,14540.95,NSW1NSW1 +52522,2015-12-29 10:00:00,14484.64,NSW1NSW1 +52523,2015-12-29 11:00:00,14286.060000000001,NSW1NSW1 +52524,2015-12-29 12:00:00,14063.16,NSW1NSW1 +52525,2015-12-29 13:00:00,14089.38,NSW1NSW1 +52526,2015-12-29 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10:00:00,16897.010000000002,NSW1NSW1 +71747,2018-03-09 11:00:00,16771.5,NSW1NSW1 +71748,2018-03-09 12:00:00,16667.73,NSW1NSW1 +71749,2018-03-09 13:00:00,16579.61,NSW1NSW1 +71750,2018-03-09 14:00:00,16557.71,NSW1NSW1 +71751,2018-03-09 15:00:00,16803.760000000002,NSW1NSW1 +71752,2018-03-09 16:00:00,17084.85,NSW1NSW1 +71753,2018-03-09 17:00:00,16833.440000000002,NSW1NSW1 +71754,2018-03-09 18:00:00,16510.97,NSW1NSW1 +71755,2018-03-09 19:00:00,16530.04,NSW1NSW1 +71756,2018-03-09 20:00:00,15975.029999999999,NSW1NSW1 +71757,2018-03-09 21:00:00,15310.689999999999,NSW1NSW1 +71758,2018-03-09 22:00:00,15095.369999999999,NSW1NSW1 +71759,2018-03-09 23:00:00,14755.119999999999,NSW1NSW1 +71760,2018-03-10 00:00:00,14062.33,NSW1NSW1 +71761,2018-03-10 01:00:00,13296.1,NSW1NSW1 +71762,2018-03-10 02:00:00,12424.970000000001,NSW1NSW1 +71763,2018-03-10 03:00:00,12119.34,NSW1NSW1 +71764,2018-03-10 04:00:00,12174.41,NSW1NSW1 +71765,2018-03-10 05:00:00,12608.08,NSW1NSW1 +71766,2018-03-10 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21:00:00,15941.5,NSW1NSW1 +71830,2018-03-12 22:00:00,15445.02,NSW1NSW1 +71831,2018-03-12 23:00:00,14967.26,NSW1NSW1 +71832,2018-03-13 00:00:00,14342.45,NSW1NSW1 +71833,2018-03-13 01:00:00,13513.89,NSW1NSW1 +71834,2018-03-13 02:00:00,12654.26,NSW1NSW1 +71835,2018-03-13 03:00:00,12461.970000000001,NSW1NSW1 +71836,2018-03-13 04:00:00,12750.58,NSW1NSW1 +71837,2018-03-13 05:00:00,14084.0,NSW1NSW1 +71838,2018-03-13 06:00:00,15988.560000000001,NSW1NSW1 +71839,2018-03-13 07:00:00,16932.949999999997,NSW1NSW1 +71840,2018-03-13 08:00:00,17162.86,NSW1NSW1 +71841,2018-03-13 09:00:00,17249.53,NSW1NSW1 +71842,2018-03-13 10:00:00,17159.86,NSW1NSW1 +71843,2018-03-13 11:00:00,17139.75,NSW1NSW1 +71844,2018-03-13 12:00:00,17017.19,NSW1NSW1 +71845,2018-03-13 13:00:00,16982.739999999998,NSW1NSW1 +71846,2018-03-13 14:00:00,16949.35,NSW1NSW1 +71847,2018-03-13 15:00:00,17144.78,NSW1NSW1 +71848,2018-03-13 16:00:00,17482.199999999997,NSW1NSW1 +71849,2018-03-13 17:00:00,17535.82,NSW1NSW1 +71850,2018-03-13 18:00:00,17428.67,NSW1NSW1 +71851,2018-03-13 19:00:00,17161.56,NSW1NSW1 +71852,2018-03-13 20:00:00,16447.28,NSW1NSW1 +71853,2018-03-13 21:00:00,15667.79,NSW1NSW1 +71854,2018-03-13 22:00:00,15226.1,NSW1NSW1 +71855,2018-03-13 23:00:00,14836.43,NSW1NSW1 +71856,2018-03-14 00:00:00,14199.759999999998,NSW1NSW1 +71857,2018-03-14 01:00:00,13450.869999999999,NSW1NSW1 +71858,2018-03-14 02:00:00,12515.95,NSW1NSW1 +71859,2018-03-14 03:00:00,12271.33,NSW1NSW1 +71860,2018-03-14 04:00:00,12775.630000000001,NSW1NSW1 +71861,2018-03-14 05:00:00,14070.619999999999,NSW1NSW1 +71862,2018-03-14 06:00:00,15987.34,NSW1NSW1 +71863,2018-03-14 07:00:00,16958.98,NSW1NSW1 +71864,2018-03-14 08:00:00,17014.59,NSW1NSW1 +71865,2018-03-14 09:00:00,17091.6,NSW1NSW1 +71866,2018-03-14 10:00:00,17186.05,NSW1NSW1 +71867,2018-03-14 11:00:00,17001.59,NSW1NSW1 +71868,2018-03-14 12:00:00,17047.02,NSW1NSW1 +71869,2018-03-14 13:00:00,17358.1,NSW1NSW1 +71870,2018-03-14 14:00:00,17650.4,NSW1NSW1 +71871,2018-03-14 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21:00:00,20813.22,NSW1NSW1 +74758,2018-07-12 22:00:00,19721.949999999997,NSW1NSW1 +74759,2018-07-12 23:00:00,18704.53,NSW1NSW1 +74760,2018-07-13 00:00:00,17855.510000000002,NSW1NSW1 +74761,2018-07-13 01:00:00,16936.449999999997,NSW1NSW1 +74762,2018-07-13 02:00:00,15992.66,NSW1NSW1 +74763,2018-07-13 03:00:00,14904.650000000001,NSW1NSW1 +74764,2018-07-13 04:00:00,14518.74,NSW1NSW1 +74765,2018-07-13 05:00:00,15125.23,NSW1NSW1 +74766,2018-07-13 06:00:00,17061.09,NSW1NSW1 +74767,2018-07-13 07:00:00,19583.15,NSW1NSW1 +74768,2018-07-13 08:00:00,20966.99,NSW1NSW1 +74769,2018-07-13 09:00:00,20591.81,NSW1NSW1 +74770,2018-07-13 10:00:00,19292.989999999998,NSW1NSW1 +74771,2018-07-13 11:00:00,18104.800000000003,NSW1NSW1 +74772,2018-07-13 12:00:00,17115.34,NSW1NSW1 +74773,2018-07-13 13:00:00,16630.05,NSW1NSW1 +74774,2018-07-13 14:00:00,16277.51,NSW1NSW1 +74775,2018-07-13 15:00:00,16564.809999999998,NSW1NSW1 +74776,2018-07-13 16:00:00,17617.39,NSW1NSW1 +74777,2018-07-13 17:00:00,19749.91,NSW1NSW1 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09:00:00,21613.949999999997,NSW1NSW1 +74842,2018-07-16 10:00:00,20506.66,NSW1NSW1 +74843,2018-07-16 11:00:00,19238.04,NSW1NSW1 +74844,2018-07-16 12:00:00,18368.08,NSW1NSW1 +74845,2018-07-16 13:00:00,17746.019999999997,NSW1NSW1 +74846,2018-07-16 14:00:00,17664.260000000002,NSW1NSW1 +74847,2018-07-16 15:00:00,18023.72,NSW1NSW1 +74848,2018-07-16 16:00:00,19123.239999999998,NSW1NSW1 +74849,2018-07-16 17:00:00,21294.36,NSW1NSW1 +74850,2018-07-16 18:00:00,23691.86,NSW1NSW1 +74851,2018-07-16 19:00:00,23622.83,NSW1NSW1 +74852,2018-07-16 20:00:00,22770.52,NSW1NSW1 +74853,2018-07-16 21:00:00,21644.72,NSW1NSW1 +74854,2018-07-16 22:00:00,20197.739999999998,NSW1NSW1 +74855,2018-07-16 23:00:00,18769.519999999997,NSW1NSW1 +74856,2018-07-17 00:00:00,17926.65,NSW1NSW1 +74857,2018-07-17 01:00:00,17002.75,NSW1NSW1 +74858,2018-07-17 02:00:00,16044.58,NSW1NSW1 +74859,2018-07-17 03:00:00,14974.21,NSW1NSW1 +74860,2018-07-17 04:00:00,14633.53,NSW1NSW1 +74861,2018-07-17 05:00:00,15219.71,NSW1NSW1 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22:00:00,15178.41,NSW1NSW1 +77711,2018-11-12 23:00:00,14896.400000000001,NSW1NSW1 +77712,2018-11-13 00:00:00,14271.7,NSW1NSW1 +77713,2018-11-13 01:00:00,13515.99,NSW1NSW1 +77714,2018-11-13 02:00:00,12665.82,NSW1NSW1 +77715,2018-11-13 03:00:00,12447.99,NSW1NSW1 +77716,2018-11-13 04:00:00,12777.73,NSW1NSW1 +77717,2018-11-13 05:00:00,13820.689999999999,NSW1NSW1 +77718,2018-11-13 06:00:00,15274.83,NSW1NSW1 +77719,2018-11-13 07:00:00,15894.32,NSW1NSW1 +77720,2018-11-13 08:00:00,15850.0,NSW1NSW1 +77721,2018-11-13 09:00:00,15858.849999999999,NSW1NSW1 +77722,2018-11-13 10:00:00,16036.59,NSW1NSW1 +77723,2018-11-13 11:00:00,15927.189999999999,NSW1NSW1 +77724,2018-11-13 12:00:00,15934.880000000001,NSW1NSW1 +77725,2018-11-13 13:00:00,16220.93,NSW1NSW1 +77726,2018-11-13 14:00:00,16406.940000000002,NSW1NSW1 +77727,2018-11-13 15:00:00,16936.86,NSW1NSW1 +77728,2018-11-13 16:00:00,17396.96,NSW1NSW1 +77729,2018-11-13 17:00:00,17398.86,NSW1NSW1 +77730,2018-11-13 18:00:00,17263.309999999998,NSW1NSW1 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16:00:00,16672.45,NSW1NSW1 +77753,2018-11-14 17:00:00,16927.41,NSW1NSW1 +77754,2018-11-14 18:00:00,16810.309999999998,NSW1NSW1 +77755,2018-11-14 19:00:00,16744.89,NSW1NSW1 +77756,2018-11-14 20:00:00,16211.07,NSW1NSW1 +77757,2018-11-14 21:00:00,15556.869999999999,NSW1NSW1 +77758,2018-11-14 22:00:00,15175.23,NSW1NSW1 +77759,2018-11-14 23:00:00,14673.91,NSW1NSW1 +77760,2018-11-15 00:00:00,14127.08,NSW1NSW1 +77761,2018-11-15 01:00:00,13363.98,NSW1NSW1 +77762,2018-11-15 02:00:00,12445.44,NSW1NSW1 +77763,2018-11-15 03:00:00,12159.74,NSW1NSW1 +77764,2018-11-15 04:00:00,12540.18,NSW1NSW1 +77765,2018-11-15 05:00:00,13671.34,NSW1NSW1 +77766,2018-11-15 06:00:00,15231.77,NSW1NSW1 +77767,2018-11-15 07:00:00,15904.04,NSW1NSW1 +77768,2018-11-15 08:00:00,15856.03,NSW1NSW1 +77769,2018-11-15 09:00:00,16077.39,NSW1NSW1 +77770,2018-11-15 10:00:00,16076.52,NSW1NSW1 +77771,2018-11-15 11:00:00,16063.96,NSW1NSW1 +77772,2018-11-15 12:00:00,15955.36,NSW1NSW1 +77773,2018-11-15 13:00:00,16044.49,NSW1NSW1 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08:00:00,14280.779999999999,NSW1NSW1 +77817,2018-11-17 09:00:00,14450.57,NSW1NSW1 +77818,2018-11-17 10:00:00,14210.52,NSW1NSW1 +77819,2018-11-17 11:00:00,13962.25,NSW1NSW1 +77820,2018-11-17 12:00:00,13704.17,NSW1NSW1 +77821,2018-11-17 13:00:00,13426.21,NSW1NSW1 +77822,2018-11-17 14:00:00,13411.59,NSW1NSW1 +77823,2018-11-17 15:00:00,13666.310000000001,NSW1NSW1 +77824,2018-11-17 16:00:00,14158.66,NSW1NSW1 +77825,2018-11-17 17:00:00,14675.75,NSW1NSW1 +77826,2018-11-17 18:00:00,14881.279999999999,NSW1NSW1 +77827,2018-11-17 19:00:00,14949.119999999999,NSW1NSW1 +77828,2018-11-17 20:00:00,14607.220000000001,NSW1NSW1 +77829,2018-11-17 21:00:00,14209.49,NSW1NSW1 +77830,2018-11-17 22:00:00,14087.73,NSW1NSW1 +77831,2018-11-17 23:00:00,13726.18,NSW1NSW1 +77832,2018-11-18 00:00:00,13250.82,NSW1NSW1 +77833,2018-11-18 01:00:00,12516.66,NSW1NSW1 +77834,2018-11-18 02:00:00,11736.76,NSW1NSW1 +77835,2018-11-18 03:00:00,11517.35,NSW1NSW1 +77836,2018-11-18 04:00:00,11561.04,NSW1NSW1 +77837,2018-11-18 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14:00:00,12481.580000000002,NSW1NSW1 +95031,2020-11-03 15:00:00,13273.779999999999,NSW1NSW1 +95032,2020-11-03 16:00:00,14548.73,NSW1NSW1 +95033,2020-11-03 17:00:00,15772.84,NSW1NSW1 +95034,2020-11-03 18:00:00,16197.01,NSW1NSW1 +95035,2020-11-03 19:00:00,16244.76,NSW1NSW1 +95036,2020-11-03 20:00:00,15731.94,NSW1NSW1 +95037,2020-11-03 21:00:00,15028.529999999999,NSW1NSW1 +95038,2020-11-03 22:00:00,14721.77,NSW1NSW1 +95039,2020-11-03 23:00:00,14462.48,NSW1NSW1 +95040,2020-11-04 00:00:00,13949.029999999999,NSW1NSW1 +95041,2020-11-04 01:00:00,13080.689999999999,NSW1NSW1 +95042,2020-11-04 02:00:00,12233.4,NSW1NSW1 +95043,2020-11-04 03:00:00,11865.84,NSW1NSW1 +95044,2020-11-04 04:00:00,12300.51,NSW1NSW1 +95045,2020-11-04 05:00:00,13339.25,NSW1NSW1 +95046,2020-11-04 06:00:00,14424.119999999999,NSW1NSW1 +95047,2020-11-04 07:00:00,14560.189999999999,NSW1NSW1 +95048,2020-11-04 08:00:00,14037.96,NSW1NSW1 +95049,2020-11-04 09:00:00,13083.68,NSW1NSW1 +95050,2020-11-04 10:00:00,12614.07,NSW1NSW1 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07:00:00,15542.619999999999,NSW1NSW1 +95072,2020-11-05 08:00:00,15695.099999999999,NSW1NSW1 +95073,2020-11-05 09:00:00,15834.93,NSW1NSW1 +95074,2020-11-05 10:00:00,15830.66,NSW1NSW1 +95075,2020-11-05 11:00:00,15670.08,NSW1NSW1 +95076,2020-11-05 12:00:00,15516.15,NSW1NSW1 +95077,2020-11-05 13:00:00,15288.82,NSW1NSW1 +95078,2020-11-05 14:00:00,15451.43,NSW1NSW1 +95079,2020-11-05 15:00:00,15729.560000000001,NSW1NSW1 +95080,2020-11-05 16:00:00,16366.349999999999,NSW1NSW1 +95081,2020-11-05 17:00:00,17459.88,NSW1NSW1 +95082,2020-11-05 18:00:00,17728.71,NSW1NSW1 +95083,2020-11-05 19:00:00,17490.95,NSW1NSW1 +95084,2020-11-05 20:00:00,16767.98,NSW1NSW1 +95085,2020-11-05 21:00:00,15836.23,NSW1NSW1 +95086,2020-11-05 22:00:00,15228.05,NSW1NSW1 +95087,2020-11-05 23:00:00,14818.93,NSW1NSW1 +95088,2020-11-06 00:00:00,14338.15,NSW1NSW1 +95089,2020-11-06 01:00:00,13502.11,NSW1NSW1 +95090,2020-11-06 02:00:00,12556.029999999999,NSW1NSW1 +95091,2020-11-06 03:00:00,12278.3,NSW1NSW1 +95092,2020-11-06 04:00:00,12582.43,NSW1NSW1 +95093,2020-11-06 05:00:00,13731.89,NSW1NSW1 +95094,2020-11-06 06:00:00,15117.68,NSW1NSW1 +95095,2020-11-06 07:00:00,15329.3,NSW1NSW1 +95096,2020-11-06 08:00:00,14405.1,NSW1NSW1 +95097,2020-11-06 09:00:00,13696.48,NSW1NSW1 +95098,2020-11-06 10:00:00,13006.39,NSW1NSW1 +95099,2020-11-06 11:00:00,12556.779999999999,NSW1NSW1 +95100,2020-11-06 12:00:00,12260.03,NSW1NSW1 +95101,2020-11-06 13:00:00,11984.69,NSW1NSW1 +95102,2020-11-06 14:00:00,12041.32,NSW1NSW1 +95103,2020-11-06 15:00:00,12657.48,NSW1NSW1 +95104,2020-11-06 16:00:00,13744.28,NSW1NSW1 +95105,2020-11-06 17:00:00,14860.48,NSW1NSW1 +95106,2020-11-06 18:00:00,15546.83,NSW1NSW1 +95107,2020-11-06 19:00:00,15816.759999999998,NSW1NSW1 +95108,2020-11-06 20:00:00,15500.130000000001,NSW1NSW1 +95109,2020-11-06 21:00:00,14934.71,NSW1NSW1 +95110,2020-11-06 22:00:00,14788.720000000001,NSW1NSW1 +95111,2020-11-06 23:00:00,14481.55,NSW1NSW1 +95112,2020-11-07 00:00:00,13980.830000000002,NSW1NSW1 +95113,2020-11-07 01:00:00,13236.8,NSW1NSW1 +95114,2020-11-07 02:00:00,12311.68,NSW1NSW1 +95115,2020-11-07 03:00:00,11846.47,NSW1NSW1 +95116,2020-11-07 04:00:00,11911.91,NSW1NSW1 +95117,2020-11-07 05:00:00,12315.86,NSW1NSW1 +95118,2020-11-07 06:00:00,12868.3,NSW1NSW1 +95119,2020-11-07 07:00:00,13172.41,NSW1NSW1 +95120,2020-11-07 08:00:00,12719.720000000001,NSW1NSW1 +95121,2020-11-07 09:00:00,12373.66,NSW1NSW1 +95122,2020-11-07 10:00:00,11961.92,NSW1NSW1 +95123,2020-11-07 11:00:00,11922.259999999998,NSW1NSW1 +95124,2020-11-07 12:00:00,11412.58,NSW1NSW1 +95125,2020-11-07 13:00:00,11238.61,NSW1NSW1 +95126,2020-11-07 14:00:00,11391.61,NSW1NSW1 +95127,2020-11-07 15:00:00,12079.43,NSW1NSW1 +95128,2020-11-07 16:00:00,13129.11,NSW1NSW1 +95129,2020-11-07 17:00:00,14327.84,NSW1NSW1 +95130,2020-11-07 18:00:00,14995.529999999999,NSW1NSW1 +95131,2020-11-07 19:00:00,15161.529999999999,NSW1NSW1 +95132,2020-11-07 20:00:00,14792.3,NSW1NSW1 +95133,2020-11-07 21:00:00,14308.279999999999,NSW1NSW1 +95134,2020-11-07 22:00:00,14027.08,NSW1NSW1 +95135,2020-11-07 23:00:00,13583.630000000001,NSW1NSW1 +95136,2020-11-08 00:00:00,13059.08,NSW1NSW1 +95137,2020-11-08 01:00:00,12227.33,NSW1NSW1 +95138,2020-11-08 02:00:00,11503.68,NSW1NSW1 +95139,2020-11-08 03:00:00,11316.6,NSW1NSW1 +95140,2020-11-08 04:00:00,11316.93,NSW1NSW1 +95141,2020-11-08 05:00:00,11525.75,NSW1NSW1 +95142,2020-11-08 06:00:00,11782.119999999999,NSW1NSW1 +95143,2020-11-08 07:00:00,12016.650000000001,NSW1NSW1 +95144,2020-11-08 08:00:00,12075.060000000001,NSW1NSW1 +95145,2020-11-08 09:00:00,11987.08,NSW1NSW1 +95146,2020-11-08 10:00:00,11675.3,NSW1NSW1 +95147,2020-11-08 11:00:00,11262.119999999999,NSW1NSW1 +95148,2020-11-08 12:00:00,11036.029999999999,NSW1NSW1 +95149,2020-11-08 13:00:00,11000.83,NSW1NSW1 +95150,2020-11-08 14:00:00,11076.11,NSW1NSW1 +95151,2020-11-08 15:00:00,11630.060000000001,NSW1NSW1 +95152,2020-11-08 16:00:00,12676.32,NSW1NSW1 +95153,2020-11-08 17:00:00,14153.52,NSW1NSW1 +95154,2020-11-08 18:00:00,14951.18,NSW1NSW1 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14:00:00,12584.89,NSW1NSW1 +95175,2020-11-09 15:00:00,13148.29,NSW1NSW1 +95176,2020-11-09 16:00:00,14221.49,NSW1NSW1 +95177,2020-11-09 17:00:00,15561.99,NSW1NSW1 +95178,2020-11-09 18:00:00,16108.86,NSW1NSW1 +95179,2020-11-09 19:00:00,16214.89,NSW1NSW1 +95180,2020-11-09 20:00:00,15724.779999999999,NSW1NSW1 +95181,2020-11-09 21:00:00,14962.83,NSW1NSW1 +95182,2020-11-09 22:00:00,14659.11,NSW1NSW1 +95183,2020-11-09 23:00:00,14411.01,NSW1NSW1 +95184,2020-11-10 00:00:00,14047.67,NSW1NSW1 +95185,2020-11-10 01:00:00,13183.41,NSW1NSW1 +95186,2020-11-10 02:00:00,12260.880000000001,NSW1NSW1 +95187,2020-11-10 03:00:00,11961.880000000001,NSW1NSW1 +95188,2020-11-10 04:00:00,12298.86,NSW1NSW1 +95189,2020-11-10 05:00:00,13324.26,NSW1NSW1 +95190,2020-11-10 06:00:00,14506.95,NSW1NSW1 +95191,2020-11-10 07:00:00,14627.02,NSW1NSW1 +95192,2020-11-10 08:00:00,13673.3,NSW1NSW1 +95193,2020-11-10 09:00:00,13236.26,NSW1NSW1 +95194,2020-11-10 10:00:00,12812.619999999999,NSW1NSW1 +95195,2020-11-10 11:00:00,12480.9,NSW1NSW1 +95196,2020-11-10 12:00:00,12319.7,NSW1NSW1 +95197,2020-11-10 13:00:00,12441.45,NSW1NSW1 +95198,2020-11-10 14:00:00,12546.44,NSW1NSW1 +95199,2020-11-10 15:00:00,13351.59,NSW1NSW1 +95200,2020-11-10 16:00:00,14619.93,NSW1NSW1 +95201,2020-11-10 17:00:00,15891.119999999999,NSW1NSW1 +95202,2020-11-10 18:00:00,16404.6,NSW1NSW1 +95203,2020-11-10 19:00:00,16420.73,NSW1NSW1 +95204,2020-11-10 20:00:00,15837.72,NSW1NSW1 +95205,2020-11-10 21:00:00,15118.48,NSW1NSW1 +95206,2020-11-10 22:00:00,14713.400000000001,NSW1NSW1 +95207,2020-11-10 23:00:00,14377.74,NSW1NSW1 +95208,2020-11-11 00:00:00,13903.3,NSW1NSW1 +95209,2020-11-11 01:00:00,13068.01,NSW1NSW1 +95210,2020-11-11 02:00:00,12190.67,NSW1NSW1 +95211,2020-11-11 03:00:00,11868.029999999999,NSW1NSW1 +95212,2020-11-11 04:00:00,12169.54,NSW1NSW1 +95213,2020-11-11 05:00:00,13190.310000000001,NSW1NSW1 +95214,2020-11-11 06:00:00,14281.82,NSW1NSW1 +95215,2020-11-11 07:00:00,14355.869999999999,NSW1NSW1 +95216,2020-11-11 08:00:00,13697.41,NSW1NSW1 +95217,2020-11-11 09:00:00,13305.02,NSW1NSW1 +95218,2020-11-11 10:00:00,12936.439999999999,NSW1NSW1 +95219,2020-11-11 11:00:00,12810.869999999999,NSW1NSW1 +95220,2020-11-11 12:00:00,12819.14,NSW1NSW1 +95221,2020-11-11 13:00:00,13256.91,NSW1NSW1 +95222,2020-11-11 14:00:00,13728.7,NSW1NSW1 +95223,2020-11-11 15:00:00,14640.91,NSW1NSW1 +95224,2020-11-11 16:00:00,15804.16,NSW1NSW1 +95225,2020-11-11 17:00:00,16891.760000000002,NSW1NSW1 +95226,2020-11-11 18:00:00,17066.65,NSW1NSW1 +95227,2020-11-11 19:00:00,16730.06,NSW1NSW1 +95228,2020-11-11 20:00:00,15984.75,NSW1NSW1 +95229,2020-11-11 21:00:00,15315.869999999999,NSW1NSW1 +95230,2020-11-11 22:00:00,14971.349999999999,NSW1NSW1 +95231,2020-11-11 23:00:00,14467.32,NSW1NSW1 +95232,2020-11-12 00:00:00,13863.72,NSW1NSW1 +95233,2020-11-12 01:00:00,13011.689999999999,NSW1NSW1 +95234,2020-11-12 02:00:00,12179.48,NSW1NSW1 +95235,2020-11-12 03:00:00,11890.83,NSW1NSW1 +95236,2020-11-12 04:00:00,12213.19,NSW1NSW1 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02:00:00,12355.67,NSW1NSW1 +95259,2020-11-13 03:00:00,12100.439999999999,NSW1NSW1 +95260,2020-11-13 04:00:00,12420.720000000001,NSW1NSW1 +95261,2020-11-13 05:00:00,13420.689999999999,NSW1NSW1 +95262,2020-11-13 06:00:00,14570.54,NSW1NSW1 +95263,2020-11-13 07:00:00,15428.029999999999,NSW1NSW1 +95264,2020-11-13 08:00:00,15464.14,NSW1NSW1 +95265,2020-11-13 09:00:00,15565.7,NSW1NSW1 +95266,2020-11-13 10:00:00,14987.96,NSW1NSW1 +95267,2020-11-13 11:00:00,14967.439999999999,NSW1NSW1 +95268,2020-11-13 12:00:00,14700.93,NSW1NSW1 +95269,2020-11-13 13:00:00,14579.71,NSW1NSW1 +95270,2020-11-13 14:00:00,15861.65,NSW1NSW1 +95271,2020-11-13 15:00:00,15770.57,NSW1NSW1 +95272,2020-11-13 16:00:00,15488.89,NSW1NSW1 +95273,2020-11-13 17:00:00,15438.61,NSW1NSW1 +95274,2020-11-13 18:00:00,15792.98,NSW1NSW1 +95275,2020-11-13 19:00:00,15746.779999999999,NSW1NSW1 +95276,2020-11-13 20:00:00,15327.77,NSW1NSW1 +95277,2020-11-13 21:00:00,14854.810000000001,NSW1NSW1 +95278,2020-11-13 22:00:00,14718.58,NSW1NSW1 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20:00:00,15131.119999999999,NSW1NSW1 +95301,2020-11-14 21:00:00,14589.29,NSW1NSW1 +95302,2020-11-14 22:00:00,14316.17,NSW1NSW1 +95303,2020-11-14 23:00:00,13749.09,NSW1NSW1 +95304,2020-11-15 00:00:00,13194.06,NSW1NSW1 +95305,2020-11-15 01:00:00,12447.33,NSW1NSW1 +95306,2020-11-15 02:00:00,11695.8,NSW1NSW1 +95307,2020-11-15 03:00:00,11472.880000000001,NSW1NSW1 +95308,2020-11-15 04:00:00,11450.849999999999,NSW1NSW1 +95309,2020-11-15 05:00:00,11569.41,NSW1NSW1 +95310,2020-11-15 06:00:00,11764.76,NSW1NSW1 +95311,2020-11-15 07:00:00,11792.45,NSW1NSW1 +95312,2020-11-15 08:00:00,11820.26,NSW1NSW1 +95313,2020-11-15 09:00:00,11779.65,NSW1NSW1 +95314,2020-11-15 10:00:00,11621.130000000001,NSW1NSW1 +95315,2020-11-15 11:00:00,11671.58,NSW1NSW1 +95316,2020-11-15 12:00:00,12033.650000000001,NSW1NSW1 +95317,2020-11-15 13:00:00,12560.02,NSW1NSW1 +95318,2020-11-15 14:00:00,13216.65,NSW1NSW1 +95319,2020-11-15 15:00:00,14538.7,NSW1NSW1 +95320,2020-11-15 16:00:00,15951.1,NSW1NSW1 +95321,2020-11-15 17:00:00,17418.07,NSW1NSW1 +95322,2020-11-15 18:00:00,17767.559999999998,NSW1NSW1 +95323,2020-11-15 19:00:00,17225.550000000003,NSW1NSW1 +95324,2020-11-15 20:00:00,16405.65,NSW1NSW1 +95325,2020-11-15 21:00:00,15427.939999999999,NSW1NSW1 +95326,2020-11-15 22:00:00,14707.029999999999,NSW1NSW1 +95327,2020-11-15 23:00:00,13937.17,NSW1NSW1 +95328,2020-11-16 00:00:00,13320.02,NSW1NSW1 +95329,2020-11-16 01:00:00,12548.23,NSW1NSW1 +95330,2020-11-16 02:00:00,12079.07,NSW1NSW1 +95331,2020-11-16 03:00:00,11920.11,NSW1NSW1 +95332,2020-11-16 04:00:00,12083.189999999999,NSW1NSW1 +95333,2020-11-16 05:00:00,12939.77,NSW1NSW1 +95334,2020-11-16 06:00:00,14301.8,NSW1NSW1 +95335,2020-11-16 07:00:00,15140.77,NSW1NSW1 +95336,2020-11-16 08:00:00,15547.279999999999,NSW1NSW1 +95337,2020-11-16 09:00:00,15506.02,NSW1NSW1 +95338,2020-11-16 10:00:00,15718.2,NSW1NSW1 +95339,2020-11-16 11:00:00,16760.699999999997,NSW1NSW1 +95340,2020-11-16 12:00:00,17891.88,NSW1NSW1 +95341,2020-11-16 13:00:00,19102.0,NSW1NSW1 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01:00:00,12971.68,NSW1NSW1 +98234,2021-03-17 02:00:00,12154.509999999998,NSW1NSW1 +98235,2021-03-17 03:00:00,11945.67,NSW1NSW1 +98236,2021-03-17 04:00:00,12288.77,NSW1NSW1 +98237,2021-03-17 05:00:00,13483.16,NSW1NSW1 +98238,2021-03-17 06:00:00,15274.27,NSW1NSW1 +98239,2021-03-17 07:00:00,16128.95,NSW1NSW1 +98240,2021-03-17 08:00:00,15743.08,NSW1NSW1 +98241,2021-03-17 09:00:00,15569.46,NSW1NSW1 +98242,2021-03-17 10:00:00,15290.55,NSW1NSW1 +98243,2021-03-17 11:00:00,15048.619999999999,NSW1NSW1 +98244,2021-03-17 12:00:00,14945.95,NSW1NSW1 +98245,2021-03-17 13:00:00,14779.29,NSW1NSW1 +98246,2021-03-17 14:00:00,14925.08,NSW1NSW1 +98247,2021-03-17 15:00:00,15453.369999999999,NSW1NSW1 +98248,2021-03-17 16:00:00,16085.39,NSW1NSW1 +98249,2021-03-17 17:00:00,16838.62,NSW1NSW1 +98250,2021-03-17 18:00:00,17014.65,NSW1NSW1 +98251,2021-03-17 19:00:00,16669.5,NSW1NSW1 +98252,2021-03-17 20:00:00,15731.880000000001,NSW1NSW1 +98253,2021-03-17 21:00:00,15064.099999999999,NSW1NSW1 +98254,2021-03-17 22:00:00,14837.68,NSW1NSW1 +98255,2021-03-17 23:00:00,14459.71,NSW1NSW1 +98256,2021-03-18 00:00:00,7094.51,NSW1 diff --git a/data_preprocessor.py b/data_preprocessor.py new file mode 100644 index 000000000..a8100f17c --- /dev/null +++ b/data_preprocessor.py @@ -0,0 +1,234 @@ +import pandas as pd +import numpy as np +from sklearn.preprocessing import MinMaxScaler, RobustScaler +from datetime import datetime, timedelta +import warnings + +warnings.filterwarnings('ignore') + + +class NSWDataPreprocessor: + def __init__(self, window_size=1440): + """ + 初始化预处理器 + + 参数: + window_size: int - 时间窗口大小，默认为1440（24小时） + """ + self.window_size = window_size + self.scalers = {} + + def _is_nsw_holiday(self, dates): + """ + 判断是否为NSW的公共假期 + + 参数: + dates: pandas Series 或 DatetimeIndex，日期数据 + """ + holidays = [ + # 添加NSW的公共假期日期 + '2023-01-01', '2023-01-26', '2023-04-07', '2023-04-10', + '2023-04-25', '2023-06-12', '2023-12-25', '2023-12-26' + ] + holidays = pd.to_datetime(holidays).date + if isinstance(dates, pd.Series): + return dates.dt.date.isin(holidays).astype(int) + else: + return pd.Series(dates.date.isin(holidays), index=dates).astype(int) + + def load_and_merge_data(self, temp_file, demand_file): + """ + 读取并合并温度和需求数据 + """ + try: + # 读取温度数据 + temp_df = pd.read_csv(temp_file) + temp_df.columns = ['location', 'datetime', 'temperature'] + temp_df['datetime'] = pd.to_datetime(temp_df['datetime'], format='%d/%m/%Y %H:%M') + + # 如果有多个地点，取平均温度 + temp_df = temp_df.groupby('datetime')['temperature'].mean().reset_index() + + # 读取需求数据 + demand_df = pd.read_csv(demand_file) + demand_df.columns = ['datetime', 'totaldemand', 'regionid'] + demand_df['datetime'] = pd.to_datetime(demand_df['datetime'], format='%d/%m/%Y %H:%M') + + # 合并数据 + df = pd.merge(demand_df, temp_df, on='datetime', how='inner') + + # 只保留需要的列并重命名 + df = df[['datetime', 'temperature', 'totaldemand']] + df.columns = ['timestamp', 'temperature', 'load'] + + # 确保数据按时间排序 + df = df.sort_values('timestamp').reset_index(drop=True) + + # 检查并处理缺失值 + if df.isnull().any().any(): + print("Find missing values and fill them in using interpolation.") + df = self._handle_missing_values(df) + + return df + + except Exception as e: + print(f"Data loading error: {str(e)}") + return None + + def _handle_missing_values(self, df): + """ + 处理缺失值 + """ + # 对温度和负载使用线性插值 + df['temperature'] = df['temperature'].interpolate(method='linear') + df['load'] = df['load'].interpolate(method='linear') + return df + + def _handle_outliers(self, df, threshold=3): + """ + 使用IQR方法处理异常值 + """ + for column in ['temperature', 'load']: + # 按每个小时分组计算异常值 + df['hour'] = df['timestamp'].dt.hour + grouped = df.groupby('hour')[column] + + Q1 = grouped.transform('quantile', 0.25) + Q3 = grouped.transform('quantile', 0.75) + IQR = Q3 - Q1 + lower_bound = Q1 - threshold * IQR + upper_bound = Q3 + threshold * IQR + + # 记录并处理异常值 + outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)][column] + if len(outliers) > 0: + print(f"{column} column contains {len(outliers)} outliers.") + + df.loc[df[column] < lower_bound, column] = lower_bound + df.loc[df[column] > upper_bound, column] = upper_bound + + df = df.drop('hour', axis=1) + return df + + def create_features(self, df): + """ + 为NSW数据创建特征 + """ + # 基本时间特征 + df['hour'] = df['timestamp'].dt.hour + df['minute'] = df['timestamp'].dt.minute + df['day_of_week'] = df['timestamp'].dt.dayofweek + df['month'] = df['timestamp'].dt.month + df['day'] = df['timestamp'].dt.day + df['week_of_year'] = df['timestamp'].dt.isocalendar().week + df['is_weekend'] = df['day_of_week'].isin([5, 6]).astype(int) + + # NSW的工作日/假期特征 + df['is_holiday'] = self._is_nsw_holiday(df['timestamp']) + + # 周期性特征 + df['hour_sin'] = np.sin(2 * np.pi * df['hour'] / 24) + df['hour_cos'] = np.cos(2 * np.pi * df['hour'] / 24) + df['minute_sin'] = np.sin(2 * np.pi * df['minute'] / 60) + df['minute_cos'] = np.cos(2 * np.pi * df['minute'] / 60) + df['day_of_week_sin'] = np.sin(2 * np.pi * df['day_of_week'] / 7) + df['day_of_week_cos'] = np.cos(2 * np.pi * df['day_of_week'] / 7) + df['month_sin'] = np.sin(2 * np.pi * df['month'] / 12) + df['month_cos'] = np.cos(2 * np.pi * df['month'] / 12) + + # 负载相关特征 + df['load_rolling_mean_24h'] = df['load'].rolling(window=24).mean() + df['load_rolling_std_24h'] = df['load'].rolling(window=24).std() + df['load_rolling_mean_7d'] = df['load'].rolling(window=24 * 7).mean() + + # 温度相关特征 + df['temp_rolling_mean_24h'] = df['temperature'].rolling(window=24).mean() + df['temp_diff'] = df['temperature'].diff() + df['temp_rolling_std_24h'] = df['temperature'].rolling(window=24).std() + + # 温度和负载的交互特征 + df['temp_load_interaction'] = df['temperature'] * df['load_rolling_mean_24h'] + + # 填充滚动特征的空值 + rolling_columns = [col for col in df.columns if 'rolling' in col or 'diff' in col] + df[rolling_columns] = df[rolling_columns].fillna(method='bfill') + + return df + + def scale_data(self, data, feature_names): + """ + 分别对不同类型的特征进行标准化 + """ + scaled_data = np.zeros_like(data, dtype=np.float32) + + # 对周期性特征不进行标准化 + periodic_features = ['hour_sin', 'hour_cos', 'minute_sin', 'minute_cos', + 'day_of_week_sin', 'day_of_week_cos', 'month_sin', 'month_cos'] + + # 对布尔特征不进行标准化 + boolean_features = ['is_weekend', 'is_holiday'] + + # 对不同类型的特征使用不同的标准化方法 + for i, feature in enumerate(feature_names): + if feature in periodic_features or feature in boolean_features: + scaled_data[:, i] = data[:, i] + else: + scaler = RobustScaler() if 'load' in feature or 'temperature' in feature else MinMaxScaler() + scaled_data[:, i] = scaler.fit_transform(data[:, i].reshape(-1, 1)).ravel() + self.scalers[feature] = scaler + + return scaled_data + + def create_sequences(self, data, seq_length): + """ + 创建时间窗口数据 + """ + sequences = [] + targets = [] + + for i in range(len(data) - seq_length - 2880): + sequence = data[i:(i + seq_length)] + target = data[i + seq_length:i + seq_length + 2880, -1] + + if len(sequence) == seq_length and len(target) == 2880: + sequences.append(sequence) + targets.append(target) + + return np.array(sequences), np.array(targets) + + def prepare_data(self, temp_file, demand_file): + """ + 完整的NSW数据准备流程 + """ + # 加载并合并数据 + df = self.load_and_merge_data(temp_file, demand_file) + if df is None: + return None + + # 创建特征 + df = self.create_features(df) + + # 选择特征 + feature_names = [ + 'hour_sin', 'hour_cos', 'minute_sin', 'minute_cos', + 'day_of_week_sin', 'day_of_week_cos', 'month_sin', 'month_cos', + 'is_weekend', 'is_holiday', + 'temperature', 'temp_rolling_mean_24h', 'temp_diff', 'temp_rolling_std_24h', + 'load', 'load_rolling_mean_24h', 'load_rolling_std_24h', 'load_rolling_mean_7d', + 'temp_load_interaction' + ] + + print("Start with feature engineering.") + data = df[feature_names].values + scaled_data = self.scale_data(data, feature_names) + + print("Start creating sequences.") + # 创建序列 + X, y = self.create_sequences(scaled_data, self.window_size) + + # 划分训练集和测试集 + train_size = int(len(X) * 0.8) + X_train, X_test = X[:train_size], X[train_size:] + y_train, y_test = y[:train_size], y[train_size:] + + return X_train, X_test, y_train, y_test, feature_names, df \ No newline at end of file diff --git a/dataset.py b/dataset.py new file mode 100644 index 000000000..db37e0af9 --- /dev/null +++ b/dataset.py @@ -0,0 +1,69 @@ +import torch +from torch.utils.data import Dataset +import numpy as np +from typing import Tuple + + +class LoadForecastingDataset(Dataset): + """ + 电力负载预测数据集类 + """ + + def __init__(self, features: np.ndarray, targets: np.ndarray): + """ + 初始化数据集 + + 参数: + features: np.ndarray - 输入特征，形状为 (N, sequence_length, num_features) + targets: np.ndarray - 目标值，形状为 (N, forecast_horizon) + """ + self.features = torch.FloatTensor(features) + self.targets = torch.FloatTensor(targets) + + def __len__(self) -> int: + """返回数据集大小""" + return len(self.features) + + def __getitem__(self, idx: int) -> Tuple[torch.Tensor, torch.Tensor]: + """返回一个数据样本""" + return self.features[idx], self.targets[idx] + + +class SequentialDataLoader: + """ + 序列数据加载器，用于生成批次数据 + """ + + def __init__(self, dataset: LoadForecastingDataset, batch_size: int, shuffle: bool = True): + """ + 初始化数据加载器 + + 参数: + dataset: LoadForecastingDataset - 数据集实例 + batch_size: int - 批次大小 + shuffle: bool - 是否打乱数据 + """ + self.dataset = dataset + self.batch_size = batch_size + self.shuffle = shuffle + self.num_samples = len(dataset) + self.indices = np.arange(self.num_samples) + + def __iter__(self): + """返回数据迭代器""" + if self.shuffle: + np.random.shuffle(self.indices) + + for start_idx in range(0, self.num_samples, self.batch_size): + end_idx = min(start_idx + self.batch_size, self.num_samples) + batch_indices = self.indices[start_idx:end_idx] + + # 获取批次数据 + features = torch.stack([self.dataset[i][0] for i in batch_indices]) + targets = torch.stack([self.dataset[i][1] for i in batch_indices]) + + yield features, targets + + def __len__(self) -> int: + """返回批次数量""" + return (self.num_samples + self.batch_size - 1) // self.batch_size \ No newline at end of file diff --git a/gantt_chart/README.md b/gantt_chart/README.md deleted file mode 100644 index 51cbeade7..000000000 --- a/gantt_chart/README.md +++ /dev/null @@ -1 +0,0 @@ -gantt_chart: Gantt chart or a link to an account in a project task management tool diff --git a/main.py b/main.py new file mode 100644 index 000000000..03a82a1fc --- /dev/null +++ b/main.py @@ -0,0 +1,411 @@ +import os +import sys +import logging +import time +from contextlib import contextmanager +from functools import wraps + +# 以下是文件 +from data_preprocessor import NSWDataPreprocessor +from visualizer import DataVisualizer +from time_series_predictor import TimeSeriesPredictor +from prophet_predictor import ProphetPredictor +from MLP_predictor import MLPPredictor +from BNN_predictor import BNNPredictor +from CNN_predictor import CNNPredictor +from LSTM_predictor import LSTMPredictor +from XGBoost_ensemble import XGBoostEnsemblePredictor +from RandomForests_ensemble import RandomForestsPredictor + + +# 输出Tee +class Tee: + def __init__(self, stdout, file): + self.stdout = stdout + self.file = file + self.encoding = stdout.encoding + + def write(self, data): + try: + self.stdout.write(data) + self.file.write(data) + # 确保立即刷新缓冲区 + self.stdout.flush() + self.file.flush() + except Exception as e: + print(f"Tee write error: {e}") + + def flush(self): + try: + self.stdout.flush() + self.file.flush() + except Exception as e: + print(f"Tee flush error: {e}") + +# 定义装饰器 +def log_function_name(func): + @wraps(func) # 保留原函数的元信息（如名称、文档字符串等） + def wrapper(*args, **kwargs): + print(f"{'='*10}{func.__name__} is running {'='*20}") # 打印函数名称 + result = func(*args, **kwargs) # 执行原函数并保存返回值 + print(f"{'='*10}{func.__name__} is done {'='*20}\n") # 打印函数完成信息 + return result # 返回原函数的结果 + return wrapper + +@log_function_name +def check_data_files(): + """ + 检查必要的数据文件是否存在 + """ + data_files = { + 'temperature': 'data/NSW/temperature_nsw.csv', + 'demand': 'data/NSW/totaldemand_nsw.csv' + } + + for name, path in data_files.items(): + if not os.path.exists(path): + logging.error(f"Error: {name} data file not found: {path}") + return False + return True + +@log_function_name +def process_data(): + """ + 数据处理步骤 + """ + try: + # 创建预处理器实例 + preprocessor = NSWDataPreprocessor(window_size=1440) # 24小时 + + # 准备数据 + X_train, X_test, y_train, y_test, feature_names, df = preprocessor.prepare_data( + 'data/NSW/temperature_nsw.csv', + 'data/NSW/totaldemand_nsw.csv' + ) + + if X_train is not None: + print("\nData preprocessing completed:") + print(f"Training set shape: {X_train.shape}") + print(f"Test set shape: {X_test.shape}") + print(f"Number of features: {len(feature_names)}") + print("\nFeature list:") + for i, feature in enumerate(feature_names): + print(f"{i + 1}. {feature}") + + return X_train, X_test, y_train, y_test, feature_names, preprocessor, df + + return None + + except Exception as e: + logging.error(f"Error during data processing: {str(e)}") + return None + +@log_function_name +def create_visualizations(df, feature_names, save_dir='data-preprocessor'): + """ + 创建数据可视化 + """ + visualizer = DataVisualizer(save_dir) + + print("Starting data visualization...") + + # 绘制每日负载模式 + visualizer.plot_daily_pattern(df) + + # 绘制温度与负载关系 + visualizer.plot_temp_load_relationship(df) + + print("Data visualization completed successfully") + +@log_function_name +def time_series(df): + """ + 示例使用方法 + """ + # 创建预测器实例 + predictor = TimeSeriesPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T', + n_neighbors=5 + ) + + # 读取示例数据 + try: + save_dir = 'model-time_series' + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + predictions.to_csv(os.path.join(save_dir, 'time_series_predictions.csv'), index=False) + print("Predictions saved to CSV file") + + except Exception as e: + logging.error(f"Error in main execution: {str(e)}") + + + +@log_function_name +def prophet_series(df): + """ + 使用Prophet模型进行预测 + """ + # 创建Prophet预测器实例 + predictor = ProphetPredictor( + forecast_hours=48, + sample_interval='30T' + ) + + try: + save_dir = 'model-prophet' + os.makedirs(save_dir, exist_ok=True) + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + predictions.to_csv(os.path.join(save_dir, 'prophet_predictions.csv'), index=False) + print("Prophet predictions saved to CSV file") + + except Exception as e: + logging.error(f"Error in prophet execution: {str(e)}") + +@log_function_name +def mlp_prediction(df): + """ + 使用MLP模型进行预测 + """ + # 创建预测器实例 + predictor = MLPPredictor( + lookback_hours=48, # 使用过去48小时的数据 + forecast_hours=48, # 预测未来48小时 + sample_interval='30T', # 30分钟间隔 + ) + + try: + # 创建保存目录 + save_dir = 'modle-mlp' + os.makedirs(save_dir, exist_ok=True) + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + # 保存预测结果到CSV + predictions.to_csv(os.path.join(save_dir, 'mlp_predictions.csv'), index=False) + print("MLP predictions saved to CSV file") + return predictions + + except Exception as e: + logging.error(f"Error in MLP prediction: {str(e)}") + + +@log_function_name +def bnn_prediction(df): + """ + 使用BNN模型进行预测 + """ + # 创建预测器实例 + predictor = BNNPredictor( + lookback_hours=48, # 使用过去48小时的数据 + forecast_hours=48, # 预测未来48小时 + sample_interval='30T' # 30分钟间隔 + ) + + try: + # 创建保存目录 + save_dir = 'model-bnn' + os.makedirs(save_dir, exist_ok=True) + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + # 保存预测结果到CSV + predictions.to_csv(os.path.join(save_dir, 'bnn_predictions.csv'), index=False) + print("BNN predictions saved to CSV file") + return predictions + + except Exception as e: + logging.error(f"Error in BNN prediction: {str(e)}") + +@log_function_name +def cnn_prediction(df): + """ + CNN模型预测 + """ + predictor = CNNPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ) + + try: + save_dir = 'model-cnn' + os.makedirs(save_dir, exist_ok=True) + + print("Starting CNN prediction process...") + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + predictions.to_csv(os.path.join(save_dir, 'cnn_predictions.csv'), index=False) + print("CNN predictions saved to CSV file") + return predictions + + except Exception as e: + logging.error(f"Error in CNN prediction: {str(e)}") + print(f"CNN prediction failed with error: {str(e)}") + +@log_function_name +def lstm_prediction(df): + """ + 使用LSTM模型进行预测 + """ + # 创建预测器实例 + predictor = LSTMPredictor( + lookback_hours=48, # 使用过去48小时的数据 + forecast_hours=48, # 预测未来48小时 + sample_interval='30T' # 30分钟间隔 + ) + + try: + # 创建保存目录 + save_dir = 'model-lstm' + os.makedirs(save_dir, exist_ok=True) + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + # 保存预测结果到CSV + predictions.to_csv(os.path.join(save_dir, 'lstm_predictions.csv'), index=False) + print("LSTM predictions saved to CSV file") + return predictions + + except Exception as e: + logging.error(f"Error in LSTM prediction: {str(e)}") + +@log_function_name +def xgboost_prediction(df): + """ + Using XGBoost Ensemble model for prediction + """ + # Initialize predictor + predictor = XGBoostEnsemblePredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ) + + try: + # Create save directory + save_dir = 'model-xgboost' + os.makedirs(save_dir, exist_ok=True) + + # Execute prediction + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + # Save predictions to CSV + predictions.to_csv(os.path.join(save_dir, 'xgboost_predictions.csv'), index=False) + print("XGBoost ensemble predictions saved to CSV file") + return predictions + + except Exception as e: + logging.error(f"Error in XGBoost prediction: {str(e)}") + +@log_function_name +def random_forest_prediction(df): + """ + 随机森林预测 + """ + # 创建预测器实例 + predictor = RandomForestsPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ) + + try: + save_dir = 'model-random_forest' + os.makedirs(save_dir, exist_ok=True) + + # 执行预测 + predictions = predictor.predict(df, save_dir=save_dir) + + if predictions is not None: + predictions.to_csv(os.path.join(save_dir, 'random_forest_predictions.csv'), index=False) + print("Random Forest predictions saved to CSV file") + + except Exception as e: + logging.error(f"Error in Random Forest prediction: {str(e)}") + +def main(): + """ + 主函数，用于协调整个程序的执行流程 + """ + # 检查数据文件 + if not check_data_files(): + return + + + # 数据处理 + results = process_data() + if results is None: + logging.error("Data processing failed") + return + + X_train, X_test, y_train, y_test, feature_names, preprocessor, df = results + + + # # 创建可视化 + # create_visualizations(df, feature_names) + # + # # 模型-时间序列-负载 + # time_series(df) + # + # # 模型-prophet + # prophet_series(df) + # + # # 模型-MLP预测 + # mlp_prediction(df) + # + # # 模型-BNN预测 + # bnn_prediction(df) + # + # # 模型-CNN预测 + # cnn_prediction(df) + # + # # 模型-LSTM预测 + # lstm_prediction(df) + # + # # 模型-XGBoost集成预测 + # xgboost_prediction(df) + + # 随机森林预测 + random_forest_prediction(df) + + +if __name__ == "__main__": + + @contextmanager + def tee_output(filename): + try: + os.makedirs('logs', exist_ok=True) + with open(filename, 'w', encoding='utf-8') as file: + tee = Tee(sys.stdout, file) + old_stdout = sys.stdout + sys.stdout = tee + try: + yield + finally: + sys.stdout = old_stdout + except Exception as e: + print(f"Error in tee_output: {e}") + + + # 使用方式 + current_time = time.strftime("%Y%m%d_%H%M%S") + with tee_output(f'logs/output_{current_time}.txt'): + main() \ No newline at end of file diff --git a/minutes/README.md b/minutes/README.md deleted file mode 100644 index 2db70b528..000000000 --- a/minutes/README.md +++ /dev/null @@ -1 +0,0 @@ -minutes: minutes for each meeting (left not more than 24h after the corresponding meeting) diff --git a/prophet.md b/prophet.md new file mode 100644 index 000000000..c329a722a --- /dev/null +++ b/prophet.md @@ -0,0 +1,71 @@ +基于时间序列预测的 Prophet 模型研究与实现机制分析 + +一、引言 +Prophet 是由 Facebook（现为 Meta）研究团队开发的开源时间序列预测系统，其设计理念源于对大规模业务预测需求的实践总结。该模型具有较强的鲁棒性和可解释性，能够有效处理缺失值、异常值，并自动检测趋势变点，在保持预测精度的同时兼顾了模型的实用性。 + +二、模型理论基础 +Prophet 采用分解模型的思想，将时间序列分解为趋势项、季节性项、节假日效应项及误差项四个部分。其核心数学表达式为： + +y(t) = g(t) + s(t) + h(t) + ε(t) + +其中，g(t)表示趋势函数，用于捕捉时间序列的长期走势；s(t)代表季节性成分，描述周期性变化；h(t)表示节假日效应；ε(t)为误差项，假设服从正态分布。 + +三、趋势建模机制 +Prophet 提供了两种趋势建模范式：分段线性增长模型和逻辑增长模型。分段线性增长模型适用于增长模式相对稳定的场景，其数学表达式为： + +g(t) = (k + a(t)ᵀδ)t + (m + a(t)ᵀγ) + +而逻辑增长模型则适用于具有增长上限的场景，表达式为： + +g(t) = C/(1 + exp(-(k + a(t)ᵀδ)(t - (m + a(t)ᵀγ)))) + +其中，C 代表增长上限，k 为增长率，δ 表示速率调整参数，m 为偏移量。 + +四、季节性建模方法 +Prophet 采用傅里叶级数来刻画时间序列中的周期性模式。对于年度、周度等不同尺度的季节性，模型分别构建相应的傅里叶级数： + +s(t) = ∑[an cos(2πnt/P) + bn sin(2πnt/P)] + +其中，P 表示周期长度，n 为傅里叶级数的阶数，通过调整阶数可以控制季节性模式的复杂程度。 + +五、节假日效应处理机制 +模型通过引入节假日指示变量来捕捉特殊时期的影响： + +h(t) = Z(t)κ + +其中，Z(t) 为节假日指示矩阵，κ 为对应的影响系数向量。模型允许用户自定义节假日窗口期，从而更精确地刻画节假日效应。 + +六、模型估计与优化 +Prophet 采用贝叶斯框架进行参数估计，为主要参数设定了先验分布： + +1. 趋势变化率参数 τ 采用拉普拉斯分布：τ ~ Laplace(0, τ₀) +2. 趋势调整参数 δ 采用拉普拉斯分布：δ ~ Laplace(0, σ) +3. 季节性参数 β 采用正态分布：β ~ Normal(0, 5) + +模型使用 L-BFGS 算法对参数进行优化，在计算效率和优化效果之间取得平衡。 + +七、不确定性量化 +Prophet 通过贝叶斯框架提供了预测的不确定性估计。模型生成的预测区间不仅考虑了参数的不确定性，还包含了模型结构的不确定性，为决策提供了更全面的信息支持。 + +八、优势与局限性 +Prophet 的主要优势在于： +1. 自动化程度高，能够处理缺失值和异常值 +2. 具有较强的可解释性，支持分解查看各成分的贡献 +3. 预测结果稳健，对异常值不敏感 +4. 支持自定义节假日效应和外部回归变量 + +然而，Prophet 也存在一些局限性： +1. 对于高度非线性的时间序列，预测效果可能不如深度学习模型 +2. 在处理具有复杂多变量关系的数据时，表现可能不够理想 +3. 对于样本量较小的数据集，模型的稳定性可能受到影响 + +九、结论 +Prophet 作为一个面向实践的时间序列预测框架，通过decomposition思想和贝叶斯方法的结合，在保证预测精度的同时提供了较好的可解释性和易用性。其自动化的特征使其特别适合大规模业务预测场景，但在应用时仍需根据具体问题特点选择合适的模型配置和参数设置。 + +十、未来研究方向 +1. 探索将深度学习方法整合入Prophet框架 +2. 改进对多变量时间序列的建模能力 +3. 优化计算效率，使其更适合实时预测场景 +4. 发展针对特定领域的专门化模型变体 + +这一研究不仅推进了时间序列预测的理论发展，也为实践应用提供了有力工具，对相关领域的进一步研究具有重要的参考价值。 \ No newline at end of file diff --git a/prophet_predictor.py b/prophet_predictor.py new file mode 100644 index 000000000..447bc2c3f --- /dev/null +++ b/prophet_predictor.py @@ -0,0 +1,258 @@ +import pandas as pd +import numpy as np +from prophet import Prophet +from sklearn.metrics import mean_squared_error, mean_absolute_error +import itertools +import matplotlib.pyplot as plt +import os +from typing import Optional, Dict, List, Tuple +from datetime import datetime +import logging + + +class ProphetPredictor: + """ + 基于Facebook Prophet的时间序列预测器 + 主要用于预测电力负载，支持温度作为额外的回归变量 + """ + + def __init__(self, forecast_hours: int = 48, sample_interval: str = '30T'): + """ + 初始化预测器 + + 参数: + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + """ + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.best_params = None + + # 定义参数网格 + self.param_grid = { + 'changepoint_prior_scale': [0.01, 0.1], + 'seasonality_prior_scale': [0.1, 1.0], + 'seasonality_mode': ['multiplicative'], + 'changepoint_range': [0.9], + 'holidays_prior_scale': [0.1] + } + + def _preprocess_data(self, df: pd.DataFrame) -> pd.DataFrame: + """ + 预处理时间序列数据 + + 参数: + df: DataFrame - 包含 'timestamp', 'temperature', 'load' 列的数据框 + + 返回: + DataFrame - 处理后的Prophet格式数据框 + """ + try: + print("Starting data preprocessing for Prophet...") + + # 准备Prophet格式数据 + prophet_df = df[['timestamp', 'load', 'temperature']].copy() + prophet_df.columns = ['ds', 'y', 'temperature'] + + # 确保数据按时间排序 + prophet_df = prophet_df.sort_values('ds').reset_index(drop=True) + + # 重采样数据 + prophet_df.set_index('ds', inplace=True) + prophet_df = prophet_df.resample(self.sample_interval).mean().interpolate(method='time') + prophet_df.reset_index(inplace=True) + + return prophet_df + + except Exception as e: + logging.error(f"Error in data preprocessing: {str(e)}") + raise + + def _grid_search(self, train_df: pd.DataFrame, val_df: pd.DataFrame) -> Dict: + """ + 网格搜索最佳参数 + + 参数: + train_df: DataFrame - 训练数据 + val_df: DataFrame - 验证数据 + + 返回: + Dict - 最佳参数 + """ + all_params = [dict(zip(self.param_grid.keys(), v)) + for v in itertools.product(*self.param_grid.values())] + print(f"Evaluating {len(all_params)} parameter combinations") + + best_params = None + best_score = float('inf') + + for params in all_params: + try: + print(f"\nTrying parameters: {params}") + + model = Prophet( + changepoint_prior_scale=params['changepoint_prior_scale'], + seasonality_prior_scale=params['seasonality_prior_scale'], + seasonality_mode=params['seasonality_mode'], + changepoint_range=params['changepoint_range'], + holidays_prior_scale=params['holidays_prior_scale'], + yearly_seasonality=True, + weekly_seasonality=True, + daily_seasonality=True + ) + + # 添加温度作为回归变量 + model.add_regressor('temperature') + + # 训练模型 + model.fit(train_df) + + # 验证 + forecast = model.predict(val_df) + mse = mean_squared_error(val_df['y'], forecast['yhat']) + mae = mean_absolute_error(val_df['y'], forecast['yhat']) + + if mse < best_score: + best_score = mse + best_params = params + print(f'New best parameters found: MSE={mse:.2f}, MAE={mae:.2f}') + + except Exception as e: + print(f"Error with parameters {params}: {str(e)}") + continue + + return best_params + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + + 参数: + df: DataFrame - 输入数据 + save_dir: Optional[str] - 保存预测结果的目录 + + 返回: + Optional[pd.DataFrame] - 预测结果数据框 + """ + try: + # 数据预处理 + prophet_df = self._preprocess_data(df) + + # 划分训练集和验证集 + train_size = int(len(prophet_df) * 0.8) + train_df = prophet_df[:train_size] + val_df = prophet_df[train_size:] + + # 网格搜索最佳参数 + if not self.best_params: + self.best_params = self._grid_search(train_df, val_df) + + if self.best_params: + print("\nTraining final model with best parameters...") + final_model = Prophet( + changepoint_prior_scale=self.best_params['changepoint_prior_scale'], + seasonality_prior_scale=self.best_params['seasonality_prior_scale'], + seasonality_mode=self.best_params['seasonality_mode'], + changepoint_range=self.best_params['changepoint_range'], + holidays_prior_scale=self.best_params['holidays_prior_scale'], + yearly_seasonality=True, + weekly_seasonality=True, + daily_seasonality=True + ) + final_model.add_regressor('temperature') + final_model.fit(prophet_df) + + # 创建未来时间序列 + future = final_model.make_future_dataframe(periods=self.forecast_points, + freq=self.sample_interval) + + # 使用最后一个已知温度值 + future['temperature'] = df['temperature'].iloc[-1] + + # 生成预测 + print("Generating predictions...") + forecast = final_model.predict(future) + predictions = forecast['yhat'].tail(self.forecast_points).values + + # 创建时间戳 + last_timestamp = pd.to_datetime(df['timestamp'].iloc[-1]) + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': predictions + }) + + # 可视化结果 + self._plot_predictions(df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(predictions) + + return predictions_df + + return None + + except Exception as e: + logging.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表 + + 参数: + historical_df: pd.DataFrame - 历史数据 + predictions_df: pd.DataFrame - 预测数据 + save_dir: Optional[str] - 保存图表的目录 + """ + plt.figure(figsize=(15, 6)) + + # 绘制历史数据（最后48小时） + historical_data = historical_df['load'].iloc[-48:] + historical_timestamps = historical_df['timestamp'].iloc[-48:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='Prophet Predicted Load', color='red', alpha=0.6) + + plt.title(f'{self.forecast_hours}-hour Prophet Load Forecast') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'prophet_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"Prophet prediction plot saved in {save_dir}") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + + 参数: + predictions: np.ndarray - 预测结果数组 + """ + print("\nProphet Prediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") \ No newline at end of file diff --git a/report/README.md b/report/README.md deleted file mode 100644 index 30ea0b294..000000000 --- a/report/README.md +++ /dev/null @@ -1 +0,0 @@ -report: RMarkdown or Jupyter notebook report in progress diff --git a/src/.ipynb_checkpoints/GoogleColab-checkpoint.ipynb b/src/.ipynb_checkpoints/GoogleColab-checkpoint.ipynb deleted file mode 100644 index 55cf0c9a2..000000000 --- a/src/.ipynb_checkpoints/GoogleColab-checkpoint.ipynb +++ /dev/null @@ -1,103 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "KvzS9oPYBJQZ" - }, - "source": [ - "\n", - " \"Open\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Welcome to ZZSC9020\n", - "\n", - "This Python notebook shows how to clone the course GitHub repository on Google Colab.\n", - "\n", - "You can develop your data analysis on Google Colab without downloading the data to your computer." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "brynNOEi6FzS", - "outputId": "41c6d4a4-bc13-4b14-c75c-951705efe1fb" - }, - "outputs": [], - "source": [ - "# Clone the ZZSC9020 project repository from GitHub\n", - "!git clone https://github.com/UNSW-ZZSC9020/project.git" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "44VdVtiX7Ukn" - }, - "outputs": [], - "source": [ - "# Create a data folder\n", - "!mkdir -p data\n", - "# Joint forecastdemand_nsw files into a single file. \n", - "!cat project/data/forecastdemand_nsw.csv.zip.part* > data/forecastdemand_nsw.csv.zip" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "GdnC6dlz8agZ", - "outputId": "fee967de-019b-44d9-83c0-526577b1baf0" - }, - "outputs": [], - "source": [ - "# Unzip the data files into the data folder\n", - "!unzip data/forecastdemand_nsw.csv.zip -d data\n", - "!unzip project/data/temperature_nsw.csv.zip -d data\n", - "!unzip project/data/totaldemand_nsw.csv.zip -d data\n", - "\n", - "# Remove forecastdemand_nsw.csv.zip\n", - "!rm data/forecastdemand_nsw.csv.zip" - ] - } - ], - "metadata": { - "colab": { - "collapsed_sections": [], - "name": "GoogleColab.ipynb", - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.12" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/src/GoogleColab.ipynb b/src/GoogleColab.ipynb deleted file mode 100644 index 55cf0c9a2..000000000 --- a/src/GoogleColab.ipynb +++ /dev/null @@ -1,103 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "KvzS9oPYBJQZ" - }, - "source": [ - "\n", - " \"Open\n", - "" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Welcome to ZZSC9020\n", - "\n", - "This Python notebook shows how to clone the course GitHub repository on Google Colab.\n", - "\n", - "You can develop your data analysis on Google Colab without downloading the data to your computer." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "brynNOEi6FzS", - "outputId": "41c6d4a4-bc13-4b14-c75c-951705efe1fb" - }, - "outputs": [], - "source": [ - "# Clone the ZZSC9020 project repository from GitHub\n", - "!git clone https://github.com/UNSW-ZZSC9020/project.git" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "44VdVtiX7Ukn" - }, - "outputs": [], - "source": [ - "# Create a data folder\n", - "!mkdir -p data\n", - "# Joint forecastdemand_nsw files into a single file. \n", - "!cat project/data/forecastdemand_nsw.csv.zip.part* > data/forecastdemand_nsw.csv.zip" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "GdnC6dlz8agZ", - "outputId": "fee967de-019b-44d9-83c0-526577b1baf0" - }, - "outputs": [], - "source": [ - "# Unzip the data files into the data folder\n", - "!unzip data/forecastdemand_nsw.csv.zip -d data\n", - "!unzip project/data/temperature_nsw.csv.zip -d data\n", - "!unzip project/data/totaldemand_nsw.csv.zip -d data\n", - "\n", - "# Remove forecastdemand_nsw.csv.zip\n", - "!rm data/forecastdemand_nsw.csv.zip" - ] - } - ], - "metadata": { - "colab": { - "collapsed_sections": [], - "name": "GoogleColab.ipynb", - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.12" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/src/README.md b/src/README.md deleted file mode 100644 index a1b7c934a..000000000 --- a/src/README.md +++ /dev/null @@ -1 +0,0 @@ -src: source code diff --git a/time_series_predictor.py b/time_series_predictor.py new file mode 100644 index 000000000..031b15399 --- /dev/null +++ b/time_series_predictor.py @@ -0,0 +1,247 @@ +import pandas as pd +import numpy as np +from sklearn.metrics import mean_squared_error, mean_absolute_error +from sklearn.preprocessing import MinMaxScaler +import matplotlib.pyplot as plt +from scipy.spatial.distance import euclidean +from typing import Optional, Tuple, List +import logging +from datetime import datetime +import os + + +class TimeSeriesPredictor: + """ + 基于相似模式的时间序列预测器 + 主要用于预测电力负载，但也可扩展用于其他时间序列预测任务 + """ + + def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, + sample_interval: str = '30T', n_neighbors: int = 5): + """ + 初始化预测器 + + 参数: + lookback_hours: int - 用于预测的历史数据时长（小时） + forecast_hours: int - 预测时长（小时） + sample_interval: str - 数据采样间隔，默认30分钟 + n_neighbors: int - 用于预测的相似模式数量 + """ + self.lookback_hours = lookback_hours + self.forecast_hours = forecast_hours + self.sample_interval = sample_interval + self.n_neighbors = n_neighbors + self.lookback_points = int(lookback_hours * 60 / int(sample_interval[:-1])) + self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) + self.scaler = MinMaxScaler(feature_range=(0, 1)) + + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: + """ + 预处理时间序列数据 + + 参数: + df: DataFrame - 包含 'timestamp', 'temperature', 'load' 列的数据框 + + 返回: + Tuple[pd.DataFrame, np.ndarray] - 处理后的数据框和标准化后的特征数据 + """ + try: + print("Starting data preprocessing...") + + # 确保数据按时间排序 + df = df[['timestamp', 'temperature', 'load']].copy() + df['timestamp'] = pd.to_datetime(df['timestamp']) + df = df.sort_values('timestamp').reset_index(drop=True) + + # 重采样数据 + df.set_index('timestamp', inplace=True) + df = df.resample(self.sample_interval).mean().interpolate(method='time') + df.reset_index(inplace=True) + + # 添加时间特征 + df['hour'] = df['timestamp'].dt.hour + df['dayofweek'] = df['timestamp'].dt.dayofweek + + # 标准化数据 + features = ['hour', 'dayofweek', 'temperature', 'load'] + scaled_data = self.scaler.fit_transform(df[features]) + + return df, scaled_data + + except Exception as e: + self.logger.error(f"Error in data preprocessing: {str(e)}") + raise + + def _create_sequences(self, scaled_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]: + """ + 创建时间序列的输入序列和目标序列 + + 参数: + scaled_data: np.ndarray - 标准化后的特征数据 + + 返回: + Tuple[np.ndarray, np.ndarray] - 输入序列和对应的目标序列 + """ + try: + X = [] + y = [] + + for i in range(len(scaled_data) - self.lookback_points - self.forecast_points): + X.append(scaled_data[i:(i + self.lookback_points)]) + y.append(scaled_data[(i + self.lookback_points):(i + self.lookback_points + self.forecast_points), -1]) + + return np.array(X), np.array(y) + + except Exception as e: + self.logger.error(f"Error in sequence creation: {str(e)}") + raise + + def _predict_similar_pattern(self, test_window: np.ndarray, + train_windows: np.ndarray, + train_targets: np.ndarray) -> np.ndarray: + """ + 基于相似模式进行预测 + + 参数: + test_window: np.ndarray - 用于预测的测试窗口 + train_windows: np.ndarray - 训练数据窗口 + train_targets: np.ndarray - 训练数据目标值 + + 返回: + np.ndarray - 预测结果 + """ + try: + # 计算与所有训练窗口的相似度 + similarities = np.array([ + euclidean(test_window.flatten(), train_window.flatten()) + for train_window in train_windows + ]) + + # 找到最相似的k个窗口 + similar_indices = np.argsort(similarities)[:self.n_neighbors] + weights = 1 / (similarities[similar_indices] + 1e-6) + weights /= np.sum(weights) + + # 加权平均预测 + return np.average(train_targets[similar_indices], weights=weights, axis=0) + + except Exception as e: + self.logger.error(f"Error in pattern prediction: {str(e)}") + raise + + def predict(self, df: pd.DataFrame, save_dir: Optional[str] = None) -> Optional[pd.DataFrame]: + """ + 执行完整的预测流程 + + 参数: + df: DataFrame - 输入数据 + save_dir: Optional[str] - 保存预测结果的目录 + + 返回: + Optional[pd.DataFrame] - 预测结果数据框 + """ + try: + # 数据预处理 + processed_df, scaled_data = self._preprocess_data(df) + + # 创建序列 + X, y = self._create_sequences(scaled_data) + + # 划分训练集 + train_size = int(len(X) * 0.8) + X_train = X[:train_size] + y_train = y[:train_size] + + print("Preparing final prediction...") + # 使用最后一个时间窗口进行预测 + last_window = scaled_data[-self.lookback_points:] + future_prediction = self._predict_similar_pattern(last_window, X_train, y_train) + + # 准备反标准化 + dummy_features = np.zeros((self.forecast_points, scaled_data.shape[1])) + dummy_features[:, -1] = future_prediction + + # 反标准化预测结果 + final_predictions = self.scaler.inverse_transform(dummy_features)[:, -1] + + # 创建时间索引 + last_timestamp = processed_df['timestamp'].iloc[-1] + future_timestamps = pd.date_range( + start=last_timestamp, + periods=self.forecast_points + 1, + freq=self.sample_interval + )[1:] + + # 创建预测结果DataFrame + predictions_df = pd.DataFrame({ + 'timestamp': future_timestamps, + 'predicted_load': final_predictions + }) + + # 可视化结果 + self._plot_predictions(processed_df, predictions_df, save_dir) + + # 输出预测统计信息 + self._print_prediction_summary(final_predictions) + + return predictions_df + + except Exception as e: + self.logger.error(f"Error in prediction process: {str(e)}") + return None + + def _plot_predictions(self, historical_df: pd.DataFrame, + predictions_df: pd.DataFrame, + save_dir: Optional[str] = None) -> None: + """ + 绘制预测结果图表 + + 参数: + historical_df: pd.DataFrame - 历史数据 + predictions_df: pd.DataFrame - 预测数据 + save_dir: Optional[str] - 保存图表的目录 + """ + plt.figure(figsize=(15, 6)) + + # 绘制最后一个时间窗口的历史数据 + historical_data = historical_df['load'].iloc[-self.lookback_points:] + historical_timestamps = historical_df['timestamp'].iloc[-self.lookback_points:] + plt.plot(historical_timestamps, historical_data, + label='Historical Data', color='blue', alpha=0.6) + + # 绘制预测数据 + plt.plot(predictions_df['timestamp'], predictions_df['predicted_load'], + label='Predicted Load', color='red', alpha=0.6) + + plt.title(f'{self.forecast_hours}-hour Load Forecast ({self.sample_interval[:-1]} minute intervals)') + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + if save_dir: + os.makedirs(save_dir, exist_ok=True) + plt.savefig(os.path.join(save_dir, f'time_series_prediction.png'), + dpi=300, bbox_inches='tight') + print(f"Prediction plot saved in {save_dir} dir") + else: + plt.show() + + plt.close() + + def _print_prediction_summary(self, predictions: np.ndarray) -> None: + """ + 打印预测结果的统计信息 + + 参数: + predictions: np.ndarray - 预测结果数组 + """ + print("\nPrediction Summary:") + print(f"Mean Load: {predictions.mean():.2f} MW") + print(f"Standard Deviation: {predictions.std():.2f} MW") + print(f"Maximum Load: {predictions.max():.2f} MW") + print(f"Minimum Load: {predictions.min():.2f} MW") + + diff --git a/utils.py b/utils.py new file mode 100644 index 000000000..cb7759d60 --- /dev/null +++ b/utils.py @@ -0,0 +1,140 @@ +import os +import random +import numpy as np +import torch +import matplotlib.pyplot as plt +from datetime import datetime +import logging +from typing import Dict, List, Tuple, Union + + +def setup_logging(save_path: str) -> None: + """ + 设置日志记录 + """ + os.makedirs(save_path, exist_ok=True) + logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s', + handlers=[ + logging.FileHandler(os.path.join(save_path, f'training_{datetime.now().strftime("%Y%m%d_%H%M%S")}.log')), + logging.StreamHandler() + ] + ) + + +def set_random_seed(seed: int) -> None: + """ + 设置随机种子以确保结果可复现 + """ + random.seed(seed) + np.random.seed(seed) + torch.manual_seed(seed) + if torch.cuda.is_available(): + torch.cuda.manual_seed(seed) + torch.cuda.manual_seed_all(seed) + torch.backends.cudnn.deterministic = True + torch.backends.cudnn.benchmark = False + + +def calculate_metrics(y_true: np.ndarray, y_pred: np.ndarray) -> Dict[str, float]: + """ + 计算各种评估指标 + """ + metrics = {} + metrics['mae'] = np.mean(np.abs(y_true - y_pred)) + metrics['mse'] = np.mean((y_true - y_pred) ** 2) + metrics['rmse'] = np.sqrt(metrics['mse']) + # 避免除零错误 + mask = y_true != 0 + metrics['mape'] = np.mean(np.abs((y_true[mask] - y_pred[mask]) / y_true[mask])) * 100 + return metrics + + +def plot_predictions( + y_true: np.ndarray, + y_pred: np.ndarray, + timestamps: List[datetime], + save_path: str, + title: str = "Load Forecasting Results" +) -> None: + """ + 绘制预测结果 + """ + plt.figure(figsize=(15, 6)) + plt.plot(timestamps, y_true, label='Actual', alpha=0.7) + plt.plot(timestamps, y_pred, label='Predicted', alpha=0.7) + plt.title(title) + plt.xlabel('Time') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + plt.tight_layout() + + # 保存图片 + os.makedirs(save_path, exist_ok=True) + plt.savefig(os.path.join(save_path, f'prediction_{datetime.now().strftime("%Y%m%d_%H%M%S")}.png')) + plt.close() + + +def save_model( + model: torch.nn.Module, + optimizer: torch.optim.Optimizer, + epoch: int, + loss: float, + save_path: str, + model_name: str +) -> None: + """ + 保存模型检查点 + """ + os.makedirs(save_path, exist_ok=True) + checkpoint = { + 'epoch': epoch, + 'model_state_dict': model.state_dict(), + 'optimizer_state_dict': optimizer.state_dict(), + 'loss': loss + } + torch.save(checkpoint, os.path.join(save_path, f'{model_name}_epoch_{epoch}.pth')) + + +def load_model( + model: torch.nn.Module, + optimizer: torch.optim.Optimizer, + model_path: str +) -> Tuple[torch.nn.Module, torch.optim.Optimizer, int, float]: + """ + 加载模型检查点 + """ + checkpoint = torch.load(model_path) + model.load_state_dict(checkpoint['model_state_dict']) + optimizer.load_state_dict(checkpoint['optimizer_state_dict']) + epoch = checkpoint['epoch'] + loss = checkpoint['loss'] + return model, optimizer, epoch, loss + + +class EarlyStopping: + """ + 早停机制 + """ + + def __init__(self, patience: int = 7, min_delta: float = 0): + self.patience = patience + self.min_delta = min_delta + self.counter = 0 + self.best_loss = None + self.early_stop = False + + def __call__(self, val_loss: float) -> bool: + if self.best_loss is None: + self.best_loss = val_loss + elif val_loss > self.best_loss - self.min_delta: + self.counter += 1 + if self.counter >= self.patience: + self.early_stop = True + else: + self.best_loss = val_loss + self.counter = 0 + return self.early_stop \ No newline at end of file diff --git a/visualizer.py b/visualizer.py new file mode 100644 index 000000000..d059dece3 --- /dev/null +++ b/visualizer.py @@ -0,0 +1,207 @@ +import matplotlib.pyplot as plt +import seaborn as sns +import pandas as pd +import numpy as np +from typing import List, Tuple, Optional +import os +from datetime import datetime + + +class DataVisualizer: + """ + 用于数据可视化的类，提供多种图表绘制功能 + """ + + def __init__(self, save_dir: str): + """ + 初始化可视化工具 + + 参数: + save_dir: str - 图片保存目录 + """ + self.save_dir = save_dir + os.makedirs(save_dir, exist_ok=True) + self._setup_plot_style() + + def _setup_plot_style(self): + """ + 设置图表样式 + """ + # 使用内置的风格而不是seaborn + plt.style.use('classic') + sns.set_theme(style="whitegrid") # 使用seaborn的主题设置 + plt.rcParams['figure.figsize'] = (12, 6) + plt.rcParams['font.size'] = 10 + + def _save_plot(self, name: str): + """ + 保存图表 + + 参数: + name: str - 图表名称 + """ + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + filename = f"{name}.png" + plt.savefig(os.path.join(self.save_dir, filename), dpi=300, bbox_inches='tight') + plt.close() + print(f"Plot saved: {filename}") + + def plot_time_series(self, df: pd.DataFrame, columns: List[str], title: str): + """ + 绘制时间序列数据 + + 参数: + df: pd.DataFrame - 包含时间序列数据的DataFrame + columns: List[str] - 需要绘制的列名列表 + title: str - 图表标题 + """ + plt.figure(figsize=(15, 7)) + for column in columns: + plt.plot(df['timestamp'], df[column], label=column, alpha=0.7) + + plt.title(title) + plt.xlabel('Time') + plt.ylabel('Value') + plt.legend() + plt.grid(True) + plt.xticks(rotation=45) + self._save_plot(f"time_series_{columns[0]}") + + def plot_correlation_heatmap(self, df: pd.DataFrame, features: List[str]): + """ + 绘制特征相关性热力图 + + 参数: + df: pd.DataFrame - 包含特征的DataFrame + features: List[str] - 需要分析相关性的特征列表 + """ + plt.figure(figsize=(12, 10)) + correlation = df[features].corr() + sns.heatmap(correlation, annot=True, cmap='coolwarm', center=0) + plt.title('Feature Correlation Heatmap') + self._save_plot('correlation_heatmap') + + def plot_feature_distributions(self, df: pd.DataFrame, features: List[str]): + """ + 绘制特征分布图 + + 参数: + df: pd.DataFrame - 包含特征的DataFrame + features: List[str] - 需要分析分布的特征列表 + """ + n_features = len(features) + n_cols = 2 + n_rows = (n_features + 1) // 2 + + plt.figure(figsize=(15, 5 * n_rows)) + for i, feature in enumerate(features, 1): + plt.subplot(n_rows, n_cols, i) + sns.histplot(data=df, x=feature, kde=True) + plt.title(f'{feature} Distribution') + plt.xlabel(feature) + plt.ylabel('Count') + + plt.tight_layout() + self._save_plot('feature_distributions') + + def plot_daily_pattern(self, df: pd.DataFrame): + """ + 绘制每日负载模式图 + + 参数: + df: pd.DataFrame - 包含负载数据的DataFrame + """ + daily_df = df.copy() + daily_df['hour'] = daily_df['timestamp'].dt.hour + daily_pattern = daily_df.groupby('hour')['load'].agg(['mean', 'std']).reset_index() + + plt.figure(figsize=(12, 6)) + plt.plot(daily_pattern['hour'], daily_pattern['mean'], 'b-', label='Mean Load') + plt.fill_between( + daily_pattern['hour'], + daily_pattern['mean'] - daily_pattern['std'], + daily_pattern['mean'] + daily_pattern['std'], + alpha=0.2, + label='±1 std' + ) + + plt.title('Average Daily Load Pattern') + plt.xlabel('Hour of Day') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(range(0, 24, 2)) + self._save_plot('daily_pattern') + + def plot_temp_load_relationship(self, df: pd.DataFrame): + """ + 绘制温度与负载关系图 + + 参数: + df: pd.DataFrame - 包含温度和负载数据的DataFrame + """ + plt.figure(figsize=(10, 6)) + sns.scatterplot(data=df, x='temperature', y='load', alpha=0.5) + + # 添加趋势线 + z = np.polyfit(df['temperature'], df['load'], 2) + p = np.poly1d(z) + temp_range = np.linspace(df['temperature'].min(), df['temperature'].max(), 100) + plt.plot(temp_range, p(temp_range), 'r--', label='Trend Line') + + plt.title('Temperature vs Load Relationship') + plt.xlabel('Temperature (°C)') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + self._save_plot('temp_load_relationship') + + def plot_weekly_pattern(self, df: pd.DataFrame): + """ + 绘制每周负载模式图 + + 参数: + df: pd.DataFrame - 包含负载数据的DataFrame + """ + weekly_df = df.copy() + weekly_df['day_of_week'] = weekly_df['timestamp'].dt.day_name() + weekly_pattern = weekly_df.groupby('day_of_week')['load'].agg(['mean', 'std']).reset_index() + days_order = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday'] + weekly_pattern['day_of_week'] = pd.Categorical(weekly_pattern['day_of_week'], categories=days_order, ordered=True) + weekly_pattern = weekly_pattern.sort_values('day_of_week') + + plt.figure(figsize=(12, 6)) + plt.plot(days_order, weekly_pattern['mean'], 'b-', marker='o', label='Mean Load') + plt.fill_between( + range(7), + weekly_pattern['mean'] - weekly_pattern['std'], + weekly_pattern['mean'] + weekly_pattern['std'], + alpha=0.2, + label='±1 std' + ) + + plt.title('Average Weekly Load Pattern') + plt.xlabel('Day of Week') + plt.ylabel('Load (MW)') + plt.legend() + plt.grid(True) + plt.xticks(range(7), days_order, rotation=45) + self._save_plot('weekly_pattern') + + def plot_feature_importance(self, feature_names: List[str], importance_scores: np.ndarray): + """ + 绘制特征重要性图 + + 参数: + feature_names: List[str] - 特征名称列表 + importance_scores: np.ndarray - 特征重要性分数 + """ + sorted_idx = np.argsort(importance_scores) + pos = np.arange(sorted_idx.shape[0]) + .5 + + plt.figure(figsize=(10, len(feature_names) / 2)) + plt.barh(pos, importance_scores[sorted_idx], align='center') + plt.yticks(pos, np.array(feature_names)[sorted_idx]) + plt.xlabel('Feature Importance Score') + plt.title('Feature Importance') + self._save_plot('feature_importance') \ No newline at end of file From b7492dc0e9f5296ee31898567b7b7c9fd94f2818 Mon Sep 17 00:00:00 2001 From: Ethan <291938975@qq.com> Date: Wed, 27 Nov 2024 09:26:06 +1100 Subject: [PATCH 02/27] compare --- main.py | 338 +++++++------------------------------------- model_comparator.py | 239 +++++++++++++++++++++++++++++++ 2 files changed, 293 insertions(+), 284 deletions(-) create mode 100644 model_comparator.py diff --git a/main.py b/main.py index 03a82a1fc..8a36f2fa9 100644 --- a/main.py +++ b/main.py @@ -1,3 +1,8 @@ +""" +main.py +主程序入口文件 +""" + import os import sys import logging @@ -5,20 +10,12 @@ from contextlib import contextmanager from functools import wraps -# 以下是文件 +# 导入所需模块 from data_preprocessor import NSWDataPreprocessor from visualizer import DataVisualizer -from time_series_predictor import TimeSeriesPredictor -from prophet_predictor import ProphetPredictor -from MLP_predictor import MLPPredictor -from BNN_predictor import BNNPredictor -from CNN_predictor import CNNPredictor -from LSTM_predictor import LSTMPredictor -from XGBoost_ensemble import XGBoostEnsemblePredictor -from RandomForests_ensemble import RandomForestsPredictor - +from model_comparator import ModelComparator, run_comparison -# 输出Tee +# Tee类用于同时输出到控制台和文件 class Tee: def __init__(self, stdout, file): self.stdout = stdout @@ -42,17 +39,38 @@ def flush(self): except Exception as e: print(f"Tee flush error: {e}") + +# 定义输出重定向的上下文管理器 +@contextmanager +def tee_output(filename): + """ + 将输出同时重定向到文件和控制台的上下文管理器 + """ + try: + os.makedirs('logs', exist_ok=True) + with open(filename, 'w', encoding='utf-8') as file: + tee = Tee(sys.stdout, file) + old_stdout = sys.stdout + sys.stdout = tee + yield # 这里是关键，需要yield + sys.stdout = old_stdout + except Exception as e: + print(f"Error in tee_output: {e}") + sys.stdout = sys.__stdout__ # 确保发生错误时也能恢复stdout + + # 定义装饰器 -def log_function_name(func): - @wraps(func) # 保留原函数的元信息（如名称、文档字符串等） +def log_function(func): + @wraps(func) def wrapper(*args, **kwargs): - print(f"{'='*10}{func.__name__} is running {'='*20}") # 打印函数名称 - result = func(*args, **kwargs) # 执行原函数并保存返回值 - print(f"{'='*10}{func.__name__} is done {'='*20}\n") # 打印函数完成信息 - return result # 返回原函数的结果 + print(f"{'='*10}{func.__name__} is running {'='*20}") + result = func(*args, **kwargs) + print(f"{'='*10}{func.__name__} is done {'='*20}\n") + return result return wrapper -@log_function_name + +@log_function def check_data_files(): """ 检查必要的数据文件是否存在 @@ -68,13 +86,13 @@ def check_data_files(): return False return True -@log_function_name + +@log_function def process_data(): """ 数据处理步骤 """ try: - # 创建预处理器实例 preprocessor = NSWDataPreprocessor(window_size=1440) # 24小时 # 准备数据 @@ -100,13 +118,13 @@ def process_data(): logging.error(f"Error during data processing: {str(e)}") return None -@log_function_name + +@log_function def create_visualizations(df, feature_names, save_dir='data-preprocessor'): """ 创建数据可视化 """ visualizer = DataVisualizer(save_dir) - print("Starting data visualization...") # 绘制每日负载模式 @@ -117,229 +135,19 @@ def create_visualizations(df, feature_names, save_dir='data-preprocessor'): print("Data visualization completed successfully") -@log_function_name -def time_series(df): - """ - 示例使用方法 - """ - # 创建预测器实例 - predictor = TimeSeriesPredictor( - lookback_hours=48, - forecast_hours=48, - sample_interval='30T', - n_neighbors=5 - ) - - # 读取示例数据 - try: - save_dir = 'model-time_series' - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - predictions.to_csv(os.path.join(save_dir, 'time_series_predictions.csv'), index=False) - print("Predictions saved to CSV file") - - except Exception as e: - logging.error(f"Error in main execution: {str(e)}") - - -@log_function_name -def prophet_series(df): +@log_function +def compare_models(df): """ - 使用Prophet模型进行预测 + 比较不同模型的性能 """ - # 创建Prophet预测器实例 - predictor = ProphetPredictor( - forecast_hours=48, - sample_interval='30T' - ) + print("Starting model comparison...") - try: - save_dir = 'model-prophet' - os.makedirs(save_dir, exist_ok=True) - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - predictions.to_csv(os.path.join(save_dir, 'prophet_predictions.csv'), index=False) - print("Prophet predictions saved to CSV file") - - except Exception as e: - logging.error(f"Error in prophet execution: {str(e)}") - -@log_function_name -def mlp_prediction(df): - """ - 使用MLP模型进行预测 - """ - # 创建预测器实例 - predictor = MLPPredictor( - lookback_hours=48, # 使用过去48小时的数据 - forecast_hours=48, # 预测未来48小时 - sample_interval='30T', # 30分钟间隔 - ) - - try: - # 创建保存目录 - save_dir = 'modle-mlp' - os.makedirs(save_dir, exist_ok=True) - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) + comparator = ModelComparator() + comparator.compare_models(df) - if predictions is not None: - # 保存预测结果到CSV - predictions.to_csv(os.path.join(save_dir, 'mlp_predictions.csv'), index=False) - print("MLP predictions saved to CSV file") - return predictions + print("Model comparison completed") - except Exception as e: - logging.error(f"Error in MLP prediction: {str(e)}") - - -@log_function_name -def bnn_prediction(df): - """ - 使用BNN模型进行预测 - """ - # 创建预测器实例 - predictor = BNNPredictor( - lookback_hours=48, # 使用过去48小时的数据 - forecast_hours=48, # 预测未来48小时 - sample_interval='30T' # 30分钟间隔 - ) - - try: - # 创建保存目录 - save_dir = 'model-bnn' - os.makedirs(save_dir, exist_ok=True) - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - # 保存预测结果到CSV - predictions.to_csv(os.path.join(save_dir, 'bnn_predictions.csv'), index=False) - print("BNN predictions saved to CSV file") - return predictions - - except Exception as e: - logging.error(f"Error in BNN prediction: {str(e)}") - -@log_function_name -def cnn_prediction(df): - """ - CNN模型预测 - """ - predictor = CNNPredictor( - lookback_hours=48, - forecast_hours=48, - sample_interval='30T' - ) - - try: - save_dir = 'model-cnn' - os.makedirs(save_dir, exist_ok=True) - - print("Starting CNN prediction process...") - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - predictions.to_csv(os.path.join(save_dir, 'cnn_predictions.csv'), index=False) - print("CNN predictions saved to CSV file") - return predictions - - except Exception as e: - logging.error(f"Error in CNN prediction: {str(e)}") - print(f"CNN prediction failed with error: {str(e)}") - -@log_function_name -def lstm_prediction(df): - """ - 使用LSTM模型进行预测 - """ - # 创建预测器实例 - predictor = LSTMPredictor( - lookback_hours=48, # 使用过去48小时的数据 - forecast_hours=48, # 预测未来48小时 - sample_interval='30T' # 30分钟间隔 - ) - - try: - # 创建保存目录 - save_dir = 'model-lstm' - os.makedirs(save_dir, exist_ok=True) - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - # 保存预测结果到CSV - predictions.to_csv(os.path.join(save_dir, 'lstm_predictions.csv'), index=False) - print("LSTM predictions saved to CSV file") - return predictions - - except Exception as e: - logging.error(f"Error in LSTM prediction: {str(e)}") - -@log_function_name -def xgboost_prediction(df): - """ - Using XGBoost Ensemble model for prediction - """ - # Initialize predictor - predictor = XGBoostEnsemblePredictor( - lookback_hours=48, - forecast_hours=48, - sample_interval='30T' - ) - - try: - # Create save directory - save_dir = 'model-xgboost' - os.makedirs(save_dir, exist_ok=True) - - # Execute prediction - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - # Save predictions to CSV - predictions.to_csv(os.path.join(save_dir, 'xgboost_predictions.csv'), index=False) - print("XGBoost ensemble predictions saved to CSV file") - return predictions - - except Exception as e: - logging.error(f"Error in XGBoost prediction: {str(e)}") - -@log_function_name -def random_forest_prediction(df): - """ - 随机森林预测 - """ - # 创建预测器实例 - predictor = RandomForestsPredictor( - lookback_hours=48, - forecast_hours=48, - sample_interval='30T' - ) - - try: - save_dir = 'model-random_forest' - os.makedirs(save_dir, exist_ok=True) - - # 执行预测 - predictions = predictor.predict(df, save_dir=save_dir) - - if predictions is not None: - predictions.to_csv(os.path.join(save_dir, 'random_forest_predictions.csv'), index=False) - print("Random Forest predictions saved to CSV file") - - except Exception as e: - logging.error(f"Error in Random Forest prediction: {str(e)}") def main(): """ @@ -349,7 +157,6 @@ def main(): if not check_data_files(): return - # 数据处理 results = process_data() if results is None: @@ -358,54 +165,17 @@ def main(): X_train, X_test, y_train, y_test, feature_names, preprocessor, df = results + # 创建可视化 + create_visualizations(df, feature_names) - # # 创建可视化 - # create_visualizations(df, feature_names) - # - # # 模型-时间序列-负载 - # time_series(df) - # - # # 模型-prophet - # prophet_series(df) - # - # # 模型-MLP预测 - # mlp_prediction(df) - # - # # 模型-BNN预测 - # bnn_prediction(df) - # - # # 模型-CNN预测 - # cnn_prediction(df) - # - # # 模型-LSTM预测 - # lstm_prediction(df) - # - # # 模型-XGBoost集成预测 - # xgboost_prediction(df) - - # 随机森林预测 - random_forest_prediction(df) + # 执行模型比较 + compare_models(df) if __name__ == "__main__": - - @contextmanager - def tee_output(filename): - try: - os.makedirs('logs', exist_ok=True) - with open(filename, 'w', encoding='utf-8') as file: - tee = Tee(sys.stdout, file) - old_stdout = sys.stdout - sys.stdout = tee - try: - yield - finally: - sys.stdout = old_stdout - except Exception as e: - print(f"Error in tee_output: {e}") - - - # 使用方式 + # 设置运行时间 current_time = time.strftime("%Y%m%d_%H%M%S") + + # 使用重定向输出 with tee_output(f'logs/output_{current_time}.txt'): main() \ No newline at end of file diff --git a/model_comparator.py b/model_comparator.py new file mode 100644 index 000000000..87aee0c2b --- /dev/null +++ b/model_comparator.py @@ -0,0 +1,239 @@ +""" +model_comparator.py +用于比较不同负载预测模型性能的模块 +""" + +import pandas as pd +import numpy as np +from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score +import matplotlib.pyplot as plt +from typing import Dict, List, Optional +import os +import logging +from datetime import datetime + +# Import model predictors +from time_series_predictor import TimeSeriesPredictor +from prophet_predictor import ProphetPredictor +from MLP_predictor import MLPPredictor +from BNN_predictor import BNNPredictor +from CNN_predictor import CNNPredictor +from LSTM_predictor import LSTMPredictor +from XGBoost_ensemble import XGBoostEnsemblePredictor +from RandomForests_ensemble import RandomForestsPredictor + + +class ModelComparator: + """ + 用于比较不同模型性能的框架类 + """ + + def __init__(self, save_dir: str = 'comparison'): + """ + 初始化比较器 + + 参数: + save_dir: str - 结果保存目录 + """ + self.save_dir = save_dir + os.makedirs(save_dir, exist_ok=True) + self.models = {} + self.results = {} + self._initialize_models() + + def _initialize_models(self): + """ + 初始化所有要比较的模型 + """ + self.models = { + 'Time Series': TimeSeriesPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T', + n_neighbors=5 + ), + 'Prophet': ProphetPredictor( + forecast_hours=48, + sample_interval='30T' + ), + 'MLP': MLPPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ), + 'BNN': BNNPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ), + 'CNN': CNNPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ), + 'LSTM': LSTMPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ), + 'XGBoost': XGBoostEnsemblePredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ), + 'Random Forest': RandomForestsPredictor( + lookback_hours=48, + forecast_hours=48, + sample_interval='30T' + ) + } + + def _calculate_metrics(self, y_true: np.ndarray, y_pred: np.ndarray) -> Dict[str, float]: + """ + 计算各种评估指标 + """ + return { + 'MSE': mean_squared_error(y_true, y_pred), + 'RMSE': np.sqrt(mean_squared_error(y_true, y_pred)), + 'MAE': mean_absolute_error(y_true, y_pred), + 'R2': r2_score(y_true, y_pred), + 'MAPE': np.mean(np.abs((y_true - y_pred) / y_true)) * 100 + } + + def compare_models(self, df: pd.DataFrame): + """ + 比较所有模型的性能 + + 参数: + df: pd.DataFrame - 输入数据 + """ + print("Starting model comparison...") + print("=" * 80) # 开始分隔线 + + for model_name, model in self.models.items(): + print("=" * 80) # 方法之间的分隔线 + print(f"\nEvaluating {model_name} model...") + print(f"\n{'='*40} {model_name} Model {'='*40}") # 添加醒目的标题 + try: + # 创建模型专属保存目录 + model_dir = os.path.join(self.save_dir, f'model-{model_name.lower().replace(" ", "_")}') + os.makedirs(model_dir, exist_ok=True) + + # 预测 + start_time = datetime.now() + predictions = model.predict(df, save_dir=model_dir) + end_time = datetime.now() + + if predictions is not None: + # 计算执行时间 + execution_time = (end_time - start_time).total_seconds() + + # 获取最后48小时的实际值进行比较 + actual_values = df['load'].iloc[-96:] # 48小时，每30分钟一个数据点 + predicted_values = predictions['predicted_load'].values + + # 计算评估指标 + metrics = self._calculate_metrics(actual_values, predicted_values) + metrics['execution_time'] = execution_time + + self.results[model_name] = metrics + print(f"\n{model_name} Evaluation Results:") + print("-" * 60) # 添加结果分隔线 + print(f"Status: Successfully completed") + print(f"Execution time: {execution_time:.2f} seconds") + print("\nMetrics:") + print("-" * 40) # 添加指标分隔线 + for metric, value in metrics.items(): + print(f"{metric:15} : {value:.4f}") + print("\n" + "=" * 80) # 添加方法结束分隔线 + + except Exception as e: + print(f"Error evaluating {model_name}: {str(e)}") + continue + + # 生成比较报告 + self._generate_comparison_report() + + def _generate_comparison_report(self): + """ + 生成模型比较报告 + """ + if not self.results: + print("No results to compare") + return + + # 创建比较表格 + comparison_df = pd.DataFrame(self.results).round(4) + + # 保存比较结果 + comparison_df.to_csv(os.path.join(self.save_dir, 'model_comparison.csv')) + + # 绘制性能对比图 + self._plot_comparison() + + print("\nModel Comparison Summary:") + print(comparison_df) + + def _plot_comparison(self): + """ + 绘制模型性能对比图 + """ + metrics_to_plot = ['MSE', 'MAE', 'MAPE'] + num_metrics = len(metrics_to_plot) + + plt.figure(figsize=(15, 5 * num_metrics)) + + for i, metric in enumerate(metrics_to_plot, 1): + plt.subplot(num_metrics, 1, i) + + values = [self.results[model][metric] for model in self.results] + models = list(self.results.keys()) + + bars = plt.bar(models, values) + plt.title(f'Model Comparison - {metric}') + plt.xlabel('Models') + plt.ylabel(metric) + plt.xticks(rotation=45) + + # 添加数值标签 + for bar in bars: + height = bar.get_height() + plt.text(bar.get_x() + bar.get_width()/2., height, + f'{height:.2f}', + ha='center', va='bottom') + + plt.tight_layout() + plt.savefig(os.path.join(self.save_dir, 'model_comparison.png'), + dpi=300, bbox_inches='tight') + plt.close() + + +def run_comparison(temp_file: str, demand_file: str): + """ + 运行模型比较的主函数 + + 参数: + temp_file: str - 温度数据文件路径 + demand_file: str - 负载数据文件路径 + """ + from data_preprocessor import NSWDataPreprocessor + + print("Starting model comparison process...") + print("Initializing data preprocessor...") + + preprocessor = NSWDataPreprocessor(window_size=1440) # 24小时 + results = preprocessor.prepare_data(temp_file, demand_file) + + if results is not None: + _, _, _, _, _, df = results + + print("Data preprocessing completed") + print("Starting model comparator...") + + # 创建比较器并运行比较 + comparator = ModelComparator() + comparator.compare_models(df) + + print("Model comparison completed. Results saved in the model_comparison directory.") + else: + print("Error in data preprocessing. Cannot proceed with model comparison.") \ No newline at end of file From 24d5e06de1949e5264f8334d2e53f72f48d8f953 Mon Sep 17 00:00:00 2001 From: Ethan <291938975@qq.com> Date: Wed, 27 Nov 2024 14:34:53 +1100 Subject: [PATCH 03/27] result --- MLP_predictor.py | 12 +- data-preprocessor/daily_pattern.png | Bin 0 -> 205784 bytes data-preprocessor/temp_load_relationship.png | Bin 0 -> 2461959 bytes logs/output_20241127_035056.txt | 226 +++ logs/output_20241127_042136.txt | 51 + logs/output_20241127_043438.txt | 53 + logs/output_20241127_044658.txt | 70 + logs/output_20241127_055044.txt | 52 + logs/output_20241127_071832.txt | 1108 ++++++++++++ logs/output_20241127_093006.txt | 1537 +++++++++++++++++ model_comparator.py | 2 +- model_comparison/model-bnn/bnn_prediction.png | Bin 0 -> 357049 bytes model_comparison/model-cnn/cnn_prediction.png | Bin 0 -> 494589 bytes .../model-lstm/lstm_prediction.png | Bin 0 -> 464997 bytes model_comparison/model-mlp/mlp_prediction.png | Bin 0 -> 264438 bytes .../model-prophet/prophet_prediction.png | Bin 0 -> 252433 bytes .../random_forest_prediction.png | Bin 0 -> 221528 bytes .../time_series_prediction.png | Bin 0 -> 270688 bytes .../model-xgboost/xgboost_prediction.png | Bin 0 -> 211705 bytes model_comparison/model_comparison.csv | 7 + model_comparison/model_comparison.png | Bin 0 -> 500259 bytes prophet_predictor.py | 4 +- 22 files changed, 3108 insertions(+), 14 deletions(-) create mode 100644 data-preprocessor/daily_pattern.png create mode 100644 data-preprocessor/temp_load_relationship.png create mode 100644 logs/output_20241127_035056.txt create mode 100644 logs/output_20241127_042136.txt create mode 100644 logs/output_20241127_043438.txt create mode 100644 logs/output_20241127_044658.txt create mode 100644 logs/output_20241127_055044.txt create mode 100644 logs/output_20241127_071832.txt create mode 100644 logs/output_20241127_093006.txt create mode 100644 model_comparison/model-bnn/bnn_prediction.png create mode 100644 model_comparison/model-cnn/cnn_prediction.png create mode 100644 model_comparison/model-lstm/lstm_prediction.png create mode 100644 model_comparison/model-mlp/mlp_prediction.png create mode 100644 model_comparison/model-prophet/prophet_prediction.png create mode 100644 model_comparison/model-random_forest/random_forest_prediction.png create mode 100644 model_comparison/model-time_series/time_series_prediction.png create mode 100644 model_comparison/model-xgboost/xgboost_prediction.png create mode 100644 model_comparison/model_comparison.csv create mode 100644 model_comparison/model_comparison.png diff --git a/MLP_predictor.py b/MLP_predictor.py index 90b964537..f30da4d5a 100644 --- a/MLP_predictor.py +++ b/MLP_predictor.py @@ -32,17 +32,7 @@ def __init__(self, lookback_hours: int = 48, forecast_hours: int = 48, self.forecast_points = int(forecast_hours * 60 / int(sample_interval[:-1])) self.scaler = MinMaxScaler(feature_range=(0, 1)) - # 初始化MLPRegressor - self.model = MLPRegressor( - hidden_layer_sizes=(12, 6), # 两个隐藏层 - activation='relu', # ReLU激活函数 - solver='adam', # Adam优化器 - max_iter=500, # 最大迭代次数 - random_state=1, # 随机种子 - early_stopping=True, # 启用早停 - validation_fraction=0.1, # 验证集比例 - verbose=True # 显示训练进度 - ) + def _preprocess_data(self, df: pd.DataFrame) -> Tuple[pd.DataFrame, np.ndarray]: """ diff --git a/data-preprocessor/daily_pattern.png b/data-preprocessor/daily_pattern.png new file mode 100644 index 0000000000000000000000000000000000000000..ff3be0fca3cda6afe92579ded3b0b97741bf601c GIT binary patch literal 205784 zcmeFZXH->Lw=IfVhEfr$#6(t6!2l+Z3?(9BAV|)NV*>~=6z(szwKB;a;N5`{+{I|q8THKLt2_2ox z@jsNDLqD}SIp0>ESsbZ+eDgBrWr=={f(@%UI3ll&>ulT?`(%@n{GS<5)KnU^_dUtJ z_SARv+dUkY#i3vDUx;lKZJI+F58_P>9Ne8niTdey(a%e8`w<6qy5+!E>iuWx$mc`yCCx?=<3{NE>2Qj5$;7wK%IQxlceqt!RESWa+YHH@Nmjept)Qf2JkVV$AsO zfPesZcXy?y`Z9O+D4*K6M@c?OBctxA!RZXMM%m}jpD({{v7nJ{{qS`FyVW%*DXBL5 z4o&R>*NL?>l_U+5$xlsEx6h7DzS$jN+?;OW@7VM9PKM|FjJxh`-l-f;7Z;Z|B_+}e 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+Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========create_visualizations is running ==================== +Starting data visualization... +Plot saved: daily_pattern.png +Plot saved: temp_load_relationship.png +Data visualization completed successfully +==========create_visualizations is done ==================== + +==========time_series is running ==================== +Starting data preprocessing... +Preparing final prediction... +Prediction plot saved in model-time_series dir + +Prediction Summary: +Mean Load: 7759.02 MW +Standard Deviation: 811.98 MW +Maximum Load: 8765.72 MW +Minimum Load: 6022.73 MW +Predictions saved to CSV file +==========time_series is done ==================== + +==========prophet_series is running ==================== +Starting data preprocessing for Prophet... +Evaluating 4 parameter combinations + +Trying parameters: {'changepoint_prior_scale': 0.01, 'seasonality_prior_scale': 0.1, 'seasonality_mode': 'multiplicative', 'changepoint_range': 0.9, 'holidays_prior_scale': 0.1} +New best parameters found: MSE=714046.00, MAE=627.11 + +Trying parameters: {'changepoint_prior_scale': 0.01, 'seasonality_prior_scale': 1.0, 'seasonality_mode': 'multiplicative', 'changepoint_range': 0.9, 'holidays_prior_scale': 0.1} + +Trying parameters: {'changepoint_prior_scale': 0.1, 'seasonality_prior_scale': 0.1, 'seasonality_mode': 'multiplicative', 'changepoint_range': 0.9, 'holidays_prior_scale': 0.1} + +Trying parameters: {'changepoint_prior_scale': 0.1, 'seasonality_prior_scale': 1.0, 'seasonality_mode': 'multiplicative', 'changepoint_range': 0.9, 'holidays_prior_scale': 0.1} + +Training final model with best parameters... +Generating predictions... +Prophet prediction plot saved in model-prophet + +Prophet Prediction Summary: +Mean Load: 7376.20 MW +Standard Deviation: 737.93 MW +Maximum Load: 8487.17 MW +Minimum Load: 5812.36 MW +Prophet predictions saved to CSV file +==========prophet_series is done ==================== + +==========mlp_prediction is running ==================== +Starting data preprocessing... +Training MLP with input shape: (196321, 384), output shape: (196321, 96) +Training MLP model... +Iteration 1, loss = 0.00920350 +Validation score: 0.481993 +Iteration 2, loss = 0.00412950 +Validation score: 0.618449 +Iteration 3, loss = 0.00339593 +Validation score: 0.648816 +Iteration 4, loss = 0.00329091 +Validation score: 0.652145 +Iteration 5, loss = 0.00327207 +Validation score: 0.654476 +Iteration 6, loss = 0.00326314 +Validation score: 0.645126 +Iteration 7, loss = 0.00326057 +Validation score: 0.655551 +Iteration 8, loss = 0.00325184 +Validation score: 0.651492 +Iteration 9, loss = 0.00325084 +Validation score: 0.654697 +Iteration 10, loss = 0.00324281 +Validation score: 0.655979 +Iteration 11, loss = 0.00324129 +Validation score: 0.654256 +Iteration 12, loss = 0.00324187 +Validation score: 0.655269 +Iteration 13, loss = 0.00323397 +Validation score: 0.653328 +Iteration 14, loss = 0.00323641 +Validation score: 0.656570 +Iteration 15, loss = 0.00323215 +Validation score: 0.644460 +Iteration 16, loss = 0.00323102 +Validation score: 0.657357 +Iteration 17, loss = 0.00316942 +Validation score: 0.689658 +Iteration 18, loss = 0.00286501 +Validation score: 0.693026 +Iteration 19, loss = 0.00282105 +Validation score: 0.700872 +Iteration 20, loss = 0.00277451 +Validation score: 0.704992 +Iteration 21, loss = 0.00273984 +Validation score: 0.706571 +Iteration 22, loss = 0.00270316 +Validation score: 0.715044 +Iteration 23, loss = 0.00265040 +Validation score: 0.719574 +Iteration 24, loss = 0.00264572 +Validation score: 0.701690 +Iteration 25, loss = 0.00264240 +Validation score: 0.717739 +Iteration 26, loss = 0.00264460 +Validation score: 0.719615 +Iteration 27, loss = 0.00263677 +Validation score: 0.719306 +Iteration 28, loss = 0.00263830 +Validation score: 0.715078 +Iteration 29, loss = 0.00263662 +Validation score: 0.718256 +Iteration 30, loss = 0.00263325 +Validation score: 0.712170 +Iteration 31, loss = 0.00263457 +Validation score: 0.720390 +Iteration 32, loss = 0.00263868 +Validation score: 0.719452 +Iteration 33, loss = 0.00263170 +Validation score: 0.719926 +Iteration 34, loss = 0.00263131 +Validation score: 0.711501 +Iteration 35, loss = 0.00263418 +Validation score: 0.720609 +Iteration 36, loss = 0.00263214 +Validation score: 0.717648 +Iteration 37, loss = 0.00262802 +Validation score: 0.718670 +Iteration 38, loss = 0.00262666 +Validation score: 0.721282 +Iteration 39, loss = 0.00263357 +Validation score: 0.720730 +Iteration 40, loss = 0.00262629 +Validation score: 0.717898 +Iteration 41, loss = 0.00263230 +Validation score: 0.718397 +Iteration 42, loss = 0.00262452 +Validation score: 0.720468 +Iteration 43, loss = 0.00263103 +Validation score: 0.721004 +Iteration 44, loss = 0.00262877 +Validation score: 0.720748 +Iteration 45, loss = 0.00263220 +Validation score: 0.720830 +Iteration 46, loss = 0.00262512 +Validation score: 0.718996 +Iteration 47, loss = 0.00262939 +Validation score: 0.720696 +Iteration 48, loss = 0.00263310 +Validation score: 0.716757 +Iteration 49, loss = 0.00262653 +Validation score: 0.721724 +Iteration 50, loss = 0.00263181 +Validation score: 0.720864 +Iteration 51, loss = 0.00262494 +Validation score: 0.721349 +Iteration 52, loss = 0.00262373 +Validation score: 0.719162 +Iteration 53, loss = 0.00262850 +Validation score: 0.720724 +Iteration 54, loss = 0.00262581 +Validation score: 0.722057 +Iteration 55, loss = 0.00262647 +Validation score: 0.718365 +Iteration 56, loss = 0.00262661 +Validation score: 0.720743 +Iteration 57, loss = 0.00262608 +Validation score: 0.720318 +Iteration 58, loss = 0.00262488 +Validation score: 0.721060 +Iteration 59, loss = 0.00262917 +Validation score: 0.719473 +Iteration 60, loss = 0.00262659 +Validation score: 0.720705 +Iteration 61, loss = 0.00262206 +Validation score: 0.721932 +Iteration 62, loss = 0.00262243 +Validation score: 0.721256 +Iteration 63, loss = 0.00262461 +Validation score: 0.721521 +Iteration 64, loss = 0.00262406 +Validation score: 0.716821 +Iteration 65, loss = 0.00262187 +Validation score: 0.716992 +Validation score did not improve more than tol=0.000100 for 10 consecutive epochs. Stopping. +Model training completed +Generating predictions... +MLP prediction plot saved in modle-mlp + +MLP Prediction Summary: +Mean Load: 7665.38 MW +Standard Deviation: 683.52 MW +Maximum Load: 8767.79 MW +Minimum Load: 6273.44 MW +MLP predictions saved to CSV file +==========mlp_prediction is done ==================== + diff --git a/logs/output_20241127_042136.txt b/logs/output_20241127_042136.txt new file mode 100644 index 000000000..02b7b0622 --- /dev/null +++ b/logs/output_20241127_042136.txt @@ -0,0 +1,51 @@ +==========check_data_files is running ==================== +==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========bnn_prediction is running ==================== +Starting data preprocessing for BNN... +Training MC Dropout Network with input shape: (196321, 384), output shape: (196321, 96) +Training MC Dropout model... +Training completed - Final loss: 0.0063, Validation loss: 0.0069 +Generating predictions with MC Dropout sampling... +BNN prediction plot saved in model-bnn + +BNN Prediction Summary: +Mean Load: 7512.61 MW +Standard Deviation: 670.83 MW +Maximum Load: 8395.72 MW +Minimum Load: 6062.39 MW +Average Uncertainty: ±630.72 MW +BNN predictions saved to CSV file +==========bnn_prediction is done ==================== + diff --git a/logs/output_20241127_043438.txt b/logs/output_20241127_043438.txt new file mode 100644 index 000000000..18cee5aff --- /dev/null +++ b/logs/output_20241127_043438.txt @@ -0,0 +1,53 @@ +==========check_data_files is running ==================== +==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========cnn_prediction is running ==================== +Starting CNN prediction process... +Starting data preprocessing... +Training CNN with input shape: (196321, 96, 4), output shape: (196321, 96) +Training CNN model... +Model training completed +Generating predictions... + 1/1 [==============================] - ETA: 0s 1/1 [==============================] - 0s 68ms/step +CNN prediction plot saved in model-cnn + +CNN Prediction Summary: +Mean Load: 7427.82 MW +Standard Deviation: 699.68 MW +Maximum Load: 8589.69 MW +Minimum Load: 5925.34 MW +Minimum Load: 5925.34 MW +CNN predictions saved to CSV file +==========cnn_prediction is done ==================== + diff --git a/logs/output_20241127_044658.txt b/logs/output_20241127_044658.txt new file mode 100644 index 000000000..2dac21a78 --- /dev/null +++ b/logs/output_20241127_044658.txt @@ -0,0 +1,70 @@ +==========check_data_files is running ==================== +==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========lstm_prediction is running ==================== +Starting data preprocessing... +Training LSTM with input shape: (196321, 96, 4), output shape: (196321, 96) +LSTM model structure: +Model: "sequential" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + lstm (LSTM) (None, 96, 64) 17664 + + dropout (Dropout) (None, 96, 64) 0 + + lstm_1 (LSTM) (None, 32) 12416 + + dropout_1 (Dropout) (None, 32) 0 + + dense (Dense) (None, 96) 3168 + +================================================================= +Total params: 33248 (129.88 KB) +Trainable params: 33248 (129.88 KB) +Non-trainable params: 0 (0.00 Byte) +_________________________________________________________________ +Training LSTM model... +Generating predictions... + 1/1 [==============================] - ETA: 0s 1/1 [==============================] - 0s 381ms/step +LSTM prediction plot saved in model-lstm + +LSTM Prediction Summary: +Mean Load: 7521.27 MW +Standard Deviation: 564.28 MW +Maximum Load: 8328.67 MW +Minimum Load: 6271.63 MW +LSTM predictions saved to CSV file +==========lstm_prediction is done ==================== + diff --git a/logs/output_20241127_055044.txt b/logs/output_20241127_055044.txt new file mode 100644 index 000000000..b2e384e47 --- /dev/null +++ b/logs/output_20241127_055044.txt @@ -0,0 +1,52 @@ +==========check_data_files is running ==================== +==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========xgboost_prediction is running ==================== +Starting data preprocessing... +Created sequences with shape: X=(196321, 96, 11), y=(196321, 96) +Training XGBoost ensemble models... +Model 1 training completed +Model 2 training completed +Model 3 training completed +Generating predictions... +XGBoost prediction plot saved in model-xgboost + +XGBoost Ensemble Prediction Summary: +Mean Load: 425.44 MW +Standard Deviation: 188.70 MW +Maximum Load: 869.54 MW +Minimum Load: 119.85 MW +XGBoost ensemble predictions saved to CSV file +==========xgboost_prediction is done ==================== + diff --git a/logs/output_20241127_071832.txt b/logs/output_20241127_071832.txt new file mode 100644 index 000000000..2563c7d70 --- /dev/null +++ b/logs/output_20241127_071832.txt @@ -0,0 +1,1108 @@ +==========check_data_files is running ==================== +==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: 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+==========check_data_files is done ==================== + +==========process_data is running ==================== +Start with feature engineering. +Start creating sequences. + +Data preprocessing completed: +Training set shape: (153291, 1440, 19) +Test set shape: (38323, 1440, 19) +Number of features: 19 + +Feature list: +1. hour_sin +2. hour_cos +3. minute_sin +4. minute_cos +5. day_of_week_sin +6. day_of_week_cos +7. month_sin +8. month_cos +9. is_weekend +10. is_holiday +11. temperature +12. temp_rolling_mean_24h +13. temp_diff +14. temp_rolling_std_24h +15. load +16. load_rolling_mean_24h +17. load_rolling_std_24h +18. load_rolling_mean_7d +19. temp_load_interaction +==========process_data is done ==================== + +==========create_visualizations is running ==================== +Starting data visualization... +Plot saved: daily_pattern.png +Plot saved: temp_load_relationship.png +Data visualization completed successfully +==========create_visualizations is done ==================== + +==========compare_models is running ==================== +Starting model comparison... +Starting model comparison... +================================================================================ +================================================================================ + +Evaluating Time Series model... + +======================================== Time Series Model ======================================== +Starting data preprocessing... +Preparing final prediction... +Prediction plot saved in model_comparison\model-time_series dir + +Prediction Summary: +Mean Load: 7759.02 MW +Standard Deviation: 811.98 MW +Maximum Load: 8765.72 MW +Minimum Load: 6022.73 MW + +Time Series Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 1.31 seconds + +Metrics: +---------------------------------------- +MSE : 228035.7373 +RMSE : 477.5309 +MAE : 378.5029 +R2 : 0.5443 +MAPE : 5.0857 +execution_time : 1.3094 + +================================================================================ +================================================================================ + +Evaluating Prophet model... + +======================================== Prophet Model ======================================== +Starting data preprocessing for Prophet... +Evaluating 1 parameter combinations + +Trying parameters: {'changepoint_prior_scale': 0.01, 'seasonality_prior_scale': 0.1, 'seasonality_mode': 'multiplicative', 'changepoint_range': 0.9, 'holidays_prior_scale': 0.1} +New best parameters found: MSE=714046.00, MAE=627.11 + +Training final model with best parameters... +Generating predictions... +Prophet prediction plot saved in model_comparison\model-prophet + +Prophet Prediction Summary: +Mean Load: 7376.20 MW +Standard Deviation: 737.93 MW +Maximum Load: 8487.17 MW +Minimum Load: 5812.36 MW + +Prophet Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 129.34 seconds + +Metrics: +---------------------------------------- +MSE : 93393.4491 +RMSE : 305.6034 +MAE : 232.7323 +R2 : 0.8134 +MAPE : 3.1800 +execution_time : 129.3388 + +================================================================================ +================================================================================ + +Evaluating MLP model... + +======================================== MLP Model ======================================== +Starting data preprocessing... +Training MLP with input shape: (196321, 384), output shape: (196321, 96) +Training MLP model... +Iteration 1, loss = 0.00920350 +Validation score: 0.481993 +Iteration 2, loss = 0.00412950 +Validation score: 0.618449 +Iteration 3, loss = 0.00339593 +Validation score: 0.648816 +Iteration 4, loss = 0.00329091 +Validation score: 0.652145 +Iteration 5, loss = 0.00327207 +Validation score: 0.654476 +Iteration 6, loss = 0.00326314 +Validation score: 0.645126 +Iteration 7, loss = 0.00326057 +Validation score: 0.655551 +Iteration 8, loss = 0.00325184 +Validation score: 0.651492 +Iteration 9, loss = 0.00325084 +Validation score: 0.654697 +Iteration 10, loss = 0.00324281 +Validation score: 0.655979 +Iteration 11, loss = 0.00324129 +Validation score: 0.654256 +Iteration 12, loss = 0.00324187 +Validation score: 0.655269 +Iteration 13, loss = 0.00323397 +Validation score: 0.653328 +Iteration 14, loss = 0.00323641 +Validation score: 0.656570 +Iteration 15, loss = 0.00323215 +Validation score: 0.644460 +Iteration 16, loss = 0.00323102 +Validation score: 0.657357 +Iteration 17, loss = 0.00316942 +Validation score: 0.689658 +Iteration 18, loss = 0.00286501 +Validation score: 0.693026 +Iteration 19, loss = 0.00282105 +Validation score: 0.700872 +Iteration 20, loss = 0.00277451 +Validation score: 0.704992 +Iteration 21, loss = 0.00273984 +Validation score: 0.706571 +Iteration 22, loss = 0.00270316 +Validation score: 0.715044 +Iteration 23, loss = 0.00265040 +Validation score: 0.719574 +Iteration 24, loss = 0.00264572 +Validation score: 0.701690 +Iteration 25, loss = 0.00264240 +Validation score: 0.717739 +Iteration 26, loss = 0.00264460 +Validation score: 0.719615 +Iteration 27, loss = 0.00263677 +Validation score: 0.719306 +Iteration 28, loss = 0.00263830 +Validation score: 0.715078 +Iteration 29, loss = 0.00263662 +Validation score: 0.718256 +Iteration 30, loss = 0.00263325 +Validation score: 0.712170 +Iteration 31, loss = 0.00263457 +Validation score: 0.720390 +Iteration 32, loss = 0.00263868 +Validation score: 0.719452 +Iteration 33, loss = 0.00263170 +Validation score: 0.719926 +Iteration 34, loss = 0.00263131 +Validation score: 0.711501 +Iteration 35, loss = 0.00263418 +Validation score: 0.720609 +Iteration 36, loss = 0.00263214 +Validation score: 0.717648 +Iteration 37, loss = 0.00262802 +Validation score: 0.718670 +Iteration 38, loss = 0.00262666 +Validation score: 0.721282 +Iteration 39, loss = 0.00263357 +Validation score: 0.720730 +Iteration 40, loss = 0.00262629 +Validation score: 0.717898 +Iteration 41, loss = 0.00263230 +Validation score: 0.718397 +Iteration 42, loss = 0.00262452 +Validation score: 0.720468 +Iteration 43, loss = 0.00263103 +Validation score: 0.721004 +Iteration 44, loss = 0.00262877 +Validation score: 0.720748 +Iteration 45, loss = 0.00263220 +Validation score: 0.720830 +Iteration 46, loss = 0.00262512 +Validation score: 0.718996 +Iteration 47, loss = 0.00262939 +Validation score: 0.720696 +Iteration 48, loss = 0.00263310 +Validation score: 0.716757 +Iteration 49, loss = 0.00262653 +Validation score: 0.721724 +Iteration 50, loss = 0.00263181 +Validation score: 0.720864 +Iteration 51, loss = 0.00262494 +Validation score: 0.721349 +Iteration 52, loss = 0.00262373 +Validation score: 0.719162 +Iteration 53, loss = 0.00262850 +Validation score: 0.720724 +Iteration 54, loss = 0.00262581 +Validation score: 0.722057 +Iteration 55, loss = 0.00262647 +Validation score: 0.718365 +Iteration 56, loss = 0.00262661 +Validation score: 0.720743 +Iteration 57, loss = 0.00262608 +Validation score: 0.720318 +Iteration 58, loss = 0.00262488 +Validation score: 0.721060 +Iteration 59, loss = 0.00262917 +Validation score: 0.719473 +Iteration 60, loss = 0.00262659 +Validation score: 0.720705 +Iteration 61, loss = 0.00262206 +Validation score: 0.721932 +Iteration 62, loss = 0.00262243 +Validation score: 0.721256 +Iteration 63, loss = 0.00262461 +Validation score: 0.721521 +Iteration 64, loss = 0.00262406 +Validation score: 0.716821 +Iteration 65, loss = 0.00262187 +Validation score: 0.716992 +Validation score did not improve more than tol=0.000100 for 10 consecutive epochs. Stopping. +Model training completed +Generating predictions... +MLP prediction plot saved in model_comparison\model-mlp + +MLP Prediction Summary: +Mean Load: 7665.38 MW +Standard Deviation: 683.52 MW +Maximum Load: 8767.79 MW +Minimum Load: 6273.44 MW + +MLP Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 111.30 seconds + +Metrics: +---------------------------------------- +MSE : 153731.7066 +RMSE : 392.0864 +MAE : 331.0450 +R2 : 0.6928 +MAPE : 4.6261 +execution_time : 111.3041 + +================================================================================ +================================================================================ + +Evaluating BNN model... + +======================================== BNN Model ======================================== +Starting data preprocessing for BNN... +Training MC Dropout Network with input shape: (196321, 384), output shape: (196321, 96) +Training MC Dropout model... +Training completed - Final loss: 0.0063, Validation loss: 0.0070 +Generating predictions with MC Dropout sampling... +BNN prediction plot saved in model_comparison\model-bnn + +BNN Prediction Summary: +Mean Load: 7472.28 MW +Standard Deviation: 607.79 MW +Maximum Load: 8224.55 MW +Minimum Load: 6208.95 MW +Average Uncertainty: ±529.26 MW + +BNN Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 213.61 seconds + +Metrics: +---------------------------------------- +MSE : 123036.7962 +RMSE : 350.7660 +MAE : 296.6365 +R2 : 0.7542 +MAPE : 4.0508 +execution_time : 213.6127 + +================================================================================ +================================================================================ + +Evaluating CNN model... + +======================================== CNN Model ======================================== +Starting data preprocessing... +Training CNN with input shape: (196321, 96, 4), output shape: (196321, 96) +Training CNN model... +Model training completed +Generating predictions... + 1/1 [==============================] - ETA: 0s 1/1 [==============================] - 0s 64ms/step +CNN prediction plot saved in model_comparison\model-cnn + +CNN Prediction Summary: +Mean Load: 7493.13 MW +Standard Deviation: 677.13 MW +Maximum Load: 8695.31 MW +Minimum Load: 5932.81 MW +Minimum Load: 5932.81 MW + +CNN Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 432.57 seconds + +Metrics: +---------------------------------------- +MSE : 55068.2095 +RMSE : 234.6662 +MAE : 184.2542 +R2 : 0.8900 +MAPE : 2.5419 +execution_time : 432.5734 + +================================================================================ +================================================================================ + +Evaluating LSTM model... + +======================================== LSTM Model ======================================== +Starting data preprocessing... +Training LSTM with input shape: (196321, 96, 4), output shape: (196321, 96) +LSTM model structure: +Model: "sequential_2" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + lstm (LSTM) (None, 96, 64) 17664 + + dropout_4 (Dropout) (None, 96, 64) 0 + + lstm_1 (LSTM) (None, 32) 12416 + + dropout_5 (Dropout) (None, 32) 0 + + dense_7 (Dense) (None, 96) 3168 + +================================================================= +Total params: 33248 (129.88 KB) +Trainable params: 33248 (129.88 KB) +Non-trainable params: 0 (0.00 Byte) +_________________________________________________________________ +Training LSTM model... +Generating predictions... + 1/1 [==============================] - ETA: 0s 1/1 [==============================] - 0s 123ms/step +LSTM prediction plot saved in model_comparison\model-lstm + +LSTM Prediction Summary: +Mean Load: 7427.50 MW +Standard Deviation: 574.14 MW +Maximum Load: 8364.31 MW +Minimum Load: 6195.26 MW + +LSTM Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 1725.79 seconds + +Metrics: +---------------------------------------- +MSE : 48430.4226 +RMSE : 220.0691 +MAE : 164.2289 +R2 : 0.9032 +MAPE : 2.3129 +execution_time : 1725.7917 + +================================================================================ +================================================================================ + +Evaluating XGBoost model... + +======================================== XGBoost Model ======================================== +Starting data preprocessing... +Created sequences with shape: X=(196321, 96, 11), y=(196321, 96) +Training XGBoost ensemble models... +Model 1 training completed +Model 2 training completed +Model 3 training completed +Generating predictions... +XGBoost prediction plot saved in model_comparison\model-xgboost + +XGBoost Ensemble Prediction Summary: +Mean Load: 425.44 MW +Standard Deviation: 188.70 MW +Maximum Load: 869.54 MW +Minimum Load: 119.85 MW + +XGBoost Evaluation Results: +------------------------------------------------------------ +Status: Successfully completed +Execution time: 5117.24 seconds + +Metrics: +---------------------------------------- +MSE : 48953281.5478 +RMSE : 6996.6622 +MAE : 6955.7791 +R2 : -96.8176 +MAPE : 94.1405 +execution_time : 5117.2388 + +================================================================================ +================================================================================ + +Evaluating Random Forest model... + +======================================== Random Forest Model ======================================== +Starting data preprocessing... +Training Random Forest with input shape: (196321, 1056), output shape: (196321, 96) +Training Random Forest model... +Model training completed +Generating predictions... +Random Forest prediction plot saved in model_comparison\model-random_forest + +Random Forest Prediction Summary: +Mean Load: 7409.80 MW +Standard Deviation: 5.45 MW +Maximum Load: 7418.95 MW +Minimum Load: 7396.64 MW + +Feature Importance: +Feature importance: 0.0000 +Feature importance: 0.0000 +Feature importance: 0.0001 +Feature importance: 0.0001 +Feature importance: 0.0001 +Feature importance: 0.0005 +Feature importance: 0.0020 +Feature importance: 0.0001 +Feature importance: 0.0004 +Feature importance: 0.0005 +Feature importance: 0.0025 +Feature importance: 0.0000 +Feature importance: 0.0000 +Feature importance: 0.0001 +Feature importance: 0.0001 +Feature importance: 0.0001 +Feature importance: 0.0003 +Feature importance: 0.0007 +Feature importance: 0.0001 +Feature importance: 0.0002 +Feature importance: 0.0003 +Feature importance: 0.0009 +Feature importance: 0.0000 +Feature 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+------------------------------------------------------------ +Status: Successfully completed +Execution time: 6698.86 seconds + +Metrics: +---------------------------------------- +MSE : 501296.0283 +RMSE : 708.0226 +MAE : 542.5661 +R2 : -0.0017 +MAPE : 7.7113 +execution_time : 6698.8553 + +================================================================================ + +Model Comparison Summary: + Time Series Prophet ... XGBoost Random Forest +MSE 228035.7373 93393.4491 ... 4.895328e+07 501296.0283 +RMSE 477.5309 305.6034 ... 6.996662e+03 708.0226 +MAE 378.5029 232.7323 ... 6.955779e+03 542.5661 +R2 0.5443 0.8134 ... -9.681760e+01 -0.0017 +MAPE 5.0857 3.1800 ... 9.414050e+01 7.7113 +execution_time 1.3094 129.3388 ... 5.117239e+03 6698.8553 + +[6 rows x 8 columns] +Model comparison completed +==========compare_models is done ==================== + diff --git a/model_comparator.py b/model_comparator.py index 87aee0c2b..034b13cde 100644 --- a/model_comparator.py +++ b/model_comparator.py @@ -28,7 +28,7 @@ class ModelComparator: 用于比较不同模型性能的框架类 """ - def __init__(self, save_dir: str = 'comparison'): + def __init__(self, save_dir: str = 'model_comparison'): """ 初始化比较器 diff --git a/model_comparison/model-bnn/bnn_prediction.png b/model_comparison/model-bnn/bnn_prediction.png new file mode 100644 index 0000000000000000000000000000000000000000..3aaa8c5e37245a6712a80a92c0d9cc0c4acf0090 GIT binary patch literal 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