Weather-Forecast-Analysis

📄 Dataset Description

1. Weather Test Data.csv

• Raw weather test dataset
• Contains original, unprocessed weather records
• Used as input for cleaning and preprocessing

2. Weather_Test_Data_Cleaned.csv

• Cleaned version of the test dataset
• Missing values handled
• Data formatted and prepared for analysis or modeling

3. Weather_Data_Sampled_500 (1).csv

• Randomly sampled subset (500 records)
• Useful for faster experimentation and prototyping
• Reduces computation time for testing models

4. Weather_Data_Undersampled.csv

• Undersampled dataset
• Helps address class imbalance (if present)
• Suitable for training machine learning models

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🛠️ Tools & Technologies

• Python
• Pandas – data manipulation
• NumPy – numerical operations
• Matplotlib / Seaborn – data visualization
• Jupyter Notebook / Google Colab – analysis environment

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🔍 Project Workflow

1. Load raw weather data
2. Clean and preprocess the dataset
3. Create sampled and undersampled versions
4. Perform exploratory data analysis (EDA)
5. Prepare data for forecasting or machine learning models

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🚀 How to Use

1. Clone the repository:

   git clone https://github.com/iamkarandeepsingh/Weather-Forecast-Analysis.git
   cd Weather-Forecast-Analysis