📊 Streamlit Visualization Dashboard

An interactive dashboard built with Python, Streamlit, and Plost. This project demonstrates how to build a responsive layout with sidebar controls, custom CSS styling, and various data visualization techniques including Heatmaps, Donut charts, and Line charts.

🖼️ Preview

🚀 Features

The application features a "wide" layout with an expanded sidebar for user controls:

• Key Metrics: Real-time display of Temperature, Wind, and Humidity (static example data).
• Interactive Heatmap: Visualizes Seattle weather patterns over time.
  • Control: Toggle coloring by Minimum (temp_min) or Maximum (temp_max) temperature.
• Donut Chart: Displays stock distribution data.
  • Control: Switch between quarters (q2 or q3).
• Line Chart: Tracks weather trends.
  • Control: Multi-select data to compare (temp_min, temp_max) and adjust graph height via a slider.
• Custom Styling: Integrates external CSS for UI enhancements.

🛠️ Tech Stack

• Streamlit: The core framework for the web application.
• Pandas: Used for data manipulation and CSV reading.
• Plost: A wrapper around Altair to simplify plotting in Streamlit.

📂 Project Structure

├── style.css            # Custom CSS styling file
├── dashboard.py         # Main application script
├── README.md            # Project documentation
└── requirements.txt     # Python dependencies