Enhance WardhaMetroFlow with Historical Analytics & Export Features #180
Description
📋 Issue Description
WardhaMetroFlow is an interactive Streamlit dashboard that visualizes real-time congestion levels across Wardha Metro stations. Currently, the application provides a basic heatmap view with simulated congestion data and a simple refresh mechanism. We're looking to enhance this prototype with historical data tracking, trend analytics, and data export capabilities to make it more useful for both passengers and metro administrators.
🎯 Objective
Add three key features to transform WardhaMetroFlow from a simple real-time viewer into a comprehensive congestion analysis tool:
Historical Data Logging - Track congestion levels over time
Trend Visualization - Display congestion patterns with line charts
CSV Export Functionality - Enable data download for external analysis
🔧 Proposed Changes
Feature 1: Historical Data Storage
Implement a data structure (using st.session_state) to store congestion readings with timestamps
Each refresh should append new data points to the historical log
Include a "Clear History" button to reset accumulated data
Store data format: {timestamp, station_name, congestion_percentage}
Feature 2: Analytics Dashboard Tab
Add a new page option "Analytics" to the sidebar navigation
Create line charts showing congestion trends over time for each station
Use Plotly or Matplotlib for interactive visualizations
Display statistics: average congestion, peak times, min/max values per station
Add filters to view data by:
Time range (last 10 refreshes, last hour, etc.)
Individual stations or all stations combined
Congestion level thresholds (e.g., only show red-level incidents)
Feature 3: Export Functionality
Add a "Download Data" button that exports historical data as CSV
Include both summary statistics and raw timestamped readings
Format the CSV with proper headers and human-readable timestamps
Bonus: Add option to export the current map view as a PNG image
💡 Implementation Suggestions
python# Example structure for historical data
if "history" not in st.session_state:
st.session_state["history"] = []
On each refresh, append to history
timestamp = datetime.now()
for station, level in congestion_levels.items():
st.session_state["history"].append({
"timestamp": timestamp,
"station": station,
"congestion": level
})
✅ Acceptance Criteria
Historical data persists across refreshes within the same session
Analytics page displays at least one line chart showing congestion trends
CSV export downloads successfully with proper formatting
Code follows existing style and structure conventions
No breaking changes to existing "About" and "This App" pages
Documentation updated in the About section to describe new features
🚀 Getting Started
Fork the repository and create a new branch: feature/historical-analytics
Set up the development environment:
bash pip install streamlit pandas numpy folium streamlit-folium plotly
Test your changes locally: streamlit run app.py
Submit a pull request with a clear description of your implementation
🏷️ Labels
hacktoberfest good-first-issue enhancement python streamlit data-visualization
📚 Resources
Streamlit Session State Documentation
Plotly Python Graphing Library
Pandas DataFrame to CSV
🤝 Contributing
We welcome contributions from developers of all skill levels! This is a great opportunity to work with real-world data visualization tools and contribute to an open-source project. Feel free to ask questions in the comments if you need clarification on any aspect of the implementation.
Estimated Difficulty: Intermediate
Time Commitment: 4-6 hours
Skills Required: Python, Streamlit, Pandas, Data Visualization
Happy coding! 🎃👻
@Manjushwarofficial please assign this to me