RunningDataWithPy

A Python-based data visualization project that analyzes and displays running data, including elevation, pace, splits, and shoe usage. This project utilizes data from Strava and enhances insights through interactive visualizations using streamlit

Features

• 📊 Data Visualization – Generate interactive graphs for pace, elevation, and splits
• 👟 Shoe Usage Analysis – Track how different shoes affect performance
• ⏱ Average Pace Calculation – Compare paces across different runs
• ⛰ Elevation Insights – Visualize elevation gains
• 📁 CSV Support – Load running data from CSV files
• 📄 PDF Friendly – Dowload the graph in a PDF format
• 🔍 Filters & Analytics – Apply filters to analyze specific trends
• 🌐 Streamlit – User-friendly interface for easy data exploration
• ☁️ MongoDB Atlas Integration – Store and retrieve running data from the cloud

Installation

1. Clone the repository:

   git clone https://github.com/Sah2Sah2/RunningDataWithPy.git

2. Navigate to the project folder:

   cd RunningDataWithPy

3. Install dependencies:

   pip install -r requirements.txt

Usage

1. Ensure you have your running data in CSV format

   (If you use Strava, you can easily download a copy of your data by accessing your account from a desktop)

2. Run the Streamlit app:

streamlit run app.py

3. Open the provided URL in your browser to interact with the visualizations

4. Follow on-screen prompts to visualize and analyze data

Dependencies

• Python 3.x
• Pandas
• Matplotlib
• Seaborn
• Numpy
• Streamlit
• MongoDB Atlas (for cloud-based data storage)

Author

Sara Battistella

License

This project is licensed under the MIT License Copyright (c) [2025] [Sara Battistella]