# 🏃‍♂️ Jogging Dashboard

An interactive Python Dash app to visualize, analyze, and explore your jogging or running sessions recorded as GPX/FIT files.

<p align="left">
    <img src="WebAppFITDashboard.png" alt="Description" width="800">
</p>

---

## Features

- **Info Banner** with total distance, duration, and average pace  
- **Interactive Map View** with route trace and start/stop markers  
- **Elevation Profile** with relative height and gradient fill  
- **Speed Over Time** plot with smoothing and average line 
- **Heart Rate Over Time** plot with smoothing and average line (if .fit)
- **Deviation from Mean Speed** to see pacing consistency  
- **Pace Bar Chart** showing per-kilometer pace breakdown  

---

## Project Structure

```
gpx_app.py             # Main Dash application for gpx files
gpx_files/             # Folder for storing GPX files
fit_app.py             # Main Dash application for fit files
fit_files/             # Folder for storing FIT files
requirements.txt       # Required Python packages
README.md              # This file
```

---

## Getting Started

### 1. Clone the repository

```bash
git clone https://github.com/yourusername/jogging-dashboard.git
cd jogging-dashboard
```

### 2. Install dependencies

We recommend using a virtual environment:

```bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt
```

**Content of the requirements.txt file**:
- dash
- dash-bootstrap-components
- plotly
- pandas
- numpy
- scipy
- gpxpy
- fitparse


### 3. Run the app

```bash
python fit_app.py
```

Then open your browser and go to:  
[http://127.0.0.1:8050](http://127.0.0.1:8050)

---

## Uploading Your GPX File

1. Export your activity (e.g., from Strava, Garmin, etc.) as a `.gpx` or `.fit` file  
2. Place the file into the `gpx_files/` or `fit_files/` directory  
3. Select it via the dropdown in the dashboard

---

## Tech Stack

- **Dash** (by Plotly) for building the UI and graphs  
- **Pandas** for data wrangling  
- **Plotly Graph Objects & Express** for advanced visuals  
- **Scipy** for smoothing the data lines
- **GPXPy** for parsing `.gpx` files  
- **Numpy** for vectorized math and smoothing  
- **FitParse** for  parsing `.fit` files

---

## Example GPX File

You can test the dashboard by either placing any valid `.gpx` file in the `gpx_files/` or any valid `.fit` file in the `fit_files/` directory. Make sure it contains track points with elevation and time data.

---

## To Do / Ideas

- [X] Heart rate support if present in FIT  
- [ ] Export as PDF report  
- [ ] Multi-run comparison  

---

## License

This project is open source under the [MIT License](LICENSE).

---

## Feedback / Contributions

Feel free to open issues or pull requests!  
If you enjoy this project, a ⭐️ star is always appreciated.