{"id":45377195,"url":"https://github.com/derdilla/rowstats","last_synced_at":"2026-02-21T16:32:55.359Z","repository":{"id":284767676,"uuid":"954208747","full_name":"derdilla/rowstats","owner":"derdilla","description":"A Python tool for processing and visualizing rowing stroke data from CSV files. 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It reads raw data, processes movement direction, and generates an interactive visualization for performance analysis.\n\n## Table of Contents\n\n- [Features](#features)\n- [Installation](#installation)\n- [Usage Guide](#usage-guide)\n- [Hacking Guide](#hacking-guide)\n- [License](#license)\n\n## Features\n\n✅ Reads stroke data from CSV files  \n✅ Cleans and processes data automatically  \n✅ Identifies boat movement direction (up/down)  \n✅ Generates an interactive HTML visualization  \n✅ Works with multiple CSV files  \n\n## Installation\n\n1. Install [Python](https://www.python.org/) (version 3.8 or later).  \n2. Download or clone this repository:\n   ```sh\n   git clone https://github.com/derdilla/rowstats.git\n   cd rowstats\n   ```\n3. Launch a venv\n   ```sh\n   python -m venv venv\n   source venv/bin/activate\n   ```\n4. Install dependencies:\n   ```sh\n   pip install -r requirements.txt\n   ```\n\n## Usage Guide\n\n1. Place your CSV files inside the `csv-samples/` directory.  \n2. Run the program:\n   ```sh\n   python main.py\n   ```\n3. After the script finishes, open `index.html` in a web browser to view the results.\n\n## Hacking Guide\n\nWant to modify or improve the tool? Here’s how:\n\n### Understanding the Code Structure\n\n- `main.py` → The main script that processes data and generates the visualization.\n- `requirements.txt` → Lists all required dependencies.\n- `csv-samples/` → Folder where you should place your CSV files.\n- `index.html` → The output visualization file.\n\n### Making Changes\n\n#### 1. Modify the Data Processing Logic\n- Open `main.py` and locate the `split_frames()` function.\n- This function determines the boat’s movement direction and applies filtering.\n- Modify it to adjust stroke rate thresholds, data cleaning logic, or direction detection.\n\n#### 2. Customize the Visualization\n- Locate the `draw()` function in `main.py`.\n- Modify the Altair chart settings to change colors, axes, or tooltips.\n- Save changes and re-run `python main.py`.\n\n#### 3. Add New Features\n- Want to add extra analysis, like heart rate trends? Find the section where `get_table()` extracts CSV data.\n- Extend the code to include new metrics in the visualization.\n\n### Debugging \u0026 Testing\n- If something goes wrong, check for error messages in the console.\n- Use `print()` statements or Python’s built-in `logging` module to debug.\n- Test your changes with sample CSV files before running large datasets.\n\n## License\n\nThis project is licensed under the MIT License. Feel free to use, modify, and distribute it as you like!\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderdilla%2Frowstats","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fderdilla%2Frowstats","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fderdilla%2Frowstats/lists"}