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MiBandDataVisualization

This project is about the real extraction of Data from MI Fitness Band using selenium and applying some anatomization and visualization on real data such as your health monitoring.
Note: Make sure that while using our web app, you put your business or educational email id which is attached to your MI Fit App on your smartphone.
















Languages Used:

1. Python 2. HTML/CSS

Python Libraries/ Framework used:

1. Streamlit 2. Selenium 3. Altair 4. Autoviz 5. Matplotlib 6. Numpy 7. Pandas 8. Plotly 9. Pyperclip 10. Scikit-Learn 11. Scipy 12. Seaborn 13. Sklearn 14. Statsmodels 15. Twilio

How to run this analysis in your local machine

  1. Check your chrome version : Open chrome > At the top right, look at More > Click Help > About Chrome.
  2. Go to https://chromedriver.chromium.org/downloads and download suitable chrome driver according to your chrome version.
  3. Move the downloaded driver to C:\Program Files (x86)
  4. Clone This Project: git clone https://github.com/yashagg2001/MiBandDataVisualization.git
  5. Go to Project Directory: cd MIBandDataVisualization
  6. Create a Virtual Environment: python -m venv miui (for windows)
  7. Activate Virtual Environment: miui\Scripts\activate.bat (for windows)
  8. Install Requirements Package: pip install -r requirements.txt
  9. Run: streamlit run user_interface.py

To deactivate virtual environment: deactivate or miui\Scripts\deactivate
To delete virtual environment (simply delete folder miui): rmdir miui /s

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