MySleepProject

Overview

This project is a data science exploration using personal step and sleep data collected from a Xiaomi Mi Band 4 and 3rd party weather-related data obtained from Visual Crossing Weather Data Services. The analysis is performed using Python and Plotly for visualization.

Data Sources

Personal Data (Xiaomi Mi Band 4)

The personal health data includes step counts and sleep patterns collected using a Xiaomi Mi Band 4 fitness tracker. The data was exported from the associated mobile app and used for the analysis.

Third-Party Data (Visual Crossing Weather Data Services)

The third-party data consists of weather-related information such as temperature, humidity, moon phase, etc., obtained from Visual Crossing Weather Data Services. The data is collected at regular intervals and provides additional context for understanding potential correlations between personal health metrics and environmental conditions.

Tools and Technologies Used

• Python: The analysis is performed using Python programming language.
• Plotly: Plotly is used for creating interactive and informative visualizations.

Project Structure

• data/: Contains the raw and processed datasets.
• visualizations/: Visualizations generated from the analysis.

Installation

1. Clone the repository:

git clone https://github.com/your-username/your-repository.git
cd your-repository

pip install pandas

pip install plotly

pip install seaborn

pip install statsmodels