Sleep Analysis Project

The project is aimed at helping people with sleep fragmentation and health data from a consumer wearable. The python program analyzes my RingConn Gen 2 sleep data and generates graphical and statistical analysis of useful patterns.

This repository contains code and resources for analyzing sleep, activity, and vitals data. It includes data cleaning, merging, statistical analysis, and visualization scripts, as well as Jupyter notebook support for interactive exploration.

Features

• Data ingestion and cleaning
• Sleep, activity, and vitals data merging
• Statistical analysis (REM efficiency, nap effects, HRV)
• Visualizations (scatter plots, box plots, heatmaps)
• Jupyter notebook support

Getting Started

1. Clone the repository.
2. Install dependencies: pip install -r requirements.txt
3. The repository includes the raw data file AllRawData.csv and the results of the analysis (plots and analysis_results.txt).
4. Run sleep_analysis.py or open the notebook for interactive analysis. Results and plots will be generated in the repository root.

Project Structure

• sleep_analysis.py — Main analysis script
• notebooks/ — Jupyter notebooks for exploration
• data/ — Contains raw data files (e.g., AllRawData.csv). Place any additional datasets here.
• results/ — Contains analysis outputs:
  • analysis_results.txt — Text summary of analysis
  • rem_efficiency_scatter.png, nap_effect_latency.png, hrv_fragmentation.png, sleep_fragment_24h.png — Plots generated by the analysis
• requirements.txt — Python dependencies
• .github/ — Copilot and GitHub configuration

Data and Results Directories

data/: This folder contains the raw data file(s) used for analysis. For example, AllRawData.csv should be placed here. You may add other datasets as needed.

results/: This folder contains the outputs generated by running the analysis, including plots and the summary text file. These files are included in the repository for reference and reproducibility.

License

MIT