https://github.com/jsimell/sleepanalysis

A Python data analysis project analyzing the sleep quality affecting factors and temporal patterns in the sleeping data of a single subject.
https://github.com/jsimell/sleepanalysis

data-analysis matplotlib numpy pandas python scikit-learn seaborn

Last synced: 2 months ago
JSON representation

A Python data analysis project analyzing the sleep quality affecting factors and temporal patterns in the sleeping data of a single subject.

• Host: GitHub
• URL: https://github.com/jsimell/sleepanalysis
• Owner: jsimell
• License: mit
• Created: 2024-02-06T12:05:45.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-01-19T11:03:20.000Z (over 1 year ago)
• Last Synced: 2025-07-22T23:50:39.766Z (11 months ago)
• Topics: data-analysis, matplotlib, numpy, pandas, python, scikit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 2.37 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Subject Level Sleep Analysis

This simple data analysis project analyzes the sleeping data of a single subject with the aim of revealing interesting subject-level observations. More specifically, the analysis focuses on the sleep quality affecting factors and temporal patterns in the data. The dataset is a Kaggle dataset from Dana Diotte, obtained from: https://www.kaggle.com/datasets/danagerous/sleep-data?select=sleepdata_2.csv. The analysis was performed with Python and the utilized libraries are: Pandas, NumPy, scikit-learn, Matplotlib, and Seaborn.

![image](https://github.com/jsimell/SleepAnalysis/assets/96237825/28792c7b-2abb-403a-98cc-3dd43a9d33b4)

# Files

- The jupyter notebook containing the Python data-analysis code can be found in the `/code` folder.

- The project report is located in the `/report` folder.

- The `/data` folder contains the original unprocessed dataset.

# Credits

This project was carried out in the Aalto University CS-C4100 - Digital Health and Human Behaviour course during the fall of 2023. The responsible teacher of the course was Talayeh Aledavood.