This project analyzes the influence of lifestyle habits on sleep efficiency, exploring the impact of choices like caffeine and alcohol consumption, smoking, and exercise on sleep patterns.
The dataset used in this project was collected by ENSIAS AI engineering students and includes self-reported surveys, actigraphy, and polysomnography data from a study in Morocco.
We preprocessed the data to address missing values and transformed it to better reflect the lifestyle impacts on sleep efficiency. Key insights were obtained through Exploratory Data Analysis (EDA), highlighting significant correlations.
Design choices in our Tableau visualizations were made to enhance clarity and understanding, with monochromatic color schemes representing different sleep states and lifestyle factors.
View the interactive dashboard
- Julius Maliwat
- Alexandre Crivellari
- Alessandro Rota
- Muluken Bogale Megersa