The sleep and health Dataset, loaded and parsed as CSV.

Tasks

• Explore how sleep duration is distributed
• Analyze correlations between sleep and health outcomes (BMI, heart rate, ...)
• Compare how sleep and health patterns vary across different demographic groups
• how sleep quality changes over time and whether it aligns with changes in health metrics.
• Compare Sleep Patterns Across Weekdays vs. Weekends

Dataset Introduction

Metrics dataset is a fully synthetic collection designed to provide an extensive overview of how various factors might influence sleep quality and overall health. This dataset is created to simulate a wide range of scenarios and conditions, offering a robust foundation for predictive modeling and analytical studies. By utilizing synthetic data, the dataset ensures a comprehensive representation of potential variations and interactions in sleep and health metrics.

Dataset Description

The dataset includes a diverse array of synthetic measurements, covering:

• Heart Rate Variability: Simulated variability in time intervals between heartbeats.
• Body Temperature: Artificially generated body temperature in degrees Celsius.
• Movement During Sleep: Synthetic data on the amount of movement while sleeping.
• Sleep Duration Hours: Total hours of sleep generated through simulation.
• Sleep Quality Score: A synthetic score representing the quality of sleep.
• Caffeine Intake (mg): Amount of simulated caffeine consumption in milligrams.
• Stress Level: An index of simulated stress levels.
• Bedtime Consistency: Simulated consistency of bedtime routine. 0-1 scale, where lower values indicate more inconsistency.
• Light Exposure Hours: Synthetic hours of light exposure during the day. Reflects typical daylight exposure hours.