Dataset Overview The Comprehensive Sleep and Health Metrics dataset is a fully synthetic dataset designed to explore the impact of various factors on sleep quality and overall health. By simulating a wide range of scenarios, this dataset provides a rich resource for predictive modeling and in-depth analysis. The synthetic nature of the data ensures that it captures a broad spectrum of potential variations and interactions related to sleep and health.

Dataset Breakdown This dataset is composed of diverse synthetic metrics, which include:

• Heart Rate Variability: Modeled data showing variations in the intervals between heartbeats.
• Body Temperature: Simulated readings of body temperature in Celsius.
• Movement During Sleep: Artificial data tracking movement levels during sleep.
• Sleep Duration Hours: Generated values representing total hours of sleep.
• Sleep Quality Score: A computed score reflecting the quality of sleep.
• Caffeine Intake (mg): Simulated measurements of daily caffeine consumption in milligrams.
• Stress Level: A synthetic index representing stress levels.
• Bedtime Consistency: Modeled data assessing the regularity of bedtime routines, scored on a scale from 0 to 1, with lower values indicating more inconsistency.
• Light Exposure Hours: Simulated data representing the number of daylight hours a person is exposed to during the day.

Identify Tasks for your Datasets:

• I want to summarize the distribution of Sleep Duration Hours across all individuals.
• I want to identify outliers in the Caffeine Intake mg data.
• I want to compare the correlation between Body Temperature and Sleep Quality Score.
• I want to explore unexpected patterns in Heart Rate Variability and Movement During Sleep.
• I want to present the trend of Stress Level over time.

Link to the original source: https://www.kaggle.com/datasets/uom190346a/sleep-and-health-metrics/data