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dataset 2 - Sleep and Health Metrics

✓ Published0🌍 Public
YYiyi Wu
Last edited Sep 11, 2024
Created on Sep 9, 2024

This example visualizes the first row of a synthetic sleep and health metrics dataset from Kaggle, displaying its raw JSON structure in a large monospaced font. The code loads the CSV data, converts string values to numbers for all nine numeric fields, and then renders the first record’s key-value pairs inside a preformatted HTML block. It uses the `data.csv` import and the `container.innerHTML` assignment to present the data as-is, offering a minimal, non-interactive preview of the dataset before deeper analysis.

AI-generated description

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.
MIT Licensed

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