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Fitness Tracker Dataset

Synthetic fitness data for analyzing health trends and optimizing workouts

@kaggle.arnavsmayan_fitness_tracker_dataset

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About this Dataset

Fitness Tracker Dataset

This dataset contains synthetic data collected from fitness trackers, detailing users' daily activities, exercise routines, heart rates, sleep patterns, and calorie consumption. It is designed to analyze health and fitness trends, optimize workout plans, and promote healthy lifestyle choices.

Columns:

  1. user_id: Unique identifier for each user.
  2. date: Date of the recorded data.
  3. steps: Number of steps taken.
  4. calories_burned: Total calories burned.
  5. distance_km: Distance covered in kilometers.
  6. active_minutes: Minutes spent in physical activity.
  7. sleep_hours: Hours of sleep.
  8. heart_rate_avg: Average heart rate.
  9. workout_type: Type of workout performed (e.g., Running, Walking, Cycling).
  10. weather_conditions: Weather conditions during the activity (e.g., Clear, Rain, Snow, Fog).
  11. location: Location of the activity (e.g., Home, Gym, Park).
  12. mood: Mood of the user (e.g., Happy, Neutral, Tired, Stressed).

The dataset can be used to track physical activity, monitor health metrics, personalize fitness programs, and study the effects of different exercises on health.

Tables

Fitness Tracker Dataset

@kaggle.arnavsmayan_fitness_tracker_dataset.fitness_tracker_dataset
  • 14.18 MB
  • 1000000 rows
  • 12 columns
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CREATE TABLE fitness_tracker_dataset (
  "user_id" BIGINT,
  "date" TIMESTAMP,
  "steps" BIGINT,
  "calories_burned" DOUBLE,
  "distance_km" DOUBLE,
  "active_minutes" BIGINT,
  "sleep_hours" DOUBLE,
  "heart_rate_avg" BIGINT,
  "workout_type" VARCHAR,
  "weather_conditions" VARCHAR,
  "location" VARCHAR,
  "mood" VARCHAR
);

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