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Open Source Daily Tracker Data
Public Health & Epidemiology
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About
This collection of open source activity tracker data is designed for pattern recognition and analytical purposes. The records provide detailed daily metrics collected from consented Fitbit users, encompassing steps taken, distance travelled, minutes spent across various activity intensity levels, and calories burned. This specific release is intended to supplement datasets used in academic or professional data analytics case studies, such as the Google Data Analytics Capstone Bellabeat study, ensuring broader temporal coverage for analysis.
Columns
The dataset includes 15 unique fields detailing user activity:
- Id: A numerical identifier assigned to each user.
- ActivityDate: The date on which the activity was recorded, presented in MM/DD/YYYY format.
- TotalSteps: The count of all steps recorded for the day.
- TotalDistance: The aggregate distance travelled.
- TrackerDistance: The distance specifically measured by the wearable device.
- LoggedActivitiesDistance: Distance accounted for by activities manually logged by the user.
- VeryActiveDistance: Distance travelled during periods classified as very active intensity.
- ModeratelyActiveDistance: Distance travelled during periods classified as moderate intensity.
- LightActiveDistance: Distance travelled during periods classified as light activity.
- SedentaryActiveDistance: Distance recorded during periods of inactivity.
- VeryActiveMinutes: The total duration, in minutes, spent engaging in very active intensity exercise.
- FairlyActiveMinutes: The total duration, in minutes, spent engaging in fairly active intensity exercise.
- LightlyActiveMinutes: The total duration, in minutes, spent engaging in light activity.
- SedentaryMinutes: The total duration, in minutes, recorded as being sedentary.
- Calories: The total caloric expenditure recorded for the day.
Distribution
This dataset is supplied as a CSV file (
dailyActivity_merged.csv). The file size is approximately 51.26 kB and contains data structured across 15 columns. The file contains 457 valid records relating to daily activity metrics.Usage
The data is ideally suited for academic research into physical activity patterns and sedentary behaviour. Potential applications include developing algorithms for habit recognition, studying the correlation between activity variables (e.g., steps vs. calories), and assessing user engagement with fitness trackers. It is highly valuable for use in public health modelling and business analytics related to wellness products.
Coverage
The data was generated by 30 eligible Fitbit users who consented to share their personal tracker data after responding to a distributed survey via Amazon Mechanical Turk. The activity records primarily cover dates ranging from 12 March 2016 to 12 April 2016, though the wider survey distribution occurred between 03 December 2016 and 05 December 2016.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For training models that predict daily caloric burn or step count.
- Health Researchers: For investigating population-level physical activity trends and sedentary time.
- Students: For performing exploratory data analysis (EDA) and fulfilling requirements for data analytics capstone projects.
- Fitness Professionals: For benchmarking typical activity levels and understanding user engagement.
Dataset Name Suggestions
- Fitbit Daily Activity Metrics
- Open Source Daily Tracker Data
- 2016 User Activity Records
- Health and Fitness Daily Metrics
Attributes
Original Data Source: Open Source Daily Tracker Data
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