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Wearable Fitness Tracker Daily Data
Data Science and Analytics
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About
Explore minute-level personal tracker data from thirty Fitbit users, gathered through a survey on Amazon Mechanical Turk. This information includes physical activity, heart rate, and sleep monitoring, offering valuable insights into individual tracking behaviours and preferences. The data allows for pattern recognition to understand and potentially improve overall health.
Columns
- Id: A unique integer identifier for each subject.
- ActivityDate: The date of the activity, recorded in mm/dd/yyyy format.
- TotalSteps: The total number of steps taken by the user.
- TotalDistance: The total distance tracked in kilometres.
- TrackerDistance: The total distance in kilometres as recorded by the Fitbit device.
- LoggedActivitiesDistance: The total distance in kilometres from user-logged activities.
- VeryActiveDistance: The distance travelled in kilometres during highly active periods.
- ModeratelyActiveDistance: The distance travelled in kilometres during moderately active periods.
- LightActiveDistance: The distance travelled in kilometres during lightly active periods.
- SedentaryActiveDistance: The distance travelled in kilometres during sedentary periods.
- VeryActiveMinutes: The total minutes spent in very active activity.
- FairlyActiveMinutes: The total minutes spent in moderately active (fairly active) activity.
- LightlyActiveMinutes: The total minutes spent in light activity.
- SedentaryMinutes: The total minutes spent in sedentary activity.
- Calories: The total estimated calories burned (energy expenditure).
Distribution
The data is available in a CSV file named
dailyActivity_merged.csv with a size of 111.29 kB. It contains 940 valid records across 15 columns.Usage
This information is ideal for analysing patterns in physical activity, heart rate, and sleep. It can be used to develop applications for health improvement, study user behaviour with fitness trackers, and explore correlations between different activity levels and calorie expenditure.
Coverage
The data was collected from thirty Fitbit users between 12 March 2016 and 12 May 2016. The participants were respondents to a survey distributed via Amazon Mechanical Turk. Variations in the data reflect the use of different Fitbit tracker models and individual user preferences.
License
CC0: Public Domain
Who Can Use It
- Health Researchers: To study trends in physical activity and sedentary behaviour.
- Data Scientists: For pattern recognition and building predictive models related to health metrics.
- App Developers: To create fitness and wellness applications that provide personalised insights.
- Students: For academic projects related to health, fitness, and data analysis.
Dataset Name Suggestions
- Fitbit Daily Activity & Health Metrics
- Wearable Fitness Tracker Daily Data
- Fitbit User Activity and Sleep Data 2016
- Personal Fitness Tracker Health Data
Attributes
Original Data Source: Wearable Fitness Tracker Daily Data
QUALITY