Dark Mode
Bellabeat Smart Device Activity and Sleep Data
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Gain insights into human health behaviours by exploring the relationship between physical activity and rest patterns. Generated as part of a Google Data Analytics capstone study, the data facilitates the examination of daily habits tracked via smart devices. Specifically, it addresses the correlation between daily step counts and sleep duration, highlighting a potential paradox where increased physical activity may correlate with reduced sleep requirements rather than longer rest periods. The files include data cleaning scripts and visualisation outputs, making it suitable for replicating analysis on the "Active Sleep" phenomenon.
Columns
- id: Primary key identifiers distinguishing individual smart device users.
- date: The specific calendar dates on which the activity data was recorded, spanning from 12 April 2016 to 12 May 2016.
- step_total: The total number of steps recorded by the smart device for a given user on a specific date, ranging from 0 to over 36,000.
Distribution
- Format: Tabular data in zip format (
dailySteps_merged.csv). - Size: Approximately 2249.81 kB.
- Structure: 2140 valid records across 3 columns.
- Update Frequency: Never.
Usage
- Health Correlation Analysis: Investigating links between physical exertion (steps) and recovery needs (sleep).
- Regression Modelling: Practising statistical techniques to determine relationships between variables.
- Data Cleaning and Transformation: Utilising R and R Markdown for data preparation exercises.
- Business Intelligence: Deriving insights for health-focused consumer products like Bellabeat.
Coverage
- Time Range: Data was collected over a one-month period from 12 April 2016 to 12 May 2016.
- Demographic Scope: Users of smart health tracking devices.
- Observation Count: Includes 940 unique daily observations.
License
CC0: Public Domain
Who Can Use It
- Data Analysis Students: particularly those completing Google Data Analytics certifications.
- Health Researchers: Individuals studying sleep patterns and active lifestyles.
- R Programmers: Developers looking for practice datasets for cleaning and visualisation (
ggplot). - Business Strategists: Professionals analysing user behaviour in the health-tech market.
Dataset Name Suggestions
- Bellabeat Smart Device Activity and Sleep Data
- Daily Steps vs Sleep Duration Analysis
- The Active Sleep Paradox Dataset
- Google Capstone Health Tracker Data
Attributes
Original Data Source: Bellabeat Smart Device Activity and Sleep Data
QUALITYLoading...