Data
FitBit_HeartRate

FitBit_HeartRate

active ARFF Public Domain (CC0) Visibility: public Uploaded 31-05-2024 by Iwo Godzwon
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Description: The 'heartrate_seconds_merged.csv' dataset is a comprehensive compilation of heart rate measurements collected over varying days and times, intended to provide insights into heart rate variability across different individuals and time periods. The dataset is structured into three primary columns: 'Id', 'Time', and 'Value'. Attribute Description: - 'Id': This column contains unique numerical identifiers (e.g., 4020332650, 6962181067) for each participant in the study, allowing for the anonymized tracking of heart rate data across multiple entries. - 'Time': Each entry in this column records the specific date and time when the heart rate measurement was taken, formatted as 'Month/Day/Year Hours:Minutes:Seconds AM/PM' (e.g., '4/5/2016 8:00:15 AM'). This attribute is crucial for understanding the temporal context of each heart rate measurement. - 'Value': Represents the heart rate of an individual at the recorded time, measured in beats per minute (BPM). Sample values in this dataset range from 55 to 92 BPM, indicating the variability of heart rate measurements among different times and individuals. Use Case: This dataset can serve multiple analytical and research purposes, such as studying the effects of various factors (e.g., time of day, physical activity, stress) on heart rate variability. It can also be utilized in developing heart rate monitoring applications, conducting temporal heart rate variability studies, and enhancing personalized health and fitness recommendations. Researchers and healthcare professionals could leverage this dataset to understand patterns in heart rate data, thereby contributing to broader studies in cardiology, health informatics, and personalized medicine.

3 features

Idnominal14 unique values
0 missing
Timestring510597 unique values
0 missing
Valuenumeric148 unique values
0 missing

19 properties

1154681
Number of instances (rows) of the dataset.
3
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
1
Number of numeric attributes.
1
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
33.33
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
33.33
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.

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