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Daily Pedometer and Environmental Metrics Log
Data Science and Analytics
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About
This data captures daily personal activity metrics recorded by a pedometer for one individual. It tracks key fitness variables including the number of steps taken, calories burned, and distance walked in miles. Importantly, the data links these physical activity metrics to external environmental and situational factors, such as observed weather conditions (cold, rain, or shine) and whether the individual walked their dogs. This information provides insight into the daily consistency of fitness routines and how contextual variables might influence daily physical output.
Columns
- StepCount: The raw number of steps taken during the day. The mean step count is approximately 5,830, with recorded values ranging from 674 up to 18,200.
- Kcal: The total calories burned, as measured by the pedometer. The mean value is 136, with a maximum recorded value of 791.
- Miles: The total distance walked, measured in miles. The mean distance is 3.22 miles, with a maximum distance of 10.2 miles.
- Weather: Describes the weather conditions encountered, categorised as cold, rain, or shine. 'Shine' is the most frequently observed condition, accounting for 53% of the observations.
- Day: Indicates the day of the week (e.g., M=Monday, S=Saturday, W=Wednesday). Saturday is the most frequent observation day.
- Walk: A binary indicator (1=yes or 0=no) detailing whether the dogs were walked. The dogs were not walked in 155 of the 223 observations.
- Steps: The step count normalised into units of 1,000 steps (StepCount divided by 1,000). The mean for this variable is 5.83.
- Details: A field for any additional notes or specific details recorded by the data author.
Distribution
The data is provided as a data frame containing 223 daily observations collected across 8 columns. All observed records are noted as 100% valid, with no missing or mismatched values reported across the key metric fields. The dataset is associated with the file name
WalkTheDogs.csv.Usage
This data is ideal for several analytical purposes, including:
- Analysing correlations between individual activity levels (steps, calories, distance) and daily environmental variables such as weather.
- Studying the influence of pet ownership and the requirement to walk dogs on daily fitness statistics.
- Developing predictive models to forecast daily step counts based on scheduling (Day of the week) and external factors.
- Researching individual activity tracking, exercise adherence, and health conditions within the public health domain.
Coverage
This is a personal, single-source dataset capturing activity metrics for one author. It covers 223 daily observations. No future updates are expected for this dataset.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Analysts: For conducting time-series analysis, exploring personal activity patterns, and running correlation studies on lifestyle factors.
- Health Researchers: Interested in the daily variability of exercise and the intersection of weather conditions, scheduling, and physical movement.
- Students: Ideal for learning data cleaning, statistical analysis, and visualisation techniques using real-world pedometer data.
Dataset Name Suggestions
- Daily Pedometer and Environmental Metrics Log
- Author's 223-Day Activity and Weather Data
- Fitness Tracking Correlated with Dog Walks
- Personal Daily Step Count Analysis
Attributes
Original Data Source: Daily Pedometer and Environmental Metrics Log
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