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Synthetic Sleep and Lifestyle Behavior Dataset
Mental Health & Wellness
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£29.99
About
The Sleep and Lifestyle Behavior Dataset is a synthetic dataset designed to provide insights into the relationship between daily habits and sleep health. It comprises 100,000 rows and 14 columns, offering a comprehensive view of various lifestyle and health factors. This dataset includes key variables such as gender, age, occupation, sleep patterns, physical activity, stress levels, and cardiovascular health metrics, as well as the presence of sleep disorders.
Dataset Features:
- Gender: Gender of the person (e.g., "Female", "Male").
- Age: Age of the person (in years). - Occupation: Occupation or profession of the person (e.g., "Accountant", "Doctor", "Engineer").
- Sleep Duration: The number of hours the person sleeps per night.
- Quality of Sleep: A subjective rating of the person's sleep quality, on a scale of 1 to 10. - Physical Activity Level: The number of minutes the person engages in physical activity daily. - Stress Level: A subjective rating of the person's stress level, on a scale of 1 to 10.
- BMI Category: The BMI category of the person (e.g., "Underweight", "Normal", "Overweight"). - Heart Rate: The resting heart rate of the person, measured in beats per minute (bpm).
- Daily Steps: The number of steps the person takes per day. - Sleep Disorder: The presence or absence of a sleep disorder (e.g., "None", "Insomnia", "Sleep Apnea"). - Systolic: The systolic blood pressure measurement (in mmHg). Diastolic: The diastolic blood pressure measurement (in mmHg).
Data Distributions and Outliers
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Usage:
This dataset can be used for:
Healthcare research: Investigate the relationships between daily habits, lifestyle factors, and sleep health, and explore trends in the occurrence of sleep disorders.
Educational training: Use it for teaching data analysis, machine learning, and statistical techniques, with a focus on health and wellness.
Predictive modelling: Build models to predict sleep quality, the likelihood of sleep disorders, or cardiovascular health based on daily activities and stress levels..
Coverage:
This dataset is synthetic and anonymized, making it a safe tool for experimentation and learning without compromising real patient privacy.
License:
CCO (Public Domain)
Who can use it:
- Researchers and educators: For studies in health analytics, machine learning, and data science, or as an educational resource in healthcare-related courses.
- Data science enthusiasts: Perfect for practising data manipulation, cleaning, and predictive modelling in the context of health and wellness.
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