This project focuses on analyzing the effects of lifestyle factors on sleeping behavior, using a dataset containing individual health and lifestyle details such as:
- Person ID & Demographics (Gender, Age, Occupation)
- Sleep Duration & Quality of Sleep
- Physical Activity Level & Stress Level
- BMI Category, Blood Pressure & Heart Rate
- Daily Steps
- Presence of Sleep Disorder
The goal is to explore how lifestyle, health indicators, and demographics influence sleeping patterns and disorders through data analysis and visualization.
The Jupyter Notebook for this project has been structured like a case study, walking through the problem definition, data exploration, analysis, and visualization step by step for clarity and better understanding.
- Performed using Pandas and NumPy.
- Tasks included handling missing values, encoding categorical variables, and preparing data for deeper analysis.
- Conducted with Matplotlib and Seaborn.
- Focused on uncovering relationships between sleep duration/quality and factors such as physical activity, stress level, BMI, and daily steps.
- Analyzed demographic influences (age, gender, occupation) on sleep disorders.