Sleep, Health and Lifestyle

Introduction to Dataset

This dataset provides a detailed view of the different factors which are closely related to sleep and our daily routines. The dataset has a wide range of variables that can give us insights on how different aspects of lifestyle affect our sleep pattern and our overall health on a everyday basis.

Content and Structure

The dataset consists of 373 rows and 13 columns. It captures diverse information including:

Age

Profession

Duration of Sleep

Sleep Quality

Level of Physical Activity

Stress Levels

BMI Classification

Blood Pressure

Heart Rate

Daily Step Count

Presence of Sleep Disorders

The data is originally stored in CSV format, providing a structured yet flexible foundation for analysis.

Collection and Methodology

The dataset is downloaded from Kaggle website, a popular platform for data science and machine learning datasets. The original dataset can be found here:

https://www.kaggle.com/datasets/henryshan/sleep-health-and-lifestyle

The downloaded dataset was in CVS format. After downloading the data, I converted it into Excel (.xl) format for easier data modeling and analysis.

Quality and Limitations

Upon reviewing the dataset, I found that while the majority of the data was clean and ready for analysis, there was an inconsistency in the "BMI Classification" column. Specifically, the term 'Normal Weight' appeared in some rows, while 'Normal' was used in others. To maintain consistency, I updated all instances of 'Normal Weight' to 'Normal'. In total, this adjustment was made in 21 entries.

Data Visualization

For visualizing the dataset, I used Tableau. The process involved importing the cleaned Excel file into Tableau and then creating various visualizations to explore the data. Tableau's robust visualization capabilities allowed for an in-depth analysis of the relationships between different variables, providing valuable insights into sleep health and lifestyle patterns.

Insights from the Dataset

I found that the dataset offers a wide variety of information related to sleep and daily routine. It gave me the opportunity to find insights about how lifestyle factors influence sleep patterns and our overall health in daily life.

Here are some of the key insights which I have derived from the dataset:

• Out of the 373 rows of data, female were 184 and male were 189

• Age, Occupation and Physical activity has a major impact on the sleep quality every night

• Physical Activity helps to keep blood pressure under control

• The occupation or job we choose directly impacts the stress level

Data Visualization

Here is the last part of my analysis, the visualization part. To visualize the above insights, I have used Tableau as the visualization tool. The process involved importing the cleaned Excel file( dataset with 373 rows and 13 columns) into Tableau and create various charts to explore data.

Data Visualization (Sleep, Health and Lifestyle)

Closing Notes

Thank you for taking the time to read my analysis. I enjoyed working with the data and transforming the raw facts into meaningful information.