Project Overview
This project explores the effects of remote work on mental health using a dataset collected from various remote workers. The analysis aims to uncover trends and patterns that could help organizations better understand the potential mental health impacts of remote working environments.
Features
Dataset: This dataset includes employee demographics, job roles, work conditions, and mental health assessments.
Analysis: The analysis investigates missing data, outliers, and the distribution of key variables.
Visualization: Visuals like bar plots, histograms, and pie charts depict the relationships between different attributes.
Dataset
Dataset Name: Impact_of_Remote_Work_on_Mental_Health.csv
Source: Remote Work and Mental Health Dataset from Kaggle
Dataset Description
The dataset consists of 5,000 rows and 20 columns, covering attributes such as:
- Employee Information: Employee ID, Age, Gender, Job Role, Industry, Region.
- Work Conditions: Work Location, Hours Worked, Number of Virtual Meetings, Work-Life Balance Rating.
- Mental Health: Stress Level, Mental Health Condition, Access to Resources, Social Isolation Rating.
- Other: Satisfaction with Remote Work, Company Support, Physical Activity, Sleep Quality.
Exploratory Data Analysis (EDA)
Key Insights
Age Distribution: Employees range from 22 to 60 years old, with the majority in their 30s and 40s.
Mental Health Conditions: The most reported mental health conditions are depression and anxiety.
Work Satisfaction: A considerable percentage of employees report dissatisfaction with remote work.
Social Isolation: High social isolation ratings are associated with reduced mental well-being.
How to Use
- Open the notebooks/EDA_notebook.ipynb in Jupyter Notebook.
- Run the cells to load the dataset, clean the data, and visualize the results.
License
This project is licensed under the MIT License.