This project performs a comprehensive data analysis of global COVID-19 statistics and correlates them with economic and social indicators from the Worldwide Happiness Report.
It reveals how richer, happier, and healthier nations were better equipped to combat the pandemic.
covid19-analysis-project.ipynb( Jupyter Notebook with full code and analysis ) covid19_deaths_dataset.csv ( COVID-19 data — confirmed, recovered, deaths ) worldwide_happiness_report.csv ( Happiness data — GDP, life expectancy, generosity,etc )
- Loaded and cleaned both datasets using Pandas
- Renamed columns, handled nulls, and merged datasets
- Calculated maximum infection rate per country
- Merged happiness and COVID datasets on country names
- Plotted infection trends, scatterplots, and correlation heatmaps
- Used Seaborn and Matplotlib to reveal relationships
Python 3 , Jupyter Notebook , Pandas , NumPy , Matplotlib and Seaborn.