COVID-19 Data Analysis Using Python
COVID-19 Data Analysis Using Python
Data Analysis and Visualization: Examining the Relationship Between COVID-19 and Global Happiness
Description
This project focuses on data analysis and visualization to investigate the relationship between the spread of COVID-19 and happiness levels across different countries. It has three primary objectives:
Preparing Datasets for Analysis
Identifying Key Measures
Visualizing the Analysis Results
The datasets are sourced from a course by Johns Hopkins University on Coursera, instructed by Ahmad Varasteh. One dataset consists of the cumulative daily confirmed COVID-19 cases for each country, while the other includes scores for various life factors from people living in those countries. By merging these datasets, we aim to explore the question:
Is there a correlation between the spread of COVID-19 and the happiness levels of a country’s population?
Project Structure
Task 1: Introduction
Task 2: Importing and Preparing the COVID-19 Dataset
Task 3: Defining Key Metrics
Task 4: Importing and Preparing the World Happiness Report Dataset
Task 5: Visualizing the Results
Data Sources
COVID-19 cases dataset (Johns Hopkins University)
World Happiness Report dataset (Coursera)
Technologies Used
Python for data manipulation and analysis
Pandas for dataset cleaning and merging
Seaborn for data visualization
Project Type: Self-practiced project inspired by a guided project from Coursera.
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Posted Dec 9, 2024
Data Analysis and Visualization: Examining the Relationship Between COVID-19 and Global Happiness
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