Covid19-data-analysis-using-python

Overview

This project involves analyzing COVID-19 data in combination with the World Happiness Report to uncover insights and correlations between global happiness and the pandemic's impact. Using Python and data visualization libraries, we will explore the dataset, perform data cleaning, and generate meaningful visualizations.

Learning Objectives

• Understand the process of data cleaning and preparation in Python.
• Perform data aggregation and merging of datasets.
• Calculate and visualize key metrics for analysis.
• Use Seaborn for data visualization and uncover patterns in the data.

Project Structure

1. Course Overview

The introductory reading material to give an understanding of the course structure, datasets, and project goals.

2. Task 1: Introduction

• Understand the purpose of the project.
• Review the datasets we will be using, including COVID-19 data and the World Happiness Report.
• Identify the questions we aim to answer with our analysis.

3. Task 2: Importing COVID-19 Dataset

• Import the COVID-19 dataset into Python for analysis.
• Clean and prepare the data by dropping irrelevant columns and aggregating data where necessary.

4. Task 3: Finding a Good Measure

• Define and calculate an appropriate measure for our analysis, such as the infection rate, recovery rate, or death rate.

5. Task 4: Importing World Happiness Report Dataset

• Import the World Happiness Report dataset.
• Clean up the dataset by dropping irrelevant columns.
• Merge the COVID-19 dataset with the World Happiness Report to explore correlations and relationships.

6. Task 5: Visualizing the Results

• Create visualizations of the results using Seaborn.
• Generate various plots to show the relationships between COVID-19 statistics and happiness indicators.

Technologies Used

• Programming Language: Python
• Libraries: pandas, seaborn

Key Outcomes

• Cleaned, merged, and analyzed two real-world datasets.
• Identified key metrics that could help in understanding the correlation between COVID-19 data and happiness.
• Visualized insights using Seaborn for easier interpretation and presentation.

Dataset

The project uses two primary datasets:

1. COVID-19 Dataset: Contains information about COVID-19 cases, deaths, recoveries, etc. across different countries and regions.
2. World Happiness Report: A dataset with happiness scores and factors contributing to happiness across various countries.