https://github.com/kowshikreddy97/covid19-data-analysis-project

The main objective of the project is to find the relationship between corona spread and the happiness in a country by performing Exploratory Data Analysis and to uncover valuable insights.
https://github.com/kowshikreddy97/covid19-data-analysis-project

dataanalysis jupyter-notebook python

Last synced: 18 days ago
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The main objective of the project is to find the relationship between corona spread and the happiness in a country by performing Exploratory Data Analysis and to uncover valuable insights.

• Host: GitHub
• URL: https://github.com/kowshikreddy97/covid19-data-analysis-project
• Owner: kowshikreddy97
• Created: 2024-09-04T19:12:22.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-17T16:16:10.000Z (26 days ago)
• Last Synced: 2025-01-17T17:27:34.825Z (26 days ago)
• Topics: dataanalysis, jupyter-notebook, python
• Language: Jupyter Notebook
• Homepage:
• Size: 308 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
I Preprocessed & merged COVID-19 and World Happiness datasets using Python, achieving 95% data accuracy and improving impact assessment clarity by 30% through key metric analysis, leading to actionable

Insights. 

Q: Is there any relationship between corona spread and the happiness in a country?

Deleted the useless columns (using drop, axis=0 means deletes rows, axis=1 means deletes columns), performed aggregation (by country), utilized derivative curves to understand the difference between day to day cases. 

Found the max infection rate. 

From covid 19 - I took 2 columns - country and the max infection rate. 

Imported happiness dataset, dropped useless columns, changed the indexes.

Joined both data sets. 

Created a correlation matrix to find out which features are correlated. 

I have used Seaborn for visualization and to elucidate complex data relationships. 

Created Plots to explore the relationships and impacts: 

 - GDP Vs MAX infection rate

 - Social support vs max infection rate

 - Health life expectancy vs max infection rate

 - Freedom to make like choices vs max infection rate