https://github.com/kskmemory/covid19_data_analysis_using_python

Covid19_Data_Analysis_Using_Python
https://github.com/kskmemory/covid19_data_analysis_using_python

Last synced: about 1 year ago
JSON representation

Covid19_Data_Analysis_Using_Python

• Host: GitHub
• URL: https://github.com/kskmemory/covid19_data_analysis_using_python
• Owner: kskmemory
• Created: 2025-03-18T01:47:39.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-25T20:22:34.000Z (over 1 year ago)
• Last Synced: 2025-03-25T21:26:52.297Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 199 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# Covid19_Data_Analysis

Covid19_Data_Analysis_Using_Python

This COVID19 dataset, published by John Hopkins University, consists of the data related to the cumulative number of confirmed cases, per day, in each country. Also, there is another dataset consisting of various life factors, scored by the people living in each country around the globe. By merging these two datasets, the relationship between the spread of the virus in a country and how happy people are, living in that country is found out.

![image](https://github.com/user-attachments/assets/54f9a73c-81ac-4931-b022-7e806751cc65)

# We can see, there is a +ve correlation between both the axis. As GDP per capita increases, max_infected_rates increases. 

![image](https://github.com/user-attachments/assets/44a38aa8-b3eb-4224-8ca1-88f34474d094)

# We can observe that citizens of the developed countries are more prone to be infected

![image](https://github.com/user-attachments/assets/735e988e-7dfa-4dd4-8d79-66f45bd9e58e)