This repository contains Python code to analyze COVID-19 data using the Pandas library. Here's an overview of the different files in this repository:
: covid_data.csv: This file contains the COVID-19 data used for analysis.
: Covid_19_Analysis - RanjithKrishna_Acharya.ipynb: This Jupyter notebook contains Python code to analyze the COVID-19 data.
: README.md: This file you're reading right now. It provides an overview of the repository.
To use the code in Covid_19_Analysis - RanjithKrishna_Acharya.ipynb, you'll need to have Python and the Pandas library installed on your computer. Once you have those, you can open the notebook in Jupyter or another Python environment and run the cells to analyze the data.
Here's an overview of the analysis done in Covid_19_Analysis - RanjithKrishna_Acharya.ipynb:
The number of confirmed, recovered, and death cases in the last 24 hours is calculated and printed.
The top 15 countries with the most confirmed cases, recovered cases, and death cases in the last 24 hours are displayed.
A new column is added to the data indicating the day of the week for each data point.
The 7-day rolling mean of daily increases in confirmed, recovered, and death cases is calculated and printed.
Countries with more than 100 confirmed cases, no deaths, and a high recovery rate are identified and displayed.