This repository contains the code and analysis for a COVID-19 Data Analysis project. The dataset was sourced from Kaggle and underwent comprehensive cleaning and transformation using Jupyter Notebook.
The global COVID-19 pandemic has significantly impacted the world. This project aims to analyze and visualize COVID-19 data to gain insights into the spread, trends, and patterns of the virus.
The dataset used for this analysis is obtained from Kaggle
Jupyter Notebook: Used for data cleaning, exploration, and transformation.
Python: Primary programming language for data analysis.
Pandas: Data manipulation and analysis library.
Matplotlib and Seaborn: Visualization libraries. .
The first chart visualizes the cumulative sum of recovery rates and mortality rates, offering a quick glance at the overall trends in COVID-19 outcomes. Monitoring these rates is crucial for understanding the impact and resilience of affected populations.
The second chart provides a consolidated view of the cumulative sum of confirmed cases, active cases, recoveries, and deaths. This overview aids in assessing the overall progression of the pandemic, helping to make informed decisions and prioritize interventions.