https://github.com/sgb31/covid-19-data-analysis

"In this project, I analyzed COVID-19 data to explore trends, case growth, and key patterns. I worked on cleaning the data, performing exploratory analysis, and visualizing infection rates, recoveries, and fatalities. The goal was to gain insights into how the pandemic evolved and its overall impact.
https://github.com/sgb31/covid-19-data-analysis

data-analysis data-visualization matplotlib pandas python seaborn

Last synced: about 1 month ago
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"In this project, I analyzed COVID-19 data to explore trends, case growth, and key patterns. I worked on cleaning the data, performing exploratory analysis, and visualizing infection rates, recoveries, and fatalities. The goal was to gain insights into how the pandemic evolved and its overall impact.

• Host: GitHub
• URL: https://github.com/sgb31/covid-19-data-analysis
• Owner: sgb31
• Created: 2024-10-15T10:02:53.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-11T14:43:02.000Z (over 1 year ago)
• Last Synced: 2025-06-07T20:43:10.422Z (about 1 year ago)
• Topics: data-analysis, data-visualization, matplotlib, pandas, python, seaborn
• Homepage:
• Size: 2.93 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
This project analyzes COVID-19 data in the United States using visualizations to track trends in new cases, deaths, and vaccination rates over time.

It employs various plots, including line graphs and bar charts, to illustrate the relationship between COVID-19 metrics and vaccination progress, as well as state-level comparisons of total cases and deaths.

The final dataset is saved for further analysis and reference.