https://github.com/preranarao03/covid19-data-analysis-using-python

This repository contains code for a COVID-19 Data Analysis project that uses Python libraries and Streamlit to extract and visualize insights from COVID-19 data along with happiness metrics from the Worldwide Happiness Report.
https://github.com/preranarao03/covid19-data-analysis-using-python

matplotlib pandas pycharm python seaborn streamlit

Last synced: 4 days ago
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This repository contains code for a COVID-19 Data Analysis project that uses Python libraries and Streamlit to extract and visualize insights from COVID-19 data along with happiness metrics from the Worldwide Happiness Report.

• Host: GitHub
• URL: https://github.com/preranarao03/covid19-data-analysis-using-python
• Owner: preranarao03
• Created: 2024-03-31T18:53:46.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-07-25T06:35:03.000Z (5 months ago)
• Last Synced: 2024-10-31T14:23:21.561Z (about 2 months ago)
• Topics: matplotlib, pandas, pycharm, python, seaborn, streamlit
• Language: Python
• Homepage: https://covid19-data-analysis-using-python.streamlit.app/
• Size: 259 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# COVIDTrends - COVID19-Data-Analysis-Using-Python

COVIDInsight - COVID-19 Data Analyzer

### Overview

**COVIDTrends** is an innovative COVID-19 Data Analyzer that provides fascinating insights into the spread and impact of COVID-19 worldwide. Developed from scratch, it leverages powerful libraries such as Pandas, Matplotlib, Seaborn, and Streamlit to meticulously extract, analyze, and visualize COVID-19 data alongside happiness metrics from the Worldwide Happiness Report.

### Technology Used

**Python**: The core programming language used for the application.

**Pandas**: For data manipulation and analysis.

**Matplotlib**: For creating detailed visualizations.

**Seaborn**: For advanced data visualization.

**Streamlit**: For building and deploying the interactive web application.

### Features

**COVIDTrends** offers a comprehensive suite of features to analyze COVID-19 data:

**Time Series Visualization**: Plot confirmed COVID-19 cases over time for selected countries.

**Maximum Infection Rates**: Calculate and display maximum daily infection rates for different countries.

**Correlation Analysis**: Visualize and analyze the correlation between COVID-19 infection rates and happiness metrics such as GDP per capita, social support, healthy life expectancy, and freedom to make life choices.

### Deployment

**COVIDTrends** is deployed using Streamlit, a platform designed for creating and sharing data applications. The interactive and user-friendly interface provided by Streamlit makes analyzing COVID-19 data seamless and enjoyable.

### Contributions

We welcome contributions! If you wish to contribute to COVIDTrends, feel free to fork the repository, make your changes, and submit a pull request.

### Acknowledgements

We extend our gratitude to the developers of the libraries used in this project, including Pandas, Matplotlib, Seaborn, and Streamlit.

### Privacy

COVIDTrends ensures your privacy by not storing any uploaded data. All analyses are performed in real-time on your local session, ensuring your data remains secure.