https://github.com/iamnotadams12/python-project
Annalysing the covid dataset using the python library like numpy, pandas, matplotlib and seaborn.
https://github.com/iamnotadams12/python-project
data-analysis data-science docker hacktoberfest-accepted learn-to-code learning-python machine-learning project python python-programming-exercises python4datascience python4everybody student-vscode tutor-milaan9
Last synced: about 2 months ago
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Annalysing the covid dataset using the python library like numpy, pandas, matplotlib and seaborn.
- Host: GitHub
- URL: https://github.com/iamnotadams12/python-project
- Owner: Iamnotadams12
- Created: 2025-04-26T00:14:04.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2025-04-29T23:01:48.000Z (about 2 months ago)
- Last Synced: 2025-04-29T23:58:31.410Z (about 2 months ago)
- Topics: data-analysis, data-science, docker, hacktoberfest-accepted, learn-to-code, learning-python, machine-learning, project, python, python-programming-exercises, python4datascience, python4everybody, student-vscode, tutor-milaan9
- Language: Python
- Size: 1.31 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# COVID-19 Data Analysis with Python 🦠📊
    
Welcome to the **python-project** repository! This project focuses on analyzing COVID-19 datasets using popular Python libraries such as NumPy, Pandas, Matplotlib, and Seaborn. Our goal is to provide insights into the pandemic through data visualization and analysis.
## Table of Contents
- [Project Overview](#project-overview)
- [Installation](#installation)
- [Usage](#usage)
- [Features](#features)
- [Contributing](#contributing)
- [License](#license)
- [Releases](#releases)
- [Contact](#contact)
## Project Overview
In this project, we explore various COVID-19 datasets to extract meaningful information. The analysis includes:
- Daily case counts
- Vaccination rates
- Trends over time
- Geographic distributions
By utilizing libraries like NumPy for numerical operations, Pandas for data manipulation, and Matplotlib and Seaborn for visualization, we aim to present data in a clear and engaging manner.
## Installation
To get started, clone this repository to your local machine:
```bash
git clone https://github.com/Iamnotadams12/python-project.git
```
Next, navigate to the project directory:
```bash
cd python-project
```
You can install the required libraries using pip:
```bash
pip install numpy pandas matplotlib seaborn
```
## Usage
To run the analysis, execute the main script:
```bash
python main.py
```
This will load the dataset and generate visualizations that summarize the findings.
For detailed instructions, please refer to the code comments within the scripts.
## Features
- **Data Loading**: Easily load various COVID-19 datasets.
- **Data Cleaning**: Handle missing values and outliers.
- **Visualization**: Create charts and graphs to represent data clearly.
- **Statistical Analysis**: Perform basic statistical analysis to uncover trends.
## Contributing
We welcome contributions! If you have suggestions or improvements, feel free to fork the repository and submit a pull request. Please ensure your code adheres to the existing style and includes appropriate documentation.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Releases
For the latest releases, visit our [Releases](https://github.com/Iamnotadams12/python-project/releases) page. You can download the files and execute them locally to see the analysis in action.
## Contact
For questions or feedback, please reach out to the project maintainer at [Iamnotadams12](https://github.com/Iamnotadams12).
Thank you for your interest in the **python-project**! We hope you find it useful for understanding COVID-19 data better.