https://github.com/mchavhan1998/analyzing-the-trends-of-covid19-using-time-series-forecasting

This project analyzes the impact and trends of COVID-19 data. The project includes data visualization to understand the spread and recovery patterns of COVID-19 and uses the Facebook Prophet library to forecast future case numbers.
https://github.com/mchavhan1998/analyzing-the-trends-of-covid19-using-time-series-forecasting

covid-19

Last synced: 3 days ago
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This project analyzes the impact and trends of COVID-19 data. The project includes data visualization to understand the spread and recovery patterns of COVID-19 and uses the Facebook Prophet library to forecast future case numbers.

• Host: GitHub
• URL: https://github.com/mchavhan1998/analyzing-the-trends-of-covid19-using-time-series-forecasting
• Owner: Mchavhan1998
• License: mit
• Created: 2024-07-26T23:55:14.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-08-03T23:33:34.000Z (5 months ago)
• Last Synced: 2024-11-10T15:07:14.944Z (2 months ago)
• Topics: covid-19
• Language: Jupyter Notebook
• Homepage: https://github.com/Mchavhan1998/Analyzing-the-Trends-of-Covid19-using-Time-Series-Forecasting
• Size: 2.41 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 📂 Analyzing-the-Trends-of-Covid19-using-Time-Series-Forecasting

This project analyzes the impact and trends of COVID-19 data. The project includes data visualization to understand the spread and recovery patterns of COVID-19 and uses the Facebook Prophet library to forecast future case numbers.

## 🛠 Skills

Data Analysis, Python, Pandas, Matplotlib, Plotly, Facebook Prophet, Data Visualization, Time Series Forecasting

## 🔭 Project Objectives

- Analyze COVID-19 data to visualize the impact and trends.

- Aggregate and visualize the data using pandas, matplotlib, and plotly.

- Build a time series model using Facebook Prophet to predict future COVID-19 cases.

### 🔑 Features

- Data aggregation and cleaning using pandas.

- Data visualization using matplotlib and plotly.

- Time series forecasting using Facebook Prophet.

- Interactive visualizations to explore COVID-19 trends.

## How to Use

1. **Clone the repository**:

    ```bash

    git clone https://github.com/1vig/Covid19-data-analysis.git

    cd Covid19-data-analysis

    ```

2. **Install the required dependencies**:

    ```bash

    pip install -r requirements.txt

    ```

3. **Run the Jupyter Notebooks** to explore the data, build models, and visualize results:

    ```bash

    jupyter notebook

    ```

## Results

- The project provides visual insights into the global impact of COVID-19.

- The time series model predicts future trends in COVID-19 cases with reasonable accuracy.

## Acknowledgements

- Data sourced from various public COVID-19 datasets.

- Libraries used: numpy,pandas, matplotlib, plotly, seaborn, Prophet

## Contributing

Contributions are welcome! If you have any suggestions or improvements, please create a pull request or open an issue.