CVIP-Data-Science

COVID-19 Data Analysis

This project performs analysis and visualization of COVID-19 data using Python. It covers various aspects such as data preprocessing, aggregation, visualization, country-wise analysis, time-series modeling, and prediction using linear regression, support vector regression (SVR), and Holt's linear model.

Getting Started

Prerequisites

• Python 3.x
• Pandas
• Matplotlib
• Seaborn
• NumPy
• Scikit-learn
• Statsmodels

Installation

1. Clone the repository: gitclonehttps://github.com/Harsh-Gulati15/CVIP-Data-Science

2. Install the required libraries: pandas, matplotlib, seaborn, numpy, scikit-learn, statsmodels

3. Usage -The script will load the dataset, perform data preprocessing, aggregate the cases, and display basic information.

-It will generate visualizations such as distribution plots, weekly progress of cases, and country-wise analysis.

-The script will also analyze specific countries like India and the US.

-Time-series modeling is performed using linear regression and SVR.

-Predictions are generated for future dates using the models.

4. Acknowledgments

• Data source: COVID-19 Data Repository by Johns Hopkins CSSE

Feel free to explore, modify, and enhance this code for your own COVID-19 data analysis.