Skip to content

Latest commit

 

History

History
102 lines (67 loc) · 4.63 KB

README.md

File metadata and controls

102 lines (67 loc) · 4.63 KB
Raw

COVID-19 Data Analysis for India

Welcome to the COVID-19 Data Analysis repository. This repository contains various files and resources used to analyze COVID-19 data, providing insights into the impact and spread of the virus. The project involves data manipulation, visualization, and statistical modelling using different tools and techniques.

Project Overview

The COVID-19 pandemic has profoundly impacted global health, economies, and daily life. Understanding the patterns and trends in the spread of the virus is crucial for informing public health decisions and policy-making. This project aims to analyze COVID-19 data to uncover key insights and trends.

Files in the Repository

1. Jupyter Notebook

Filename: Covid-19.ipynb
Description: This Jupyter Notebook contains Python code for the data analysis and visualization of COVID-19 data. It includes: Data cleaning and preprocessing steps. Exploratory Data Analysis (EDA) to understand the distribution and trends in the data. Data visualization using libraries such as Matplotlib and Seaborn. Statistical modelling and hypothesis testing to identify significant patterns and relationships.

Data cleaning and preprocessing steps.

Exploratory Data Analysis (EDA) to understand the distribution and trends in the data. Data visualization using libraries such as Matplotlib and Seaborn. Statistical modelling and hypothesis testing to identify significant patterns and relationships.

2. PowerPoint Presentation

Filename: COVID-19_Presentation.pptx
Description: This PowerPoint presentation summarizes the findings and insights from the data analysis. It includes:

Key metrics and statistics related to COVID-19 cases, deaths, and recoveries. Visualizations and charts to illustrate trends and patterns. Conclusions and recommendations based on the analysis. Additional Files

3. Filtered CSV Files

Directory: filtered_csv_files
Description: Contains preprocessed and filtered datasets used for analysis.

4. Excel Dashboard

Directory: Excel_Dashboard
Description: Excel files are used to create interactive dashboards to visualize the COVID-19 data.

5. Exploratory Data Analysis (EDA)

Directory: EDA
Description: Includes scripts and notebooks focused on the exploratory data analysis phase of the project.

Dashboard Image and KPI

Excel Dashboard

Month wise total cases confirmed

Total death across testing ratio categories

Vaccination data by state

Population and vaccination by state/ut

Population, ratio, and vaccination by state/ut

Deceased ratio in state and ut

The Deceased Ratio is maximum in Punjab and minimum in Dadra & Nagar Haveli.

Getting Started

To start the project, clone the repository and explore the various files and resources. The Jupyter Notebook is a good starting point for understanding the data analysis process, and the PowerPoint presentation provides a high-level overview of the findings.

git clone https://github.com/naushadcom/COVID19-India.git Prerequisites Python 3.x Jupyter Notebook Libraries: pandas, numpy, matplotlib, seaborn, scikit-learn Install the required libraries using pip:

pip install pandas numpy matplotlib seaborn scikit-learn Usage Data Analysis: Open the covid-19.ipynb notebook in Jupyter and run the cells to perform the data analysis. Presentation: Review the COVID-19_Presentation.pptx file to understand the key findings and insights from the analysis. Interactive Dashboard: Use the files in the Excel_Dashboard directory to explore the interactive dashboards. Contributing Contributions are welcome! Please fork the repository and submit a pull request with your changes.

License This project is licensed under the MIT License.

Feel free to explore and contribute to the project to enhance the analysis and derive more insights from the COVID-19 data. If you have any questions or suggestions, please open an issue in the repository.

Thank you for visiting and happy analyzing!