COVID-19, caused by SARS-CoV-2, is a global pandemic respiratory illness since 2019. It ranges from mild to severe symptoms, affecting all aspects of life. Preventive measures include vaccination, masks, and distancing. Research and collaboration are key in managing its spread.
This project aims to analyze the COVID-19 pandemic using publicly available data. The project includes a Jupyter notebook with Python code to extract, clean, and visualize COVID-19 data from various sources. Additionally, the project provides a dashboard to explore the data interactively.
| Files/Folder | Description |
|---|---|
| Dataset Folder | This folder provides data state wise and district wise data in csv format |
| Python File | This contains the .ipynb file of the analysis for Data Extract and Data cleaning. |
| MySQL File | This contains the .sql file for the exploratory data analysis. |
- JSON Data Extraction: Navigated nested JSON structures to extract relevant COVID-19 information.
- Data Cleaning: Tackled missing values and inconsistencies in COVID-19 data for accurate analysis.
- Code Optimization: Improved efficiency in processing and analyzing extensive COVID-19 datasets.
- Domain Understanding: Gained insights into public health and epidemiology through COVID-19 data analysis.
- Collaborative Workflow: Utilized version control and teamwork for successful project completion.
- The analysis focused on the weekly progression of COVID-19 cases, recoveries, deaths, and tests, providing valuable insights into the pandemic's impact across various regions and timeframes.
- Fluctuations in the number of cases and deaths were observed, underscoring the dynamic nature of the pandemic's effects in different geographical areas.
- Through effective data visualization using charts and graphs, the project facilitated a clearer understanding of the data, aiding in the interpretation of trends and patterns.
- The project's findings hold practical significance for public health authorities, enabling them to devise more targeted and efficient strategies for containing the virus's transmission.
- Policymakers can benefit from the analysis by making informed decisions on resource allocation, directing support to regions experiencing the highest impact from the pandemic.