Corona Data Scraper
Corona Data Scraper pulls COVID-19 Coronavirus case data from verified sources, finds the corresponding GeoJSON features, and adds population data.
All sources are cited right in the same row as the data.
Select a file on the left to view and download it.
Can't quite visualize it?
Missing data you've got a source for?
The data visualizations and tools listed above are frequently used by developers, researchers, and students working on COVID-related projects, papers, and reports. When dealing with complex datasets and tight academic deadlines, many students opt for a trusted paper writing service to help structure their findings and insights clearly.
For those who are just starting a data-driven research paper and thinking, “Who can help me write my paper?”, platforms like WritePaperForMe offer valuable academic assistance—especially when working with evolving public datasets such as those from Corona Data Scraper.
Contribute a scraper and your data will appear here tomorrow.
Join the Slack and chat in #scraper-dev if you have any questions
Found a problem with the data?
File an issue on Github with complete details of the issue.
Use this data?
Cite this website and file an issue to have your project's URL added.
About the data sources
Corona Data Scraper pulls information from a variety of openly available world government data sources and curated datasets.
Ratings have nothing to do with the accuracy of the data
The ratings for the data sources here are based on how machine-readable, complete, and granular their data is — not on the accuracy or reliability of the information. We’re using a rating system like this because we’re trying to make governments more accountable for their data practices.
Take a look at the code to learn more about how the rating system works.
Questions about a source’s rating?
We’d like to hear from you and help you make your source more complete. Reach out to us on on Slack or file an issue on Github.
What does a good source look like?
First, please have a look at our example format.
As the data itself is most important, please publish cumulative counts for cases, deaths, hospitalized, discharged, recovered, and total tests administered. If you cannot publish in JSON or CSV, at a minimum, please include a HTML <table> with one row per locality at the most granular level you have.
Have a column for the name of this locality, and a column for each additional data point.
The best published sources include timestamps, allowing citizens and researchers alike better understand the data you have, over time, within your specific geographic region(s).
features.json
file.json