Corona pandemic has caused panic throughout the world and is negatively impacting not only humans but also businesses. Consequently, various companies have been moving toward the data-driven approach to analyse the spread and reported cases. To streamline this process, Johns Hopkins University Center for System Science and Engineering (JHU CCSE) has collected data from various sources and created a repository, which was then pulled by Rami Krispin, who released an R package to provide a daily summary of the coronavirus (COVID-19) cases by state/province. The data set contains various variables such as conformed cases, death, and recovered across different states.
The package was introduced on 23 February, is available for R programming users under the MIT license and supports for R 3.0.2 and above. Either you can directly install the package from the R studio or install it manually by downloading it from the GitHub repository. Besides, you can contribute to the project by pushing issues on GitHub and help researchers and developers to analyse using the package flawlessly. The package has quickly gained traction on GitHub as it has been forked 37 times and 110 people are monitoring the repository.
You can install the package with install.packages(“coronavirus”) then import the package with library(coronavirus).
However, a Python user can directly download the file in the CSV format and analyse to get insights into the data. But you will have to download it again to get the updated file. Thus, to get real-time data, it is recommended to use the package instead.
Besides, It provides a tidy format dataset, which is an icing on the cake. Therefore, you can directly get down to visualising and finding trends rather than cleaning it. Or you can directly access the dashboard that the author has created with the data.
