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Within months, COVID-19 went from an epidemic to a pandemic. From the first identified case in December 2019, how did the virus spread so fast and widely? In this free R project, we will visualize data from the early months of the coronavirus outbreak to see how this virus grew to be a global pandemic. This project assumes you can manipulate data frames using `dplyr` and make plots using `ggplot2`.
- 1From epidemic to pandemic
- 2Confirmed cases throughout the world
- 3China compared to the rest of the world
- 4Let's annotate!
- 5Adding a trend line to China
- 6And the rest of the world?
- 7Adding a logarithmic scale
- 8Which countries outside of China have been hit hardest?
- 9Plotting hardest hit countries as of Mid-March 2020
Curriculum Architect at DataCamp
Richie is a Learning Solutions Architect at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
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