Visualizing COVID-19

Visualize the rise of COVID-19 cases globally with ggplot2.

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Project Description

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.

Project Tasks

1
From epidemic to pandemic

2
Confirmed cases throughout the world
3
China compared to the rest of the world
4
Let's annotate!
5
Adding a trend line to China
6
And the rest of the world?
7
Adding a logarithmic scale
8
Which countries outside of China have been hit hardest?
9
Plotting hardest hit countries as of Mid-March 2020

Technologies

Topics

Data Visualization

Richie Cotton

Data Evangelist at DataCamp

Richie is a Data Evangelist 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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