knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%", message=FALSE, warning=FALSE )
The coronavirus package provides a tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. The raw data pulled from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository.
More details available here, and a csv
format of the package dataset available here
A summary dashboard is available here
Install the CRAN version:
install.packages("coronavirus")
Install the Github version (refreshed on a daily bases):
# install.packages("devtools") devtools::install_github("RamiKrispin/coronavirus")
The package contains a single dataset - coronavirus
:
library(coronavirus) data("coronavirus")
This coronavirus
dataset has the following fields:
head(coronavirus) tail(coronavirus)
Here is an example of a summary total cases by region and type (top 20):
library(dplyr) summary_df <- coronavirus %>% group_by(Country.Region, type) %>% summarise(total_cases = sum(cases)) %>% arrange(-total_cases) summary_df %>% head(20)
Summary of new cases during the past 24 hours by country and type (as of r max(coronavirus$date)
):
library(tidyr) coronavirus %>% filter(date == max(date)) %>% select(country = Country.Region, type, cases) %>% group_by(country, type) %>% summarise(total_cases = sum(cases)) %>% pivot_wider(names_from = type, values_from = total_cases) %>% arrange(-confirmed)
The raw data pulled and arranged by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from the following resources:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.