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
Source: Centers for Disease Control and Prevention’s Public Health Image Library
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)
#> Province.State Country.Region Lat Long date cases type
#> 1 Afghanistan 33 65 2020-01-22 0 confirmed
#> 2 Afghanistan 33 65 2020-01-23 0 confirmed
#> 3 Afghanistan 33 65 2020-01-24 0 confirmed
#> 4 Afghanistan 33 65 2020-01-25 0 confirmed
#> 5 Afghanistan 33 65 2020-01-26 0 confirmed
#> 6 Afghanistan 33 65 2020-01-27 0 confirmed
tail(coronavirus)
#> Province.State Country.Region Lat Long date cases type
#> 40063 Zhejiang China 29.1832 120.0934 2020-03-09 15 recovered
#> 40064 Zhejiang China 29.1832 120.0934 2020-03-10 15 recovered
#> 40065 Zhejiang China 29.1832 120.0934 2020-03-11 4 recovered
#> 40066 Zhejiang China 29.1832 120.0934 2020-03-12 2 recovered
#> 40067 Zhejiang China 29.1832 120.0934 2020-03-13 0 recovered
#> 40068 Zhejiang China 29.1832 120.0934 2020-03-14 14 recovered
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)
#> # A tibble: 20 x 3
#> # Groups: Country.Region [15]
#> Country.Region type total_cases
#> <chr> <chr> <int>
#> 1 China confirmed 80977
#> 2 China recovered 65660
#> 3 Italy confirmed 21157
#> 4 Iran confirmed 12729
#> 5 Korea, South confirmed 8086
#> 6 Spain confirmed 6391
#> 7 Germany confirmed 4585
#> 8 France confirmed 4480
#> 9 China death 3193
#> 10 Iran recovered 2959
#> 11 US confirmed 2727
#> 12 Italy recovered 1966
#> 13 Italy death 1441
#> 14 Switzerland confirmed 1359
#> 15 United Kingdom confirmed 1143
#> 16 Norway confirmed 1090
#> 17 Sweden confirmed 961
#> 18 Netherlands confirmed 959
#> 19 Denmark confirmed 836
#> 20 Japan confirmed 773
Summary of new cases during the past 24 hours by country and type (as of 2020-03-14):
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)
#> # A tibble: 143 x 4
#> # Groups: country [143]
#> country confirmed death recovered
#> <chr> <int> <int> <int>
#> 1 Italy 3497 175 527
#> 2 Iran 1365 97 0
#> 3 Spain 1159 62 324
#> 4 Germany 910 2 0
#> 5 France 813 12 0
#> 6 US 548 7 0
#> 7 United Kingdom 342 13 0
#> 8 Switzerland 220 2 0
#> 9 Netherlands 155 2 2
#> 10 Austria 151 0 0
#> 11 Sweden 147 1 0
#> 12 Belgium 130 1 0
#> 13 Korea, South 107 6 0
#> 14 Norway 94 3 0
#> 15 Japan 72 3 0
#> 16 Finland 70 0 0
#> 17 Portugal 57 0 1
#> 18 Australia 50 0 0
#> 19 Czechia 48 0 0
#> 20 Philippines 47 3 0
#> 21 Malaysia 41 0 9
#> 22 Slovenia 40 1 0
#> 23 Ireland 39 1 0
#> 24 Greece 38 2 8
#> 25 Estonia 36 0 0
#> 26 Poland 35 1 0
#> 27 Romania 34 0 2
#> 28 China 32 13 1464
#> 29 Denmark 32 1 0
#> 30 Israel 32 0 0
#> 31 Egypt 29 0 0
#> 32 Indonesia 27 1 6
#> 33 Kuwait 24 0 0
#> 34 Iceland 22 0 0
#> 35 Bahrain 21 0 0
#> 36 India 20 0 0
#> 37 Bulgaria 18 1 0
#> 38 Chile 18 0 0
#> 39 Luxembourg 17 1 0
#> 40 Qatar 17 0 4
#> # … with 103 more rows
The raw data pulled and arranged by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from the following resources:
- World Health Organization (WHO): https://www.who.int/
- DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.
- BNO News:
https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/
- National Health Commission of the People’s Republic of China (NHC): http:://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml
- China CDC (CCDC):
http:://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm
- Hong Kong Department of Health:
https://www.chp.gov.hk/en/features/102465.html
- Macau Government: https://www.ssm.gov.mo/portal/
- Taiwan CDC:
https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0
- US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html
- Government of Canada:
https://www.canada.ca/en/public-health/services/diseases/coronavirus.html
- Australia Government Department of Health:
https://www.health.gov.au/news/coronavirus-update-at-a-glance
- European Centre for Disease Prevention and Control (ECDC):
https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases