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
#> 45355 Zhejiang China 29.1832 120.0934 2020-03-12 2 recovered
#> 45356 Zhejiang China 29.1832 120.0934 2020-03-13 0 recovered
#> 45357 Zhejiang China 29.1832 120.0934 2020-03-14 14 recovered
#> 45358 Zhejiang China 29.1832 120.0934 2020-03-15 0 recovered
#> 45359 Zhejiang China 29.1832 120.0934 2020-03-16 5 recovered
#> 45360 Zhejiang China 29.1832 120.0934 2020-03-17 0 recoveredHere 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 [14]
#> Country.Region type total_cases
#> <chr> <chr> <int>
#> 1 China confirmed 81058
#> 2 China recovered 68798
#> 3 Italy confirmed 31506
#> 4 Iran confirmed 16169
#> 5 Spain confirmed 11748
#> 6 Germany confirmed 9257
#> 7 Korea, South confirmed 8320
#> 8 France confirmed 7699
#> 9 US confirmed 6421
#> 10 Iran recovered 5389
#> 11 China death 3230
#> 12 Italy recovered 2941
#> 13 Switzerland confirmed 2700
#> 14 Italy death 2503
#> 15 United Kingdom confirmed 1960
#> 16 Netherlands confirmed 1708
#> 17 Norway confirmed 1463
#> 18 Korea, South recovered 1407
#> 19 Austria confirmed 1332
#> 20 Belgium confirmed 1243Summary of new cases during the past 24 hours by country and type (as of 2020-03-17):
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: 152 x 4
#> # Groups: country [152]
#> country confirmed death recovered
#> <chr> <int> <int> <int>
#> 1 Italy 3526 345 192
#> 2 Germany 1985 7 0
#> 3 Spain 1806 191 498
#> 4 US 1789 23 0
#> 5 Iran 1178 135 799
#> 6 France 1031 0 0
#> 7 Switzerland 500 13 0
#> 8 United Kingdom 409 0 32
#> 9 Austria 314 0 -5
#> 10 Netherlands 294 19 0
#> 11 Belgium 185 5 0
#> 12 Norway 130 0 0
#> 13 Brazil 121 1 1
#> 14 Portugal 117 1 0
#> 15 Malaysia 107 2 7
#> 16 Pakistan 100 0 0
#> 17 Czechia 98 0 0
#> 18 Denmark 92 1 0
#> 19 Sweden 87 1 0
#> 20 Korea, South 84 6 270
#> 21 Israel 82 0 7
#> 22 Australia 75 2 0
#> 23 Canada 63 1 0
#> 24 Luxembourg 63 0 0
#> 25 Poland 61 1 0
#> 26 Greece 56 1 0
#> 27 Ireland 54 0 5
#> 28 Japan 53 2 0
#> 29 Saudi Arabia 53 0 4
#> 30 Chile 46 0 0
#> 31 Egypt 46 2 5
#> 32 Philippines 45 0 3
#> 33 Finland 44 0 0
#> 34 Iceland 40 1 0
#> 35 Indonesia 38 0 0
#> 36 Andorra 37 0 0
#> 37 Peru 31 0 1
#> 38 Iraq 30 1 6
#> 39 Thailand 30 0 6
#> 40 Mexico 29 0 0
#> # … with 112 more rowsThe 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