download_jhu_csse_covid19_data: Download Johns Hopkins University CSSE data on Covid-19

In joachim-gassen/tidycovid19: Download, Tidy and Visualize Covid-19 Related Data

Download Johns Hopkins University CSSE data on Covid-19

Description

Downloads Johns Hopkins University CSSE data on the spread of the SARS-CoV-2 virus and the Covid-19 pandemic (https://github.com/CSSEGISandData/COVID-19). The data for confirmed cases, reported deaths and recoveries are merged into one data frame, converted to long format and joined with ISO3c (ISO 3166-1 alpha-3) country codes based on the countrycode package. Please note: JHU stopped updating the data on March 10, 2023.

Usage

download_jhu_csse_covid19_data(
  type = "country",
  silent = FALSE,
  cached = FALSE
)

Arguments

type	The type of data that you want to retrieve. Can be any subset of "country": Data at the country level (the default). "country_region": Data at the country region level (only available for Australia, Canada, China and some oversea areas). "us_county": Data at the U.S. county level.
silent	Whether you want the function to send some status messages to the console. Might be informative as downloading will take some time and thus defaults to TRUE.
cached	Whether you want to download the cached version of the data from the tidycovid19 Github repository instead of retrieving the data from the authorative source. Downloading the cached version is faster and the cache is updated daily. Defaults to FALSE.

Value

If only one type was selected, a data frame containing the data. Otherwise, a list containing the desired data frames ordered as in type.

Examples

df <- download_jhu_csse_covid19_data(silent = TRUE, cached = TRUE)
df %>%
  dplyr::group_by(country) %>%
  dplyr::summarise(confirmed_cases = max(confirmed, na.rm = TRUE)) %>%
  dplyr::arrange(-confirmed_cases) %>%
  dplyr::top_n(10)

df <- download_jhu_csse_covid19_data(
  type = "us_county", silent = TRUE, cached = TRUE
)
df %>%
  dplyr::filter(!is.na(state)) %>%
  dplyr::group_by(state) %>%
  dplyr::summarise(deaths = max(deaths, na.rm = TRUE)) %>%
  dplyr::arrange(-deaths) %>%
  dplyr::top_n(10)

joachim-gassen/tidycovid19 documentation built on March 21, 2024, 6:57 a.m.