Provides an interface to source specific classes which support national level data. For simple use cases this allows downloading clean, standardised, national-level COVID-19 data sets. Internally this uses the CountryDataClass() parent class which allows documented downloading, cleaning, and processing. Optionally all steps of data processing can be returned along with the functions used for processing but by default just the finalised processed data is returned. See the examples for some potential use cases and the links to lower level functions for more details and options.

get_national_data(
  countries,
  source = "who",
  level = "1",
  totals = FALSE,
  steps = FALSE,
  class = FALSE,
  verbose = TRUE,
  country = deprecated(),
  ...
)

Arguments

countries

A character vector specifying country names of interest. Used to filter the data.

source

A character string specifying the data source (not case dependent). Defaults to WHO (the World Health Organisation). See get_available_datasets("national") for all options.

level

A character string indicating the target administrative level of the data with the default being "1". Currently supported options are level 1 ("1) and level 2 ("2"). Use get_available_datasets() for supported options by dataset.

totals

Logical, defaults to FALSE. If TRUE, returns totalled data per region up to today's date. If FALSE, returns the full dataset stratified by date and region.

steps

Logical, defaults to FALSE. Should all processing and cleaning steps be kept and output in a list.

class

Logical, defaults to FALSE. If TRUE returns the DataClass object rather than a tibble or a list of tibbles. Overrides steps.

verbose

Logical, defaults to TRUE. Should verbose processing messages and warnings be returned.

country

[Deprecated] A character string specifying a country to filter for.

...

Additional arguments to pass to class specific functionality.

Value

A tibble with data related to cases, deaths, hospitalisations, recoveries and testing.

See also

Examples

if (FALSE) {
# set up a data cache
start_using_memoise()

# download all national data from the WHO
get_national_data(source = "who")

# download data for Canada keeping all processing steps
get_national_data(countries = "canada", source = "ecdc")

# download data for Canada from the JHU and return the full class
jhu <- get_national_data(countries = "canada", source = "jhu", class = TRUE)
jhu

# return the JHU data for canada
jhu$return()

# check which regions the JHU supports national data for
jhu$available_regions()

# filter instead for France (and then reprocess)
jhu$filter("France")
jhu$process()

# explore the structure of the stored JHU data
jhu$data
}