covidregionaldata (version 0.9.3)

Covid19DataHub: R6 Class containing specific attributes and methods for Covid19 Data Hub

Description

Attributes and methods for COVID-19 data provided by the Covid19 Data Hub

Super classes

covidregionaldata::DataClass -> covidregionaldata::CountryDataClass -> Covid19DataHub

Public fields

origin

name of country to fetch data for

supported_levels

A list of supported levels.

supported_region_names

A list of region names in order of level.

supported_region_codes

A list of region codes in order of level.

level_data_urls

List of named links to raw data. The first, and only entry, is be named main.

source_data_cols

existing columns within the raw data

source_text

Plain text description of the source of the data

source_url

Website address for explanation/introduction of the data

Methods

Public methods

• Covid19DataHub$clean_common()

• Covid19DataHub$clone()

• covidregionaldata::DataClass$available_regions()

• covidregionaldata::DataClass$clean()

• covidregionaldata::DataClass$download()

• covidregionaldata::DataClass$download_JSON()

• covidregionaldata::DataClass$get()

• covidregionaldata::DataClass$initialize()

• covidregionaldata::DataClass$process()

• covidregionaldata::DataClass$return()

• covidregionaldata::DataClass$set_region_codes()

• covidregionaldata::DataClass$summary()

• covidregionaldata::DataClass$test()

• covidregionaldata::CountryDataClass$filter()

Method clean_common()

Covid19 Data Hub specific data cleaning. This takes all the raw data, renames some columns and checks types.

Usage

Covid19DataHub$clean_common()

Method clone()

The objects of this class are cloneable with this method.

Usage

Covid19DataHub$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Details

This dataset supports both national and subnational data sources with national level data returned by default. National data is sourced from John Hopkins University and so we recommend using the JHU class included in this package. Subnational data is supported for a subset of countries which can be found after cleaning using the available_regions() method, see the examples for more details. These data sets are minimally cleaned data files hosted by the team at COVID19 Data Hub so please see their source repository for further details (https://github.com/covid19datahub/COVID19/#data-sources) If using for analysis checking the source for further details is strongly advised.

If using this class please cite: "Guidotti et al., (2020). COVID-19 Data Hub Journal of Open Source Software, 5(51), 2376, https://doi.org/10.21105/joss.02376"

See Also

Aggregated data sources Google, JHU

National data sources ECDC, Google, JHU, JRC, WHO

Subnational data sources Belgium, Brazil, Canada, Colombia, Cuba, Estonia, France, Germany, Google, India, Italy, JHU, Lithuania, Mexico, Netherlands, SouthAfrica, Switzerland, UK, USA

Examples

# NOT RUN {
# nolint start
# }
# NOT RUN {
# set up a data cache
start_using_memoise()

# get all countries data
cv19dh <- Covid19DataHub$new(level = "1", get = TRUE)
cv19dh$return()

# show available regions with data at the second level of interest
cv19dh_level_2 <- Covid19DataHub$new(level = "2")
cv19dh_level_2$download()
cv19dh_level_2$clean()
cv19dh$available_regions()

# get all region data for the uk
cv19dh_level_2$filter("uk")
cv19dh_level_2$process()
cv19dh_level_2$return()

# get all regional data for the UK
uk <- Covid19DataHub$new(regions = "uk", level = "2", get = TRUE)
uk$return()

# get all subregional data for the UK
uk <- Covid19DataHub$new(regions = "uk", level = "3", get = TRUE)
uk$return()
# }
# NOT RUN {
# nolint end
# }