JRC: R6 Class containing specific attributes and methods for...

In epiforecasts/covidregionaldata: Subnational Data for COVID-19 Epidemiology

R6 Class containing specific attributes and methods for European Commission's Joint Research Centre data

Description

Class for downloading, cleaning and processing COVID-19 region data from the European Commission's Joint Research Centre. Subnational data (admin level 1) on numbers of contagious and fatalities by COVID-19, collected directly from the National Authoritative sources (National monitoring websites, when available). For more details see https://github.com/ec-jrc/COVID-19

Super classes

covidregionaldata::DataClass -> covidregionaldata::CountryDataClass -> JRC

Public fields

origin

name of origin 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.

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

• JRC$clean_common()

• JRC$clean_level_1()

• JRC$clean_level_2()

• JRC$clone()

Inherited methods

• 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()

JRC specific data cleaning. The raw source data columns are converted to the correct type and renamed appropriately to match the standard for general processing.

Usage

JRC$clean_common()

---

Method clean_level_1()

JRC specific country level data cleaning. Selects country level (level 1) columns from the data ready for further processing.

Usage

JRC$clean_level_1()

---

Method clean_level_2()

JRC specific region level data cleaning. Selects country (level 1) and region (level 2) columns from the data ready for further processing.

Usage

JRC$clean_level_2()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

JRC$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Source

https://github.com/ec-jrc/COVID-19

See Also

National data sources Covid19DataHub, ECDC, Google, JHU, WHO

Examples

## Not run: 
# get country level data
jrc_level_1 <- JRC$new(level = "1", verbose = TRUE, steps = TRUE, get = TRUE)
jrc_level_1$return()

# show available regions with data at the first level of interest (country)
jrc_level_1$available_regions()

# get region level data
jrc_level_2 <- JRC$new(level = "2", verbose = TRUE, steps = TRUE, get = TRUE)
jrc_level_2$return()

# show available regions with data at the second level of interest (region)
jrc_level_2$available_regions()

## End(Not run)

epiforecasts/covidregionaldata documentation built on June 26, 2022, 1 a.m.