R/USA.R

In covidregionaldata: Subnational Data for COVID-19 Epidemiology

#' USA Class for downloading, cleaning and processing notification data
#' @description Information for downloading, cleaning
#'  and processing COVID-19 region data for USA.
#'
# nolint start
#' @source \url{https://github.com/nytimes/covid-19-data/}
# nolint end
#' @export
#' @concept dataset
#' @family subnational
#' @examples
#' \dontrun{
#' region <- USA$new(verbose = TRUE, steps = TRUE, get = TRUE)
#' region$return()
#' }
USA <- R6::R6Class("USA",
  inherit = DataClass,
  public = list(

    # Core Attributes
    #' @field origin name of origin to fetch data for
    origin = "United States of America (USA)",
    #' @field supported_levels A list of supported levels.
    supported_levels = list("1", "2"),
    #' @field supported_region_names A list of region names in order of level.
    supported_region_names = list(
      "1" = "state",
      "2" = "county"
    ),
    #' @field supported_region_codes A list of region codes in order of level.
    supported_region_codes = list(
      "1" = "iso_3166_2",
      "2" = "fips"
    ),
    #' @field level_data_urls List of named links to raw data that are level
    #' specific.
    # nolint start
    level_data_urls = list(
      "1" = list("state" = "https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv"),
      "2" = list("county" = "https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv")
    ),
    # nolint end
    #' @field source_data_cols existing columns within the raw data
    source_data_cols = c("cases_total", "deaths_total"),
    #' @field source_text Plain text description of the source of the data
    source_text = "New York Times",
    #' @field source_url Website address for explanation/introduction of the
    #' data
    source_url = "https://github.com/nytimes/covid-19-data",

    #' @description Set up a table of region codes for clean data
    #' @importFrom dplyr tibble
    set_region_codes = function() {
      self$codes_lookup <- usa_codes <- tibble(
        level_1_region_code = c(
          "US-AL", "US-AK", "US-AZ", "US-AR", "US-CA", "US-CO", "US-CT",
          "US-DE", "US-FL", "US-GA", "US-HI", "US-ID", "US-IL", "US-IN",
          "US-IA", "US-KS", "US-KY", "US-LA", "US-ME", "US-MD", "US-MA",
          "US-MI", "US-MN", "US-MS", "US-MO", "US-MT", "US-NE", "US-NV",
          "US-NH", "US-NJ", "US-NM", "US-NY", "US-NC", "US-ND", "US-OH",
          "US-OK", "US-OR", "US-PA", "US-RI", "US-SC", "US-SD", "US-TN",
          "US-TX", "US-UT", "US-VE", "US-VA", "US-WA", "US-WV", "US-WI",
          "US-WY", "US-DC", "US-AS", "US-GU", "US-MP", "US-PR", "US-UM",
          "US-VI"
        ),
        region = c(
          "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado",
          "Connecticut", "Delaware", "Florida", "Georgia", "Hawaii", "Idaho",
          "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana",
          "Maine", "Maryland", "Massachusetts", "Michigan", "Minnesota",
          "Mississippi", "Missouri", "Montana", "Nebraska", "Nevada",
          "New Hampshire", "New Jersey", "New Mexico", "New York",
          "North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon",
          "Pennsylvania", "Rhode Island", "South Carolina", "South Dakota",
          "Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington",
          "West Virginia", "Wisconsin", "Wyoming", "District of Columbia",
          "American Samoa", "Guam", "Northern Mariana Islands", "Puerto Rico",
          "Minor Outlying Islands", "Virgin Islands"
        )
      )
    },

    #' @description State Level Data Cleaning
    #' @importFrom dplyr rename mutate select left_join
    clean_level_1 = function() {
      self$data$clean <- self$data$raw$state %>%
        rename(
          level_1_region = state,
          cases_total = cases,
          deaths_total = deaths
        ) %>%
        mutate(
          cases_total = replace(cases_total, cases_total < 0, 0),
          deaths_total = replace(deaths_total, deaths_total < 0, 0)
        ) %>%
        select(date, level_1_region, cases_total, deaths_total) %>%
        left_join(self$codes_lookup,
          by = c("level_1_region" = "region"),
          copy = TRUE
        )
    },

    #' @description County Level Data Cleaning
    #' @importFrom dplyr mutate rename left_join
    clean_level_2 = function() {
      self$data$clean <- self$data$raw$county %>%
        rename(
          level_2_region = county,
          level_1_region = state,
          level_2_region_code = fips,
          cases_total = cases,
          deaths_total = deaths
        ) %>%
        mutate(
          cases_total = replace(cases_total, cases_total < 0, 0),
          deaths_total = replace(deaths_total, deaths_total < 0, 0)
        ) %>%
        left_join(self$codes_lookup,
          by = c("level_1_region" = "region"),
          copy = TRUE
        )
    }
  )
)