Add source fields for country and global sources.

R/Covid19DataHub.R

@@ -93,6 +93,11 @@ Covid19DataHub <- R6::R6Class("Covid19DataHub",
     # nolint end
     #' @field source_data_cols existing columns within the raw data
     source_data_cols = c("confirmed", "deaths", "recovered", "tested", "hosp"),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "COVID-19 Data Hub",
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://covid19datahub.io",
 
     #' @description Covid19 Data Hub specific data cleaning.
     #' This takes all the raw data, renames some columns and checks types.

R/ECDC.R

@@ -36,6 +36,11 @@ ECDC <- R6::R6Class("ECDC",
     ),
     #' @field source_data_cols existing columns within the raw data
     source_data_cols = c("cases_new", "deaths_new"),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "European Centre for Disease Prevention and Control (ECDC)",
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide", # nolint
 
     #' @description ECDC specific state level data cleaning
     #' @importFrom dplyr mutate rename select arrange filter

R/Google.R

@@ -84,6 +84,12 @@ Google <- R6::R6Class("Google",
       "total_recovered",
       "total_tested"
     ),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "O. Wahltinez and others",
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://github.com/GoogleCloudPlatform/covid-19-open-data",
+
     #' @description GoogleData specific subregion2 level data cleaning. This
     #' takes all the raw data, puts into a single data frame, renames some
     #' columns and checks types.

R/JHU.R

@@ -77,6 +77,11 @@ JHU <- R6::R6Class("JHU", # rename to country name
     # nolint end
     #' @field source_data_cols existing columns within the raw data
     source_data_cols = c("confirmed", "deaths", "recovered"),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU)", # nolint
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://github.com/CSSEGISandData/COVID-19/",
 
     #' @description Set up a table of region codes for clean data
     #' @importFrom tibble tibble

R/JRC.R

@@ -61,6 +61,12 @@ JRC <- R6::R6Class("JRC",
       "Hospitalized",
       "IntensiveCare"
     ),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "European Commission Joint Research Centre (JRC)",
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://github.com/ec-jrc/COVID-19",
+
 
     #' @description JRC specific data cleaning. The raw source data columns are
     #' converted to the correct type and renamed appropriately to match the

R/SouthAfrica.R

@@ -42,7 +42,6 @@ SouthAfrica <- R6::R6Class("SouthAfrica",
 
     #' @description Set up a table of region codes for clean data
     #' @importFrom tibble tibble
-    #' @importFrom dplyr mutate
     set_region_codes = function() {
       self$codes_lookup$`1` <- tibble(
         code = c(

R/WHO.R

@@ -38,6 +38,12 @@ WHO <- R6::R6Class("WHO",
       "deaths_new",
       "deaths_total"
     ),
+    #' @field source_text Plain text description of the source of the data
+    source_text = "World Health Organisation",
+    #' @field source_url Website address for explanation/introduction of the
+    #' data
+    source_url = "https://covid19.who.int",
+
 
     #' @description WHO specific data cleaning
     #' @importFrom dplyr mutate rename