Add maps for all countries

Author: kalashsinghal

NAMESPACE

@@ -87,6 +87,7 @@ importFrom(tibble,tibble)
 importFrom(tibble,tribble)
 importFrom(tidyr,drop_na)
 importFrom(tidyr,pivot_wider)
+importFrom(tidyselect,all_of)
 importFrom(tidyselect,matches)
 importFrom(tiltIndicator,example_data_factory)
 importFrom(tiltIndicatorAfter,profile_emissions)

R/bar_plot_emission_profile.R

@@ -72,7 +72,7 @@ prepare_bar_plot_emission_profile <- function(data, grouping_emission, mode, sce
     group_by(.data[[risk_category]], .data$grouping_emission) |>
     summarise(total_mode = sum(.data[[mode]])) |>
     group_by(.data$grouping_emission) |>
-    mutate(proportion = total_mode / sum(total_mode))
+    mutate(proportion = .data$total_mode / sum(.data$total_mode))
 
   data
 }

R/bar_plot_emission_profile_financial.R

@@ -17,7 +17,10 @@
 #'
 #' @examples
 #' grouping_emission <- c("all", "unit", "isic_4digit")
-#' bar_plot_emission_profile_financial(financial, grouping_emission, "equal_weight", risk_category = "emission_category")
+#' bar_plot_emission_profile_financial(financial, grouping_emission,
+#'   "equal_weight",
+#'   risk_category = "emission_category"
+#' )
 bar_plot_emission_profile_financial <- function(data,
                                                 grouping_emission = grouping_emission(),
                                                 mode = c(

R/map_region_risk.R

@@ -23,8 +23,7 @@
 #'   map_region_risk(without_financial, country_code = "DE", benchmark = "unit")
 #' })
 map_region_risk <- function(data,
-                            # TODO: plot for other countries
-                            country_code = c("DE"),
+                            country_code = c("DE", "AT", "FR", "NL", "ES"),
                             grouping_emission = grouping_emission(),
                             mode = modes(),
                             scenario = scenarios(),

R/prepare_geo_data.R

@@ -8,7 +8,7 @@
 #' @noRd
 #'
 prepare_geo_data <- function(data,
-                             country_code = c("DE"),
+                             country_code = c("DE", "AT", "FR", "NL", "ES"),
                              grouping_emission = grouping_emission(),
                              mode = modes(),
                              scenario = scenarios(),
@@ -46,8 +46,7 @@ prepare_geo_data <- function(data,
 
   # merge to have zip codes with NUTS file
   shp_1 <- shp_1 |>
-    inner_join(nuts_de, by = "geo") |>
-    mutate(postcode = as.character(postcode))
+    inner_join(nuts_all, by = "geo")
 
   # merge shapefile with financial data
   geo <- data |>
@@ -92,7 +91,7 @@ aggregate_geo <- function(geo, mode, risk_category) {
     group_by(.data$postcode, .data[[risk_category]]) |>
     summarise(total_mode = sum(.data[[mode]])) |>
     group_by(.data$postcode) |>
-    mutate(proportion = total_mode / sum(total_mode)) |>
+    mutate(proportion = .data$total_mode / sum(.data$total_mode)) |>
     ungroup()
 
   # Pivot

R/sysdata.rda

@@ -74,6 +74,7 @@
 #' @importFrom tibble tribble
 #' @importFrom tidyr drop_na
 #' @importFrom tidyr pivot_wider
+#' @importFrom tidyselect all_of
 #' @importFrom tidyselect matches
 #' @importFrom tiltIndicator example_data_factory
 #' @importFrom tiltIndicatorAfter profile_emissions