add RBM mapping

unhcr-americas · Feb 22, 2024 · 72fa9b8 · 72fa9b8
1 parent 9a43cd9
commit 72fa9b8
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diff --git a/NAMESPACE b/NAMESPACE
@@ -7,8 +7,10 @@ export(show_donors)
 export(show_earmarking)
 export(show_expenditure)
 export(show_indicators)
+export(show_indicators_time)
 export(show_partnership)
 export(show_sectors)
+export(show_sectors_rbm)
 export(show_top_donors)
 import(dplyr)
 import(ggplot2)

diff --git a/R/data.R b/R/data.R
@@ -355,9 +355,30 @@
 #'}
 "dataRelated_activity"
 
+#### Mapping table #########
 
+#' @title mapping_result
+#' @description Mapping Results to UNHCR 2022 RBM Framework
+#' @format A data frame with 107 rows and 2 variables:
+#' \describe{
+#'   \item{\code{result_title}}{character result_title}
+#'   \item{\code{sector_rbm}}{character sector_rbm} 
+#'}
+#' @source \url{https://www.unhcr.org/what-we-do/build-better-futures/compass/}
+"mapping_result"
 
 
+#' @title mapping_sector
+#' @description Mapping Sector to UNHCR 2022 RBM Framework
+#' @format A data frame with 83 rows and 3 variables:
+#' \describe{
+#'   \item{\code{sector_desc}}{character COLUMN_DESCRIPTION} 
+#'   \item{\code{sector_vocabulary_name}}{character COLUMN_DESCRIPTION}
+#'   \item{\code{sector_rbm}}{character COLUMN_DESCRIPTION} 
+#'}
+#' @source \url{https://www.unhcr.org/what-we-do/build-better-futures/compass}
+"mapping_sector"
+
 #### All code list doc ############
 
 

diff --git a/R/globals.R b/R/globals.R
@@ -28,5 +28,7 @@ globalVariables(unique(c(
   # show_partnership: 
   "Accountable", 
   # show_top_donors: 
-  "transaction_provider_org"
+  "transaction_provider_org",
+  # show_sectors_rbm: 
+  "sector_rbm", "sector_vocabulary_name", "year2"
 )))
diff --git a/R/show_budget_gap.R b/R/show_budget_gap.R
@@ -2,10 +2,19 @@
 
 #' show_budget_gap
 #' 
+#' UNHCR budgets are needs-based: it represents the total amount
+#' of money that would be required were UNHCR to meet all of the needs that it is seeking to address.
+#' 
 #' @param year A numeric value corresponding to the first year of focus until the most recent year within the dataset.
 #' @param programme_lab A character vector corresponding to the name of the programme.
 #' @param iati_identifier_ops A character vector corresponding to the name of the operation.
 #' @param ctr_name A character vector corresponding to the name of the country.
+#' @param weight_by list of population group to weight the budget - 
+#'                   "refugees", "asylum_seekers",
+#'                    "returned_refugees" "idps",
+#'                    "returned_idps", "stateless", 
+#'                    "ooc", "oip"  
+#'                   default is null.
 #' 
 #' @import ggplot2
 #' @import dplyr
@@ -18,10 +27,17 @@
 #' @examples
 #' show_budget_gap(year = 2018, 
 #'              ctr_name = "Brazil")
+#'
+#'
+#'
+#' show_budget_gap(year = 2018, 
+#'              ctr_name = "Brazil",
+#'              weight_by = c("refugees", "oip"))
 show_budget_gap <- function(year, 
                         programme_lab = NULL, 
                         iati_identifier_ops = NULL, 
-                        ctr_name = NULL ) {
+                        ctr_name = NULL ,
+                        weight_by = NULL ) {
 
 
   # Check if only one argument is passed 
@@ -72,6 +88,55 @@ show_budget_gap <- function(year,
      dplyr::mutate(budget_gap = (budget_value - transaction_value) / budget_value *100) 
 
 
+
+    if (  !is.null(weight_by) &&  !all(weight_by %in% c("refugees", "asylum_seekers",
+                                                   "returned_refugees", "idps",
+                                                   "returned_idps", "stateless", 
+                                                   "ooc", "oip"  ))  ) {
+     stop("weight_by is used but the population filter is not correctly set up...\n
+          it should be among: refugees, asylum_seekers, returned_refugees, idps,
+          returned_idps, stateless,  ooc, oip")
+    } 
+
+   ## Calculate weight
+   if (!is.null(weight_by) && !is.null(ctr_name) ) {
+     ctrstat <- refugees::population |>
+            dplyr::filter( year>= thisyear & 
+                             coa_name == thisctr_name) |>
+            dplyr::group_by(year, coa_name) |>
+            dplyr::summarise(refugees = sum(refugees, na.rm = TRUE),
+                             asylum_seekers = sum(asylum_seekers, na.rm = TRUE),
+                              returned_refugees = sum(returned_refugees, na.rm = TRUE),
+                              idps = sum(idps, na.rm = TRUE),
+                              returned_idps = sum(returned_idps , na.rm = TRUE),
+                              stateless = sum(stateless, na.rm = TRUE),
+                              ooc = sum( ooc, na.rm = TRUE),
+                              oip = sum(oip, na.rm = TRUE)) |>
+            dplyr::select(year, coa_name, all_of(weight_by) ) |>
+            dplyr::mutate(year = as.factor(year) ) |>
+            dplyr::mutate( weight = rowSums(
+                                   dplyr::across(tidyselect::where(is.numeric))))
+
+      df2 <-  df2 |>
+        dplyr::left_join(ctrstat |> 
+                         dplyr::select(year, weight)   , by = c("year")) |>
+        dplyr::mutate(budget_value = round(budget_value / weight,1),   
+                      transaction_value = round(transaction_value  / weight,1))|>
+       dplyr::mutate(budget_gap = (budget_value - transaction_value) / budget_value *100) 
+
+    } 
+
+ subtitt <- if( is.null(weight_by)) {
+   paste0("In ", programme_lab, ctr_name,iati_identifier_ops, " recorded since ", year,"")
+   } else {
+   paste0("Weighted by total number of individual ", 
+          paste(weight_by, collapse = ', '),
+          " in ", 
+          programme_lab, ctr_name,iati_identifier_ops, " as recorded since ", year,"")
+     }
+
+
+
 
  p <- df2 |> 
 #  dplyr::filter(transaction_value_USD  <= 1000000 & transaction_value_USD  > 1000) |> 
@@ -90,10 +155,10 @@ show_budget_gap <- function(year,
                            legend = FALSE)+
   ggplot2::labs(
     title = paste0( "Budget Gap  (in %)"),
-    subtitle =  paste0("In ", programme_lab, ctr_name,iati_identifier_ops, " recorded since ", year,""),
+    subtitle =   subtitt ,
     x = "",
     y = "",
-    caption = "Data Source: UNHCR IATI (International Aid Transparency Initiative)" ) 
+    caption = "Data Source: UNHCR IATI (International Aid Transparency Initiative). UNHCR budget is needs-based. It represents the total amount of money that would be required were UNHCR to meet all of the needs that it is seeking to address." ) 
 
   return(p)
 

diff --git a/R/show_earmarking.R b/R/show_earmarking.R
@@ -2,7 +2,20 @@
 
 #' Title
 #' 
-#' @description What’s the breakdown of Earmarking Type (Un-earmarked, Tightly earmarked, etc.) from Donor Funds by Year?  
+#' @description What’s the breakdown of Earmarking Type (Un-earmarked, Tightly earmarked, etc.) \
+#'  from Donor Funds by Year?  
+#'  Where possible, UNHCR prefers to receive unearmarked funds, as this allows the agency 
+#'  greater flexibility in allocating its resources as new needs emerge during the course of the year. 
+#'  Should that not be possible, funds can also be softly earmarked. This could mean funds that 
+#'  can be spent anywhere within a region or for a particular situation (for example, funds that have 
+#'  to be spent to assist refugees from Syria, but which can be spent in any country hosting such 
+#'  refugees). Earmarked funds would be a contribution that corresponds to a specific country but 
+#'  can be spent on anything within that operation’s programme. Finally, tightly earmarked funds 
+#'  are those that specify an activity or a population within a country’s programme.
+#'  
+#'  UNHCR charges an ISC -  Indirect Support Costs - rate of 6.5% on all of its earmarked contributions.
+#'   This covers management and administration  costs at HQ and programme support costs 
+#'   incurred at HQ and Regional Bureaux. 
 #' 
 #' @param year A numeric value corresponding to the first year of focus until the most recent year within the dataset.
 #' @param programme_lab A character vector corresponding to the name of the programme.

diff --git a/R/show_expenditure.R b/R/show_expenditure.R
@@ -157,7 +157,7 @@ show_expenditure <- function(year,
     subtitle = subtitt,
     x = "",
     y = "",
-    caption = "Data Source: UNHCR IATI (International Aid Transparency Initiative)" ) 
+    caption = "Data Source: UNHCR IATI (International Aid Transparency Initiative). UNHCR budget is needs-based. It represents the total amount of money that would be required were UNHCR to meet all of the needs that it is seeking to address." ) 
 
   return(p)
 }