From 72fa9b8d354366d4b65a1774e8425f3ccd8ddc32 Mon Sep 17 00:00:00 2001 From: Edouard Date: Thu, 22 Feb 2024 18:57:33 -0500 Subject: [PATCH] add RBM mapping --- NAMESPACE | 2 + R/data.R | 21 + R/globals.R | 4 +- R/show_budget_gap.R | 71 ++- R/show_earmarking.R | 15 +- R/show_expenditure.R | 2 +- R/show_indicators_time.R | 304 +++++++++ R/show_sectors.R | 51 +- R/show_sectors_rbm.R | 143 +++++ _pkgdown.yml | 4 + data/mapping_result.RData | Bin 0 -> 1828 bytes data/mapping_sector.RData | Bin 0 -> 1862 bytes dev/dev_unhcr_programme.Rmd | 594 +++++++++++++++++- docs/articles/unhcr-programme.html | 123 +++- .../figure-html/example-show_budget_gap-1.png | Bin 48640 -> 54877 bytes .../figure-html/example-show_budget_gap-2.png | Bin 0 -> 60025 bytes .../example-show_expenditure-1.png | Bin 58251 -> 62582 bytes .../example-show_expenditure-2.png | Bin 62527 -> 70203 bytes .../example-show_indicators_time-1.png | Bin 0 -> 135418 bytes .../example-show_indicators_time-2.png | Bin 0 -> 42083 bytes .../example-show_indicators_time-3.png | Bin 0 -> 118198 bytes .../example-show_indicators_time-4.png | Bin 0 -> 88930 bytes .../example-show_indicators_time-5.png | Bin 0 -> 52553 bytes .../example-show_indicators_time-6.png | Bin 0 -> 43805 bytes .../example-show_sectors_rbm-1.png | Bin 0 -> 202404 bytes docs/pkgdown.yml | 2 +- docs/reference/index.html | 31 + docs/reference/mapping_result.html | 97 +++ docs/reference/mapping_sector.html | 100 +++ docs/reference/show_budget_gap-1.png | Bin 43721 -> 52824 bytes docs/reference/show_budget_gap-2.png | Bin 0 -> 59317 bytes docs/reference/show_budget_gap.html | 26 +- docs/reference/show_earmarking.html | 40 +- docs/reference/show_expenditure-1.png | Bin 51894 -> 61163 bytes docs/reference/show_expenditure-2.png | Bin 56922 -> 65053 bytes docs/reference/show_indicators_time-1.png | Bin 0 -> 81320 bytes docs/reference/show_indicators_time-2.png | Bin 0 -> 41467 bytes docs/reference/show_indicators_time-3.png | Bin 0 -> 77077 bytes docs/reference/show_indicators_time-4.png | Bin 0 -> 58419 bytes docs/reference/show_indicators_time-5.png | Bin 0 -> 56418 bytes docs/reference/show_indicators_time-6.png | Bin 0 -> 43423 bytes docs/reference/show_indicators_time.html | 163 +++++ docs/reference/show_sectors.html | 35 +- docs/reference/show_sectors_rbm-1.png | Bin 0 -> 71100 bytes docs/reference/show_sectors_rbm.html | 119 ++++ docs/search.json | 2 +- docs/sitemap.xml | 12 + man/mapping_result.Rd | 23 + man/mapping_sector.Rd | 24 + man/show_budget_gap.Rd | 19 +- man/show_earmarking.Rd | 15 +- man/show_indicators_time.Rd | 67 ++ man/show_sectors.Rd | 35 +- man/show_sectors_rbm.Rd | 32 + vignettes/unhcr-programme.Rmd | 98 ++- 55 files changed, 2149 insertions(+), 125 deletions(-) create mode 100644 R/show_indicators_time.R create mode 100644 R/show_sectors_rbm.R create mode 100644 data/mapping_result.RData create mode 100644 data/mapping_sector.RData create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_budget_gap-2.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-1.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-2.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-3.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-4.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-5.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_indicators_time-6.png create mode 100644 docs/articles/unhcr-programme_files/figure-html/example-show_sectors_rbm-1.png create mode 100644 docs/reference/mapping_result.html create mode 100644 docs/reference/mapping_sector.html create mode 100644 docs/reference/show_budget_gap-2.png create mode 100644 docs/reference/show_indicators_time-1.png create mode 100644 docs/reference/show_indicators_time-2.png create mode 100644 docs/reference/show_indicators_time-3.png create mode 100644 docs/reference/show_indicators_time-4.png create mode 100644 docs/reference/show_indicators_time-5.png create mode 100644 docs/reference/show_indicators_time-6.png create mode 100644 docs/reference/show_indicators_time.html create mode 100644 docs/reference/show_sectors_rbm-1.png create mode 100644 docs/reference/show_sectors_rbm.html create mode 100644 man/mapping_result.Rd create mode 100644 man/mapping_sector.Rd create mode 100644 man/show_indicators_time.Rd create mode 100644 man/show_sectors_rbm.Rd diff --git a/NAMESPACE b/NAMESPACE index 8daef9f..ed63f66 100644 --- 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 index 04cd6ba..d5db019 100644 --- 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 index 29275eb..5d16285 100644 --- 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" ))) \ No newline at end of file diff --git a/R/show_budget_gap.R b/R/show_budget_gap.R index 9c6efe1..f7634c7 100644 --- 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 index 5b49bf2..0c4879e 100644 --- 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 index 42258bf..92c90e9 100644 --- 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) } diff --git a/R/show_indicators_time.R b/R/show_indicators_time.R new file mode 100644 index 0000000..9d1764d --- /dev/null +++ b/R/show_indicators_time.R @@ -0,0 +1,304 @@ +# WARNING - Generated by {fusen} from dev/dev_unhcr_programme.Rmd: do not edit by hand + +#' show_indicators_time +#' +#' How much indicators evolve over time against thresholds? +#' +#' @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 result_type_name either "Impact" "Outcome" "Output" - default is "Outcome" +#' @param type "deviation" showing difference between target and actual - or +#' "progress" showing difference between baseline and actual +#' +#' @import ggplot2 +#' @import dplyr +#' @import scales +#' @import unhcrthemes +#' @importFrom stats reorder +#' +#' @export +#' +#' @return a graph +#' @examples +#' show_indicators_time(year = 2020, +#' ctr_name = "Brazil", +#' result_type_name = "Outcome", +#' type = "deviation" +#' ) +#' show_indicators_time(year = 2022, +#' ctr_name = "Brazil", +#' result_type_name = "Impact", +#' type = "deviation" +#' ) +#' show_indicators_time(year = 2019, +#' ctr_name = "Brazil", +#' result_type_name = "Output", +#' type = "deviation" +#' ) +#' show_indicators_time(year = 2022, +#' ctr_name = "Brazil", +#' result_type_name = "Outcome", +#' type = "progress" +#' ) +#' show_indicators_time(year = 2022, +#' ctr_name = "Brazil", +#' result_type_name = "Impact", +#' type = "progress" +#' ) +#' show_indicators_time(year = 2019, +#' ctr_name = "Brazil", +#' result_type_name = "Output", +#' type = "progress" +#' ) +show_indicators_time <- function(year, + programme_lab = NULL, + iati_identifier_ops = NULL, + ctr_name = NULL , + result_type_name = "Outcome", + type = "deviation") { + + + # Check if only one argument is passed + if (!is.null(programme_lab) && !is.null(iati_identifier_ops)) { + stop("Please pass only one of the arguments programme_lab or iati_identifier_ops.") + } else if (!is.null(programme_lab) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments programme_lab or ctr_name.") + } else if (!is.null(iati_identifier_ops) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments iati_identifier_ops or ctr_name.") + } + + df <- iati::dataResult |> + dplyr::left_join(iati::dataActivity, by= c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + # levels(as.factor(df$result_type_name )) + dplyr::filter( programmme_lab == thisprogramme_lab & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + dplyr::filter( ctr_name == thisctr_name & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + } + + ## in order to compare indictors alltogether in the same country, we need to normalise them + ## one way is to compute the distance to the target... + ## names(df) + + #table(df$result_indicator_ascending, useNA = "ifany") + df1 <- df |> + dplyr::select(result_type_name , result_title, sector_rbm, + indicator_measure_name, result_indicator_title, + year, + + result_indicator_baseline_value, + result_indicator_actual_value, + result_indicator_target_value, + result_indicator_target_value_1, + + result_indicator_baseline_location_ref, + result_indicator_baseline_dimension_1, + result_indicator_baseline_dimension_value_1, + result_indicator_baseline_dimension_2, + result_indicator_baseline_dimension_value_2, + result_indicator_ascending) |> + + ## Quick fix in case ascending is not documented... + dplyr::mutate( result_indicator_ascending = dplyr::if_else( is.na(result_indicator_ascending), + + "1", + result_indicator_ascending)) |> + + dplyr::mutate( actual = as.numeric(result_indicator_actual_value), + baseline = as.numeric(result_indicator_baseline_value), + target = as.numeric(result_indicator_target_value), + ## Reshape the indicator label... + operation = as.character(glue::glue("{result_indicator_title} / {result_indicator_target_value_1}") ), + # operation = as.character(glue::glue("{result_indicator_title} / {result_title} - + # {result_indicator_target_value_1}") ), + + + ## Calculating deviation to target + deviation_actual_target = round( ( actual - target ) / + dplyr::if_else(target == 0, 1, target) * + dplyr::if_else(target == 0, 1, 100) ,2 ), + + ## Account for indicator direction + deviation_actual_target = dplyr::if_else(result_indicator_ascending == 0, + deviation_actual_target * -1, + deviation_actual_target), + + deviation_color = dplyr::case_when( + deviation_actual_target >= -1 ~ "green", + deviation_actual_target < -1 & deviation_actual_target >= -15 ~ "orange", + deviation_actual_target < -15 ~ "red", + TRUE ~ ""), + ## Calculating progress to baseline.. + progress_baseline = round( ( actual - baseline) / + dplyr::if_else(baseline == 0, 1, baseline) * + dplyr::if_else(baseline == 0, 1, 100) ,2 ), + ## Account for indicator direction + progress_baseline = dplyr::if_else(result_indicator_ascending == 0, + progress_baseline * -1, + progress_baseline), + progress_color = dplyr::case_when( + progress_baseline >= -1 ~ "green", + progress_baseline < -1 & progress_baseline >= -15 ~ "orange", + progress_baseline < -15 ~ "red", + TRUE ~ "") + + ) + + ### Type of chart to build... + if(type == "deviation") { + + df1 <- df1 |> + ## Filter out - when no data... + dplyr::filter (! (is.na(actual))) |> + dplyr::filter (! (is.na(target))) |> + dplyr::filter (! (is.nan(deviation_actual_target))) |> + #dplyr::arrange(desc(actual)) + dplyr::group_by( result_indicator_title) |> + dplyr::arrange(desc( actual), .by_group=TRUE ) |> + dplyr::ungroup(result_indicator_title) + + ## case there's no data at all + if( nrow(df1) == 0) { + info <- paste0("No deviation - actual to target - \n comparative analysis \n could be produced for \n", + result_type_name, " indicator values \n in ", + programme_lab, ctr_name,iati_identifier_ops, " for year: ", year) + p <- ggplot2::ggplot() + + ggplot2::annotate("text", x = 1, y = 1, size = 12, + label = info ) + + ggplot2::theme_void() + + } else if(nrow(df1)> 0) { + ## and now the plot + p <- ggplot2::ggplot( df1, + ggplot2::aes(x = year, + y = deviation_actual_target, + #shape = indicator_measure_name, + color = sector_rbm)) + + ggplot2::geom_jitter(position=position_jitter(0.2), + shape = 17, + size = 3) + + ggplot2::stat_summary(fun.data=mean_sdl, #mult=1, + geom="pointrange", color="grey", size = 3) + + geom_hline(yintercept= 0, color="red") + + # ggplot2::scale_color_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_colour_brewer(palette = "Paired") + + ggplot2::scale_y_continuous( label = scales::label_number(accuracy = 1, + scale_cut = scales::cut_short_scale(), + suffix = "%") )+ + ggplot2::scale_x_discrete(labels = function(x) stringr::str_wrap(x, width = 120)) + + unhcrthemes::theme_unhcr(font_size = 22, + axis_text_size = 9, + grid = "Y", + axis = "y") + + ggplot2::theme( legend.direction = "vertical", + legend.box = "horizontal", + legend.position = "right")+ + + ggplot2::labs( x = "", y = "" , + title = stringr::str_wrap( + paste0( result_type_name, " Indicators ", + programme_lab, ctr_name,iati_identifier_ops ) , + 100), + subtitle = stringr::str_wrap( paste0( + "Deviation between reported \"Actual\" value and programmatic \"Target\" (in %)" ) , + 110), + caption = stringr::str_wrap( + "Data Source: UNHCR IATI (International Aid Transparency Initiative)" , + 110) ) + } + } else if( type == "progress") { + + df1 <- df1 |> + ## Filter out - when no data... + dplyr::filter (! (is.na(actual))) |> + dplyr::filter (! (is.na(baseline))) |> + dplyr::filter (! (is.nan(progress_baseline))) |> + #dplyr::arrange(desc(actual)) + dplyr::group_by( result_indicator_title) |> + dplyr::arrange(desc( actual), .by_group=TRUE ) |> + dplyr::ungroup(result_indicator_title) + + ## case there's no data at all + if( nrow(df1) == 0) { + info <- paste0("No progress - actual to baseline - \n comparative analysis \n could be produced for \n", + result_type_name, " indicator values \n in ", + programme_lab, ctr_name,iati_identifier_ops, " for year: ", year) + p <- ggplot2::ggplot() + + ggplot2::annotate("text", x = 1, y = 1, size = 12, + label = info ) + + ggplot2::theme_void() + + } else if(nrow(df1)> 0) { + ## and now the plot + p <- ggplot2::ggplot( df1, + ggplot2::aes(x = year, + y = progress_baseline, + #shape = indicator_measure_name, + color = sector_rbm)) + + ggplot2::geom_jitter(position=position_jitter(0.2), + shape = 17, + size = 3) + + ggplot2::stat_summary(fun.data=mean_sdl, #mult=1, + geom="pointrange", color="grey", size = 3) + + geom_hline(yintercept= 0, color="red") + + # ggplot2::scale_color_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_colour_brewer(palette = "Paired") + + ggplot2::scale_y_continuous( label = scales::label_number(accuracy = 1, + scale_cut = scales::cut_short_scale(), + suffix = "%") )+ + ggplot2::scale_x_discrete(labels = function(x) stringr::str_wrap(x, width = 120)) + + unhcrthemes::theme_unhcr(font_size = 22, + axis_text_size = 9, + grid = "Y", + axis = "y") + + ggplot2::theme( legend.direction = "vertical", + legend.box = "horizontal", + legend.position = "right")+ + + ggplot2::labs( x = "", y = "" , + title = stringr::str_wrap( + paste0( result_type_name, " Indicators ", + programme_lab, ctr_name,iati_identifier_ops ) , + 100), + subtitle = stringr::str_wrap( paste0( + "Deviation between reported \"Actual\" value and programmatic \"Target\" (in %)" ) , + 110), + caption = stringr::str_wrap( + "Data Source: UNHCR IATI (International Aid Transparency Initiative)" , + 110) ) + } + } + return(p) + +} diff --git a/R/show_sectors.R b/R/show_sectors.R index 66a5b94..2652121 100644 --- a/R/show_sectors.R +++ b/R/show_sectors.R @@ -4,7 +4,7 @@ #' #' @description What are the most funded sectors per country (Expenditure evolution per impact /outcome area)? #' -#' @param year A numeric value corresponding to the first year of focus until the most recent year within the dataset. +#' @param year A numeric value or a list of value. #' @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. @@ -19,16 +19,30 @@ #' @export #' @return a graph #' @examples -#' #' knitr::kable( iati::dataSector |> #' dplyr::select( sector_vocabulary_name, sector_vocabulary_description) |> -#' dplyr::distinct()) -#' -#' show_sectors(year = 2018, -#' programme_lab = NULL, -#' iati_identifier_ops = NULL, -#' ctr_name = "Syria", -#' sector_vocabulary_name = "Reporting Organisation 2") +#' dplyr::distinct() |> +#' dplyr::filter(!(is.na(sector_vocabulary_name)))) +#' show_sectors( +#' year = c(2020, 2021, 2022), +#' ctr_name = "Brazil", +#' sector_vocabulary_name = "Reporting Organisation") +#' show_sectors( +#' year = 2022, +#' ctr_name = "Brazil", +#' sector_vocabulary_name = "Reporting Organisation 2") +#' show_sectors( +#' year = c(2020, 2021, 2022), +#' ctr_name = "Brazil", +#' sector_vocabulary_name = "Reporting Organisation 2") +#' show_sectors( +#' year = c(2017,2018,2019,2020,2021, 2022), +#' ctr_name = "Brazil", +#' sector_vocabulary_name = "Humanitarian Global Clusters (Inter-Agency Standing Committee)") +#' show_sectors( +#' year = c(2017,2018,2019,2020,2021, 2022), +#' ctr_name = "Brazil", +#' sector_vocabulary_name = "OECD DAC CRS Purpose Codes (5 digit)") show_sectors <- function(year, programme_lab = NULL, iati_identifier_ops = NULL, @@ -52,24 +66,27 @@ show_sectors <- function(year, thisyear <- year thissector_vocabulary <- sector_vocabulary df <- df |> + dplyr::mutate(year = factor(year)) |> dplyr::filter(programmme_lab == thiprogramme_lab & - year > thisyear & + year %in% thisyear & sector_vocabulary_name == thissector_vocabulary_name) } else if (!is.null(iati_identifier_ops)) { thisiati_identifier_ops <- iati_identifier_ops thisyear <- year thissector_vocabulary_name <- sector_vocabulary_name df <- df |> + dplyr::mutate(year = factor(year)) |> dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & - year > thisyear & + year %in% thisyear & sector_vocabulary_name == thissector_vocabulary_name) } else if (!is.null(ctr_name)) { thisctr_name <- ctr_name thisyear <- year thissector_vocabulary_name <- sector_vocabulary_name df <- df |> + dplyr::mutate(year = factor(year)) |> dplyr::filter(ctr_name == thisctr_name & - year > thisyear & + year %in% thisyear & sector_vocabulary_name == thissector_vocabulary_name) } @@ -85,13 +102,17 @@ show_sectors <- function(year, ggplot2::aes(x = stats::reorder(sector_desc, sector_pct), y = sector_pct )) + - unhcrthemes::theme_unhcr(grid = TRUE, axis = "Y", axis_title = "Sector Percentage") + - ggplot2::geom_bar(stat = "identity") + + # unhcrthemes::theme_unhcr(grid = TRUE, axis = "Y", axis_title = "Sector Percentage") + + unhcrthemes::theme_unhcr(grid = "X", axis = "y", axis_title = "X", font_size = 18) + + + ggplot2::geom_bar(stat = "identity", fill = "#0072BC") + ggplot2::coord_flip()+ ggplot2::facet_wrap( ggplot2::vars(year)) + ggplot2::scale_fill_viridis_d(option = "inferno", na.value = "grey50") + ggplot2::scale_y_continuous(expand = ggplot2::expansion(mult = c(0, .1)), labels = scales::label_number(scale_cut = scales::cut_short_scale())) + - ggplot2::labs(title = "Share of budget per sectors for the selected year", + ggplot2::labs(title = "Share of Budget per Sectors (%)", + subtitle = paste0("Recorded in ", programme_lab, ctr_name,iati_identifier_ops, + " based on vocabulary: ", sector_vocabulary_name), x = "Sectors", y = "% of Total Funding", caption = "Data Source: UNHCR IATI (International Aid Transparency Initiative)") diff --git a/R/show_sectors_rbm.R b/R/show_sectors_rbm.R new file mode 100644 index 0000000..14c3004 --- /dev/null +++ b/R/show_sectors_rbm.R @@ -0,0 +1,143 @@ +# WARNING - Generated by {fusen} from dev/dev_unhcr_programme.Rmd: do not edit by hand + + +#' show_sectors_rbm +#' +#' @description What are the most funded sectors per country based on new RBM framework +#' +#' @param year A numeric value or a list of value. +#' @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. +#' +#' @import ggplot2 +#' @import dplyr +#' @import scales +#' @import unhcrthemes +#' @importFrom stats reorder +#' +#' @export +#' @return a graph +#' @examples +#' show_sectors_rbm( year = c(2017, 2018, 2019, 2020, 2021, 2022), +#' ctr_name = "Brazil") +show_sectors_rbm <- function(year, + programme_lab = NULL, + iati_identifier_ops = NULL, + ctr_name = NULL ){ + # Check if only one argument is passed + if (!is.null(programme_lab) && !is.null(iati_identifier_ops)) { + stop("Please pass only one of the arguments programme_lab or iati_identifier_ops.") + } else if (!is.null(programme_lab) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments programme_lab or ctr_name.") + } else if (!is.null(iati_identifier_ops) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments iati_identifier_ops or ctr_name.") + } + + # Join dataActivity and dataSector on iati_identifier + df <- iati::dataSector |> + dplyr::left_join(iati::dataActivity, by = c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(programmme_lab == thiprogramme_lab & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(ctr_name == thisctr_name & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } + + df <- df |> + dplyr::group_by(sector_desc, sector_rbm, year) |> + dplyr::summarise(sector_pct = mean( as.numeric(sector_pct)) ) |> + dplyr::group_by( sector_rbm, year) |> + dplyr::summarise(sector_pct = sum(sector_pct, rm.na = TRUE)) |> + # dplyr::summarise(sector_pct = sum(sector_pct, na.rm = TRUE)/sum(df$sector_pct, na.rm = TRUE)*100) |> + # top_n(5, wt = sector_pct) |> + dplyr::mutate(sector_rbm = as.factor(sector_rbm)) + + + ## Now joining budget & Expenditure to make the chart more informative... + df_bud <- iati::dataTransaction |> + dplyr::left_join(iati::dataActivity, by= c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + df_bud <- df_bud |> + # levels(as.factor(df$programmme_lab)) + dplyr::filter( programmme_lab == thisprogramme_lab & + year %in% thisyear & + transaction_type_name == "Expenditure") + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + df_bud <- df_bud |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year %in% thisyear & + transaction_type_name == "Expenditure") + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + df_bud <- df_bud |> + dplyr::filter( ctr_name == thisctr_name & + year %in% thisyear & + transaction_type_name == "Expenditure") + } + + df_bud2 <- df_bud |> + dplyr::group_by(iati_identifier, year) |> + dplyr::summarise(transaction_value= sum(transaction_value, na.rm = TRUE)) |> + dplyr::left_join(iati::dataBudget |> + dplyr::mutate(budget_value= as.numeric(budget_value)) |> + dplyr::group_by(iati_identifier) |> + dplyr::summarise(budget_value= sum(budget_value, na.rm = TRUE)) + , by= c("iati_identifier")) |> + dplyr::select(iati_identifier, year,budget_value, transaction_value ) |> + dplyr::mutate( year2 = glue::glue('{year} - Bud:{scales::label_number(accuracy = .2, scale_cut = scales::cut_short_scale())(budget_value)}$/ Exp:{scales::label_number(accuracy = .2, scale_cut = scales::cut_short_scale())(transaction_value)}$ ')) + + df <- df |> + dplyr::left_join(df_bud2, by = c("year")) + + + + p <- ggplot2::ggplot(data = df, + ggplot2::aes(x = stats::reorder(sector_rbm, sector_pct), + y = sector_pct + )) + + # unhcrthemes::theme_unhcr(grid = TRUE, axis = "Y", axis_title = "Sector Percentage") + + unhcrthemes::theme_unhcr(grid = "X", axis = "y", axis_title = "X", font_size = 18) + + + ggplot2::geom_bar(stat = "identity", fill = "#0072BC") + + ggplot2::coord_flip()+ + ggplot2::facet_wrap( ggplot2::vars(year2)) + + ggplot2::scale_fill_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_y_continuous(expand = ggplot2::expansion(mult = c(0, .1)), labels = scales::label_number(scale_cut = scales::cut_short_scale())) + + ggplot2::labs(title = "Share of Budget per Sectors (%)", + subtitle = paste0("Recorded in ", programme_lab, ctr_name,iati_identifier_ops, + " based on UNHCR Results Framework "), + x = "Sectors", y = "% of Total Funding", + 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/_pkgdown.yml b/_pkgdown.yml index 942add9..5b6e169 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -15,6 +15,10 @@ reference: desc: Lookup tables contents: - starts_with("code") +- title: Mapping + desc: Mapping tables + contents: + - starts_with("mapping") - title: Reference desc: UNHCR Geographci Referential contents: diff --git a/data/mapping_result.RData b/data/mapping_result.RData new file mode 100644 index 0000000000000000000000000000000000000000..82a13ede8ce29b2d277ee50f3c20fd2e4c50a59a GIT binary patch literal 1828 zcmV+<2iy1`iwFP!000001Jzn>a}zfZb_ro7yia*)OG^WYN+)3k% zO%uLl)e@KC z=l4+RMu~Q)jikcLlgQ$x=MV-1%2_CJy~G{IV^sB!!yDA5ALFYRw{aI?W+9i`)a-?` z=W9d~rEH>&g>ygD-@e{Mt{@$l0|UMm?9Js&l2B&3PDF>AM4~1a$R$F;BI;7rM$#oF zZBi34LM$1|e_iLcr;SNCfxwEiq8(hVhbJP62#2!xo-dc$)P@}ku829o{CE#6l`YR4 zJ8@=h6iRKsgA&tbS!QB$i zlMhrX!b}qE+~y{>kr}23B{I9{nKC1ypSHuJJ8uQi8-N}9;RVO?rjJ!(6Db+|WR^@N z+|4?%n|VQOiuGo-Gi^vDo3=UcM`I$P!(4iaa(x-`5!=0{ntVKuxV+K$(WU))-KS=el+enQcr1_uE{@gPM~|jL6x$+oT2G z6Tq4l;5Sh7r?8ZutdWsj^k#{3VTIfjL=p=HEFjy|m05(A4GTCf%sZ$A6>toMGANH) zXIEfI^Zu8!%0I3`Cg5P%!3?+j^05L*k=UCA=W?NDQ#-u0FYf?ogzsL-Jz<9am2C{< zhY0IX!C9=bWtG2Tm>{F`A3@RqS8~xidg;<8XI%5I9h`Oibhd=PS|cWLeMbQTEgH8p zZta^L&hl6^C^!&ES(iZ;OXwq(Q3*S4EM)#J<59~fceU(5ZG(!~iwS3AyKyEiyn#}L zBr!dROK;rdwIt)4f;wc9#m&Mhs(K2lIMhI>xG&L&gjn%IIYj@XIPKnA($<)6<^Fn7 z_$^@;5%~s|ki;FzZ8G4LSI?5tgASIkRy!lQ;j;sOK6;)svQKO~-vD}V z`Kk@SD#v@a^%tolc@Rc8O2dZElzTGL9kid3ZW&x#aa>@W$g@goYK125aN(O6wB~W# zO0*mX?Lla)R4Ar)5^rEu5CO1o2lh{yX~Vw4K&6|S7ln0={a!FuCVeYhwV{Cv`a~I#Uufj#wS;$S(B{*R+B<@_+Ta4HV-hz>!Y?(y zfwv;R>=YAb%0bw*omgw?ZwH%gN;-O_<)<1Ve?WQGDYP7FMOGiKC#=?eyn$x_7-$*j zyhHjLsqn;57j!Z~IB+-AxSfi^A(ypVg(peL;KJ2I+YsEyq2Cu$P)=UkHVP?(mTZC< z>grB=1>8O6y7Q)xLTtP{h8z(zUitig3lt8`U*@x84ZFjxitSAc>rHni!iz$U^MY0u{DIz%nC%>Z#I~Resu3eF=K&aUQBAc__YzQTMp{yLf6)OszP-XwAS$Gt=1^BtCc2$f$@J^PvQdDV)_S2fo9Zg1tH@On z4#~xVXgCQIOM-V-BQqDYnNRS?=g*)2On%F>v5da85Kf*^4g0`qhNA@-MIW@V!mCXI ShGF!N{`nUTzUsjWBme-+{C?8_ literal 0 HcmV?d00001 diff --git a/data/mapping_sector.RData b/data/mapping_sector.RData new file mode 100644 index 0000000000000000000000000000000000000000..6f551c941dbb723db6a995ce1dbaacf3362b73e1 GIT binary patch literal 1862 zcmV-M2f6qkiwFP!000001MON}bJIo?bqO#7G%e+;0ZLg)flv}4BrUDmJ}8a@Zb_W6 zDd8=%k=FJOl2)^l9L!VyQ2%1-S*=!5Y$vfDXlFWp2t>NOckjo!=iU`G)?P24eSNl6 zD$SHm&YURCoWifAQ-8c%U;MFDI(Y&QpOj9P&fxFQJQ@VtZ|{W6j)cUHi^;Z9={$a# zX4MP2N2u?RE#Y#zm%hFIg0-nj8q8x3XJN8Hzp}!RhY|H{mM(p;74Kpvv7(4av4h2t z*rU=3$rh8L@IxY6q$03E`stQy4c3MdNh2eDuS|Z+O*`)@vS&*EMOgcQ#oyz8Fc+urf3~&sK`sH=%akmGp zi-;5Aw@-+~M}Vi&+>*j070Eqg=q;7~JX7luamNzCX+w02=3OahQDEzE*OAPear!x< zZq!Mit~Xd9g%jIJth6Xm|Gf4pU2KuKG-7;Fw#bA#kQvuL+MKoi?dO%rhZBQ-%G- zFy5|+MfMgDU??+<))&G?LJT@l!|Bo+P3E?c4411K)`g8oxV!@&&7$+KfLo+dskt(DYV0AaF)9>nzd)LAxC`C@CA%WXpz*se_FU$)SphSK zigL#XWEXS~E2=Zp|B~4qpR1Cfd1%9Zq5Wk`a-r&8V{9RV4Y6ET*g3%0xrz#ht^o_q zSKlTfMxSi8D3`|dyX&!vHsv9_Hc8UThqR4vHqdoxUuaF6-KX~oIusg}mt<+cnxE^) zV948@h|D9wfd@_aaqEc22Y`9aGZE*KH zQx*MCTw@5JNz8KII86z<^_|H>p@7r!18hwKVeXlq^ znD7SrQL*+GjXHa@XO=(E-JrnU$sU3JFVjwuO)7@6o9u0zvcxmyJE-_w8iMg&apAIj z{5zj?Tat5EHf+%ri}X;DNA0&bEKDK``S4Wr+r{3njkf3C3&C=M*uw-^An9%9x{IsK z)RAtL#gS|=tHC~{hn3vb0{Nyal0=^FnMtMD3snm?X zu+DY$1*488aSep5CG_1Q=AarrD_3+qh5C>uQ~6Xrl~3hU`BXlYPvukjR6dq`|D5@C z-C8b_qh|G6b?b*R8Q}sln!3kzYpF~Qy81ml@XGgZ@4HjCR?4H^+iupaAIs#(%hXcc zdRitE+|!=G2_%7xfAd_#&hN`)yc_O!Rci_UjByY9f8~B;$ba~Sm+KbNb--tUi}2@h znGE~*F_~yY+}?+VC$MVdYx39|=Iho^Wit9@e%$pVI{G>624edEMPTB(eF}ZcibW>- zFjdBOkkB!{IZRF*<8#2cIa#h+Pk_rwJ}`Z3xJ(|lkqdqDBPM0F(Kz~JasN$Z8)hH; z4eZ#Un1kiW@`0cE#`o;QYrKvfppwHre;y+O|IOB;qI6vO2r(N!5##R|5x^r@J81zQ z(#Vh5XeOExCugv+X6r*IqLJx#;ub#QyADc469%+L=nvrc$}<_31w&#oj}6#w>nL z{E0u_zkmN%zah3u!+t|fN4xHh(@LLa@MI2jXha{jq%xsY`dj_{0}*<7xV + 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) |> @@ -786,10 +858,10 @@ 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) @@ -799,6 +871,12 @@ show_budget_gap <- function(year, ```{r example-show_budget_gap, message=FALSE, warning=FALSE, fig.retina = 2, fig.width = 8, fig.asp = 0.618, fig.align = "center", out.width = "90%"} show_budget_gap(year = 2018, ctr_name = "Brazil") + + + +show_budget_gap(year = 2018, + ctr_name = "Brazil", + weight_by = c("refugees", "oip")) ``` ```{r tests-show_budget_gap} @@ -1057,21 +1135,26 @@ knitr::kable( iati::dataSector |> dplyr::select( sector_vocabulary_name, sector_vocabulary_description) |> dplyr::distinct() |> dplyr::filter(!(is.na(sector_vocabulary_name)))) -show_sectors(year = c(2020, 2021, 2022), - ctr_name = "Brazil", - sector_vocabulary_name = "Reporting Organisation") -show_sectors(year = 2022, - ctr_name = "Brazil", - sector_vocabulary_name = "Reporting Organisation 2") -show_sectors(year = c(2020, 2021, 2022), - ctr_name = "Brazil", - sector_vocabulary_name = "Reporting Organisation 2") -show_sectors(year = c(2017,2018,2019,2020,2021, 2022), - ctr_name = "Brazil", - sector_vocabulary_name = "Humanitarian Global Clusters (Inter-Agency Standing Committee)") -show_sectors(year = c(2017,2018,2019,2020,2021, 2022), - ctr_name = "Brazil", - sector_vocabulary_name = "OECD DAC CRS Purpose Codes (5 digit)") +show_sectors( + year = c(2020, 2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation") +show_sectors( + year = 2022, + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation 2") +show_sectors( + year = c(2020, 2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation 2") +show_sectors( + year = c(2017,2018,2019,2020,2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Humanitarian Global Clusters (Inter-Agency Standing Committee)") +show_sectors( + year = c(2017,2018,2019,2020,2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "OECD DAC CRS Purpose Codes (5 digit)") ``` ```{r tests-show_sectors} @@ -1079,7 +1162,162 @@ test_that("show_sectors works", { expect_true(inherits(show_sectors, "function")) }) ``` + + +## show_sectors_rbm + +```{r function-show_sectors_rbm} + +#' show_sectors_rbm +#' +#' @description What are the most funded sectors per country based on new RBM framework +#' +#' @param year A numeric value or a list of value. +#' @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. +#' +#' @import ggplot2 +#' @import dplyr +#' @import scales +#' @import unhcrthemes +#' @importFrom stats reorder +#' +#' @export +#' @return a graph +show_sectors_rbm <- function(year, + programme_lab = NULL, + iati_identifier_ops = NULL, + ctr_name = NULL ){ + # Check if only one argument is passed + if (!is.null(programme_lab) && !is.null(iati_identifier_ops)) { + stop("Please pass only one of the arguments programme_lab or iati_identifier_ops.") + } else if (!is.null(programme_lab) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments programme_lab or ctr_name.") + } else if (!is.null(iati_identifier_ops) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments iati_identifier_ops or ctr_name.") + } + + # Join dataActivity and dataSector on iati_identifier + df <- iati::dataSector |> + dplyr::left_join(iati::dataActivity, by = c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(programmme_lab == thiprogramme_lab & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + df <- df |> + dplyr::mutate(year = factor(year)) |> + dplyr::filter(ctr_name == thisctr_name & + year %in% thisyear & + sector_vocabulary_name == "Reporting Organisation 2") |> + dplyr::left_join(iati::mapping_sector, by= c("sector_desc")) + } + + df <- df |> + dplyr::group_by(sector_desc, sector_rbm, year) |> + dplyr::summarise(sector_pct = mean( as.numeric(sector_pct)) ) |> + dplyr::group_by( sector_rbm, year) |> + dplyr::summarise(sector_pct = sum(sector_pct, rm.na = TRUE)) |> + # dplyr::summarise(sector_pct = sum(sector_pct, na.rm = TRUE)/sum(df$sector_pct, na.rm = TRUE)*100) |> + # top_n(5, wt = sector_pct) |> + dplyr::mutate(sector_rbm = as.factor(sector_rbm)) + + + ## Now joining budget & Expenditure to make the chart more informative... + df_bud <- iati::dataTransaction |> + dplyr::left_join(iati::dataActivity, by= c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + df_bud <- df_bud |> + # levels(as.factor(df$programmme_lab)) + dplyr::filter( programmme_lab == thisprogramme_lab & + year %in% thisyear & + transaction_type_name == "Expenditure") + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + df_bud <- df_bud |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year %in% thisyear & + transaction_type_name == "Expenditure") + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + df_bud <- df_bud |> + dplyr::filter( ctr_name == thisctr_name & + year %in% thisyear & + transaction_type_name == "Expenditure") + } + + df_bud2 <- df_bud |> + dplyr::group_by(iati_identifier, year) |> + dplyr::summarise(transaction_value= sum(transaction_value, na.rm = TRUE)) |> + dplyr::left_join(iati::dataBudget |> + dplyr::mutate(budget_value= as.numeric(budget_value)) |> + dplyr::group_by(iati_identifier) |> + dplyr::summarise(budget_value= sum(budget_value, na.rm = TRUE)) + , by= c("iati_identifier")) |> + dplyr::select(iati_identifier, year,budget_value, transaction_value ) |> + dplyr::mutate( year2 = glue::glue('{year} - Bud:{scales::label_number(accuracy = .2, scale_cut = scales::cut_short_scale())(budget_value)}$/ Exp:{scales::label_number(accuracy = .2, scale_cut = scales::cut_short_scale())(transaction_value)}$ ')) + + df <- df |> + dplyr::left_join(df_bud2, by = c("year")) + + + p <- ggplot2::ggplot(data = df, + ggplot2::aes(x = stats::reorder(sector_rbm, sector_pct), + y = sector_pct + )) + + # unhcrthemes::theme_unhcr(grid = TRUE, axis = "Y", axis_title = "Sector Percentage") + + unhcrthemes::theme_unhcr(grid = "X", axis = "y", axis_title = "X", font_size = 18) + + + ggplot2::geom_bar(stat = "identity", fill = "#0072BC") + + ggplot2::coord_flip()+ + ggplot2::facet_wrap( ggplot2::vars(year2)) + + ggplot2::scale_fill_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_y_continuous(expand = ggplot2::expansion(mult = c(0, .1)), labels = scales::label_number(scale_cut = scales::cut_short_scale())) + + ggplot2::labs(title = "Share of Budget per Sectors (%)", + subtitle = paste0("Recorded in ", programme_lab, ctr_name,iati_identifier_ops, + " based on UNHCR Results Framework "), + x = "Sectors", y = "% of Total Funding", + 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) +} +``` + +```{r example-show_sectors_rbm} +show_sectors_rbm( year = c(2017, 2018, 2019, 2020, 2021, 2022), + ctr_name = "Brazil") +``` + +```{r tests-show_sectors_rbm} +test_that("show_sectors_rbm works", { + expect_true(inherits(show_sectors_rbm, "function")) +}) +``` + # Using `iati::dataResult` @@ -1399,6 +1637,322 @@ test_that("show_indicators works", { expect_true(inherits(show_indicators, "function")) }) ``` + +## show_indicators_time + + +```{r function-show_indicators_time} +#' show_indicators_time +#' +#' How much indicators evolve over time against thresholds? +#' +#' @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 result_type_name either "Impact" "Outcome" "Output" - default is "Outcome" +#' @param type "deviation" showing difference between target and actual - or +#' "progress" showing difference between baseline and actual +#' +#' @import ggplot2 +#' @import dplyr +#' @import scales +#' @import unhcrthemes +#' @importFrom stats reorder +#' +#' @export +#' +#' @return a graph +show_indicators_time <- function(year, + programme_lab = NULL, + iati_identifier_ops = NULL, + ctr_name = NULL , + result_type_name = "Outcome", + type = "deviation") { + + + # Check if only one argument is passed + if (!is.null(programme_lab) && !is.null(iati_identifier_ops)) { + stop("Please pass only one of the arguments programme_lab or iati_identifier_ops.") + } else if (!is.null(programme_lab) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments programme_lab or ctr_name.") + } else if (!is.null(iati_identifier_ops) && !is.null(ctr_name)) { + stop("Please pass only one of the arguments iati_identifier_ops or ctr_name.") + } + + df <- iati::dataResult |> + dplyr::left_join(iati::dataActivity, by= c("iati_identifier")) + + if (!is.null(programme_lab)) { + thisprogramme_lab <- programme_lab + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + # levels(as.factor(df$result_type_name )) + dplyr::filter( programmme_lab == thisprogramme_lab & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + + } else if (!is.null(iati_identifier_ops)) { + thisiati_identifier_ops <- iati_identifier_ops + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + dplyr::filter(iati_identifier_ops == thisiati_identifier_ops & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + + } else if (!is.null(ctr_name)) { + thisctr_name <- ctr_name + thisyear <- year + thisresult_type_name <- result_type_name + df <- df |> + dplyr::filter( ctr_name == thisctr_name & + year >= thisyear & + result_type_name == thisresult_type_name) |> + dplyr::left_join(iati::mapping_result, by= c("result_title")) |> + dplyr::distinct() + } + + ## in order to compare indictors alltogether in the same country, we need to normalise them + ## one way is to compute the distance to the target... + ## names(df) + + #table(df$result_indicator_ascending, useNA = "ifany") + df1 <- df |> + dplyr::select(result_type_name , result_title, sector_rbm, + indicator_measure_name, result_indicator_title, + year, + + result_indicator_baseline_value, + result_indicator_actual_value, + result_indicator_target_value, + result_indicator_target_value_1, + + result_indicator_baseline_location_ref, + result_indicator_baseline_dimension_1, + result_indicator_baseline_dimension_value_1, + result_indicator_baseline_dimension_2, + result_indicator_baseline_dimension_value_2, + result_indicator_ascending) |> + + ## Quick fix in case ascending is not documented... + dplyr::mutate( result_indicator_ascending = dplyr::if_else( is.na(result_indicator_ascending), + + "1", + result_indicator_ascending)) |> + + dplyr::mutate( actual = as.numeric(result_indicator_actual_value), + baseline = as.numeric(result_indicator_baseline_value), + target = as.numeric(result_indicator_target_value), + ## Reshape the indicator label... + operation = as.character(glue::glue("{result_indicator_title} / {result_indicator_target_value_1}") ), + # operation = as.character(glue::glue("{result_indicator_title} / {result_title} - + # {result_indicator_target_value_1}") ), + + + ## Calculating deviation to target + deviation_actual_target = round( ( actual - target ) / + dplyr::if_else(target == 0, 1, target) * + dplyr::if_else(target == 0, 1, 100) ,2 ), + + ## Account for indicator direction + deviation_actual_target = dplyr::if_else(result_indicator_ascending == 0, + deviation_actual_target * -1, + deviation_actual_target), + + deviation_color = dplyr::case_when( + deviation_actual_target >= -1 ~ "green", + deviation_actual_target < -1 & deviation_actual_target >= -15 ~ "orange", + deviation_actual_target < -15 ~ "red", + TRUE ~ ""), + ## Calculating progress to baseline.. + progress_baseline = round( ( actual - baseline) / + dplyr::if_else(baseline == 0, 1, baseline) * + dplyr::if_else(baseline == 0, 1, 100) ,2 ), + ## Account for indicator direction + progress_baseline = dplyr::if_else(result_indicator_ascending == 0, + progress_baseline * -1, + progress_baseline), + progress_color = dplyr::case_when( + progress_baseline >= -1 ~ "green", + progress_baseline < -1 & progress_baseline >= -15 ~ "orange", + progress_baseline < -15 ~ "red", + TRUE ~ "") + + ) + + ### Type of chart to build... + if(type == "deviation") { + + df1 <- df1 |> + ## Filter out - when no data... + dplyr::filter (! (is.na(actual))) |> + dplyr::filter (! (is.na(target))) |> + dplyr::filter (! (is.nan(deviation_actual_target))) |> + #dplyr::arrange(desc(actual)) + dplyr::group_by( result_indicator_title) |> + dplyr::arrange(desc( actual), .by_group=TRUE ) |> + dplyr::ungroup(result_indicator_title) + + ## case there's no data at all + if( nrow(df1) == 0) { + info <- paste0("No deviation - actual to target - \n comparative analysis \n could be produced for \n", + result_type_name, " indicator values \n in ", + programme_lab, ctr_name,iati_identifier_ops, " for year: ", year) + p <- ggplot2::ggplot() + + ggplot2::annotate("text", x = 1, y = 1, size = 12, + label = info ) + + ggplot2::theme_void() + + } else if(nrow(df1)> 0) { + ## and now the plot + p <- ggplot2::ggplot( df1, + ggplot2::aes(x = year, + y = deviation_actual_target, + #shape = indicator_measure_name, + color = sector_rbm)) + + ggplot2::geom_jitter(position=position_jitter(0.2), + shape = 17, + size = 3) + + ggplot2::stat_summary(fun.data=mean_sdl, #mult=1, + geom="pointrange", color="grey", size = 3) + + geom_hline(yintercept= 0, color="red") + + # ggplot2::scale_color_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_colour_brewer(palette = "Paired") + + ggplot2::scale_y_continuous( label = scales::label_number(accuracy = 1, + scale_cut = scales::cut_short_scale(), + suffix = "%") )+ + ggplot2::scale_x_discrete(labels = function(x) stringr::str_wrap(x, width = 120)) + + unhcrthemes::theme_unhcr(font_size = 22, + axis_text_size = 9, + grid = "Y", + axis = "y") + + ggplot2::theme( legend.direction = "vertical", + legend.box = "horizontal", + legend.position = "right")+ + + ggplot2::labs( x = "", y = "" , + title = stringr::str_wrap( + paste0( result_type_name, " Indicators ", + programme_lab, ctr_name,iati_identifier_ops ) , + 100), + subtitle = stringr::str_wrap( paste0( + "Deviation between reported \"Actual\" value and programmatic \"Target\" (in %)" ) , + 110), + caption = stringr::str_wrap( + "Data Source: UNHCR IATI (International Aid Transparency Initiative)" , + 110) ) + } + } else if( type == "progress") { + + df1 <- df1 |> + ## Filter out - when no data... + dplyr::filter (! (is.na(actual))) |> + dplyr::filter (! (is.na(baseline))) |> + dplyr::filter (! (is.nan(progress_baseline))) |> + #dplyr::arrange(desc(actual)) + dplyr::group_by( result_indicator_title) |> + dplyr::arrange(desc( actual), .by_group=TRUE ) |> + dplyr::ungroup(result_indicator_title) + + ## case there's no data at all + if( nrow(df1) == 0) { + info <- paste0("No progress - actual to baseline - \n comparative analysis \n could be produced for \n", + result_type_name, " indicator values \n in ", + programme_lab, ctr_name,iati_identifier_ops, " for year: ", year) + p <- ggplot2::ggplot() + + ggplot2::annotate("text", x = 1, y = 1, size = 12, + label = info ) + + ggplot2::theme_void() + + } else if(nrow(df1)> 0) { + ## and now the plot + p <- ggplot2::ggplot( df1, + ggplot2::aes(x = year, + y = progress_baseline, + #shape = indicator_measure_name, + color = sector_rbm)) + + ggplot2::geom_jitter(position=position_jitter(0.2), + shape = 17, + size = 3) + + ggplot2::stat_summary(fun.data=mean_sdl, #mult=1, + geom="pointrange", color="grey", size = 3) + + geom_hline(yintercept= 0, color="red") + + # ggplot2::scale_color_viridis_d(option = "inferno", na.value = "grey50") + + ggplot2::scale_colour_brewer(palette = "Paired") + + ggplot2::scale_y_continuous( label = scales::label_number(accuracy = 1, + scale_cut = scales::cut_short_scale(), + suffix = "%") )+ + ggplot2::scale_x_discrete(labels = function(x) stringr::str_wrap(x, width = 120)) + + unhcrthemes::theme_unhcr(font_size = 22, + axis_text_size = 9, + grid = "Y", + axis = "y") + + ggplot2::theme( legend.direction = "vertical", + legend.box = "horizontal", + legend.position = "right")+ + + ggplot2::labs( x = "", y = "" , + title = stringr::str_wrap( + paste0( result_type_name, " Indicators ", + programme_lab, ctr_name,iati_identifier_ops ) , + 100), + subtitle = stringr::str_wrap( paste0( + "Deviation between reported \"Actual\" value and programmatic \"Target\" (in %)" ) , + 110), + caption = stringr::str_wrap( + "Data Source: UNHCR IATI (International Aid Transparency Initiative)" , + 110) ) + } + } + return(p) + +} +``` + +```{r example-show_indicators_time, message=FALSE, warning=FALSE, fig.retina = 2, fig.width = 8, fig.align = "center", out.width = "90%"} +show_indicators_time(year = 2020, + ctr_name = "Brazil", + result_type_name = "Outcome", + type = "deviation" + ) +show_indicators_time(year = 2022, + ctr_name = "Brazil", + result_type_name = "Impact", + type = "deviation" + ) +show_indicators_time(year = 2019, + ctr_name = "Brazil", + result_type_name = "Output", + type = "deviation" + ) +show_indicators_time(year = 2022, + ctr_name = "Brazil", + result_type_name = "Outcome", + type = "progress" + ) +show_indicators_time(year = 2022, + ctr_name = "Brazil", + result_type_name = "Impact", + type = "progress" + ) +show_indicators_time(year = 2019, + ctr_name = "Brazil", + result_type_name = "Output", + type = "progress" + ) +``` + +```{r tests-show_indicators_time} +test_that("show_indicators_time works", { + expect_true(inherits(show_indicators_time, "function")) +}) +``` diff --git a/docs/articles/unhcr-programme.html b/docs/articles/unhcr-programme.html index 8ce0a4d..ca345d8 100644 --- a/docs/articles/unhcr-programme.html +++ b/docs/articles/unhcr-programme.html @@ -319,6 +319,14 @@

show_budget_gapshow_budget_gap(year = 2018, ctr_name = "Brazil")

+
+
+
+
+show_budget_gap(year = 2018, 
+             ctr_name = "Brazil",
+             weight_by = c("refugees", "oip"))
+

@@ -330,7 +338,7 @@

Show partnership
  • How organisations partner together?
  • -
    +
     show_partnership(year = 2022,
                ctr_name = "Brazil" ) 
    @@ -411,7 +419,7 @@

    show_sectors
    +
     knitr::kable( iati::dataSector |> 
                     dplyr::select( sector_vocabulary_name, sector_vocabulary_description) |>
                     dplyr::distinct() |>
    @@ -450,32 +458,45 @@ 

    show_sectors
    -show_sectors(year =  c(2020, 2021, 2022), 
    -             ctr_name = "Brazil",
    -            sector_vocabulary_name = "Reporting Organisation")

    -

    -show_sectors(year = 2022, 
    -             ctr_name = "Brazil",
    -            sector_vocabulary_name = "Reporting Organisation 2")
    -

    +show_sectors( + year = c(2020, 2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation")
    +

    -show_sectors(year = c(2020, 2021, 2022),  
    -             ctr_name = "Brazil",
    -            sector_vocabulary_name = "Reporting Organisation 2")
    -

    +show_sectors( + year = 2022, + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation 2") +

    -show_sectors(year = c(2017,2018,2019,2020,2021, 2022), 
    -             ctr_name = "Brazil",
    -            sector_vocabulary_name = "Humanitarian Global Clusters (Inter-Agency Standing Committee)")
    -

    +show_sectors( + year = c(2020, 2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Reporting Organisation 2") +

    -show_sectors(year = c(2017,2018,2019,2020,2021, 2022), 
    -             ctr_name = "Brazil",
    -            sector_vocabulary_name = "OECD DAC CRS Purpose Codes (5 digit)")
    +show_sectors( + year = c(2017,2018,2019,2020,2021, 2022), + ctr_name = "Brazil", + sector_vocabulary_name = "Humanitarian Global Clusters (Inter-Agency Standing Committee)") +

    +
    +show_sectors(
    +  year = c(2017,2018,2019,2020,2021, 2022), 
    +  ctr_name = "Brazil",
    +  sector_vocabulary_name = "OECD DAC CRS Purpose Codes (5 digit)")

    +
    +

    show_sectors_rbm +

    +
    +show_sectors_rbm( year =  c(2017, 2018, 2019, 2020, 2021, 2022), 
    +             ctr_name = "Brazil")
    +

    +

    Using iati::dataResult @@ -487,42 +508,42 @@

    show_indicatorsHow much indicators relate to target or baseline? -
    +
     show_indicators(year = 2022,  
                  ctr_name = "Brazil",
                   result_type_name = "Outcome",
                  type = "deviation"
                  )

    -
    +
     show_indicators(year = 2022,  
                  ctr_name = "Brazil",
                   result_type_name = "Impact",
                  type = "deviation"
                  )

    -
    +
     show_indicators(year = 2019,  
                  ctr_name = "Brazil",
                   result_type_name = "Output",
                  type = "deviation"
                  )

    -
    +
     show_indicators(year = 2022,  
                  ctr_name = "Brazil",
                   result_type_name = "Outcome",
                  type = "progress"
                  )

    -
    +
     show_indicators(year = 2022,  
                  ctr_name = "Brazil",
                   result_type_name = "Impact",
                  type = "progress"
                  )

    -
    +
     show_indicators(year = 2019,  
                  ctr_name = "Brazil",
                   result_type_name = "Output",
    @@ -530,6 +551,52 @@ 

    show_indicators )

    +
    +

    show_indicators_time +

    +
    +show_indicators_time(year = 2020,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Outcome",
    +             type = "deviation"
    +             )
    +

    +
    +show_indicators_time(year = 2022,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Impact",
    +             type = "deviation"
    +             )
    +

    +
    +show_indicators_time(year = 2019,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Output",
    +             type = "deviation"
    +             )
    +

    +
    +show_indicators_time(year = 2022,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Outcome",
    +             type = "progress"
    +             )
    +

    +
    +show_indicators_time(year = 2022,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Impact",
    +             type = "progress"
    +             )
    +

    +
    +show_indicators_time(year = 2019,  
    +             ctr_name = "Brazil",
    +              result_type_name = "Output",
    +             type = "progress"
    +             )
    +

    +
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diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index b574f73..ae01882 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -3,5 +3,5 @@ pkgdown: 2.0.7 pkgdown_sha: ~ articles: unhcr-programme: unhcr-programme.html -last_built: 2024-02-15T23:42Z +last_built: 2024-02-22T23:55Z diff --git a/docs/reference/index.html b/docs/reference/index.html index da21542..c6153ff 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -92,6 +92,11 @@

    Chart Libraryshow_indicators_time() +

    +
    show_indicators_time
    +
    + show_partnership()
    show_partnership
    @@ -102,6 +107,11 @@

    Chart Libraryshow_sectors_rbm() + +
    show_sectors_rbm
    +

    + show_top_donors()
    show_top_donors
    @@ -368,6 +378,27 @@

    Code

    codeUNSDGTargets
    +

    Mapping

    + +

    Mapping tables

    + + +
    + + + + +
    + + mapping_result +
    +
    mapping_result
    +
    + + mapping_sector +
    +
    mapping_sector
    +

    Reference

    UNHCR Geographci Referential

    diff --git a/docs/reference/mapping_result.html b/docs/reference/mapping_result.html new file mode 100644 index 0000000..cfd4a8d --- /dev/null +++ b/docs/reference/mapping_result.html @@ -0,0 +1,97 @@ + +mapping_result — mapping_result • iati + Skip to contents + + +
    +
    +
    + +
    +

    Mapping Results to UNHCR 2022 RBM Framework

    +
    + +
    +

    Usage

    +
    mapping_result
    +
    + +
    +

    Format

    +

    A data frame with 107 rows and 2 variables:

    result_title
    +

    character result_title

    + +
    sector_rbm
    +

    character sector_rbm

    + + +
    + + +
    + + +
    + + + +
    + + + + + + + diff --git a/docs/reference/mapping_sector.html b/docs/reference/mapping_sector.html new file mode 100644 index 0000000..95081b7 --- /dev/null +++ b/docs/reference/mapping_sector.html @@ -0,0 +1,100 @@ + +mapping_sector — mapping_sector • iati + Skip to contents + + +
    +
    +
    + +
    +

    Mapping Sector to UNHCR 2022 RBM Framework

    +
    + +
    +

    Usage

    +
    mapping_sector
    +
    + +
    +

    Format

    +

    A data frame with 83 rows and 3 variables:

    sector_desc
    +

    character COLUMN_DESCRIPTION

    + +
    sector_vocabulary_name
    +

    character COLUMN_DESCRIPTION

    + +
    sector_rbm
    +

    character COLUMN_DESCRIPTION

    + + +
    + + +
    + + +
    + + + +
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    -

    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.

    @@ -82,6 +86,15 @@

    Arguments +