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| # WARNING - Generated by {fusen} from dev/utilities.Rmd: do not edit by hand | ||
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| #' @title Write simple compass indicator table | ||
| #' @description The function take the list of calculated variables from an RMS | ||
| #' and output an excel document in the same folder with the correct | ||
| #' format for import into COMPASS. | ||
| #' | ||
| #' The function assumes you have already calculated the indicators and | ||
| #' have a datalist object with all the correct calculation inside | ||
| #' | ||
| #' @param country iso3 code for the country (easier to recall than the M49 used in the API) | ||
| #' @param operation operation name | ||
| #' @param year year to use to extract the baseline from Population Statistics | ||
| #' @param population_type The list of population type for baseline calculation | ||
| #' @param population_rms The list of population type covered by RMS | ||
| #' @param rms_indicator list with indicators and their related frame to pull the value | ||
| #' @param ridl name of ridl data container to push the data to | ||
| #' @param publish yes / no | ||
| #' | ||
| #' @importFrom unhcrdatapackage end_year_population_totals_long | ||
| #' @importFrom janitor clean_names | ||
| #' | ||
| #' @return frame with all compass indicators | ||
| #' | ||
| #' @export | ||
| #' | ||
| #' @examples | ||
| #' # compass <- export_compass_fill( country = "ECU", | ||
| #' # operation = "Ecuador ABC", | ||
| #' # year = 2022, | ||
| #' # population_type = c("REF","ASY", "OIP"), | ||
| #' # population_rms = "Refugees and Asylum-seekers", | ||
| #' # rms_indicator = rbind( | ||
| #' # c("main", "impact2_2", "2.2 Proportion of PoCs residing in physically safe and | ||
| #' # secure settlements with access to basic facilities"), | ||
| #' # c("main", "impact2_3", "2.3 Proportion of PoC with access to health services"), | ||
| #' # c("P2.S3", "impact3_2a", "3.2a Proportion of PoC enrolled in primary education" ), | ||
| #' # c("P2.S3", "impact3_2b", "3.2b Proportion of PoC enrolled in secondary education" ), | ||
| #' # c("main", "impact3_3", "3.3 Proportion of PoC feeling safe walking alone in their neighborhood (related SDG 16.1.4)." ), | ||
| #' # c("S2", "outcome1_2", "1.2 Proportion of children under 5 years of age whose births | ||
| #' # have been registered with a civil authority. [SDG 16.9.1 - Tier 1]" ), | ||
| #' # c("S2", "outcome1_3", "1.3 Proportion of PoC with legally recognized identity documents or credentials [GCR 4.2.2]." ), | ||
| #' # c("main", "outcome4_1", "4.1 Proportion of PoC who know where to access available GBV services." ), | ||
| #' # c("main", "outcome4_2", "4.2 Proportion of POCs who do not accept violence against women." ), | ||
| #' # c("main", "outcome8_2", "8.2 Proportion of PoC with primary reliance on clean (cooking) fuels and technology [SDG 7.1.2 Tier 1]" ), | ||
| #' # c("main", "outcome9_1", "9.1 Proportion of PoCs living in habitable and affordable housing." ), | ||
| #' # c("main", "outcome9_2", "9.2 Proportion of PoC that have energy to ensure lighting (close to Sphere)." ), | ||
| #' # c("main","outcome12_1", "12.1 Proportion of PoC using at least basic drinking water services (SDG)." ), | ||
| #' # # c("main" , "outcome12_2", "12.2 Proportion of PoC with access to a safe household toilet (SDG)." ), | ||
| #' # c("main", "outcome13_1", "13.1. Proportion of PoC with an account at a bank or other | ||
| #' # financial institution or with a mobile-money-service provider [SDG 8.10.2 Tier 1]." ), | ||
| #' # c("main", "outcome13_2", "13.2. Proportion of PoC who self-report positive changes in their income compared to previous year." ), | ||
| #' # c("main", "outcome13_3", "13.3 Proportion of PoC (working age) who are unemployed." ), | ||
| #' # c("main", "outcome16_1", "16.1. Proportion of PoC with secure tenure rights and/or | ||
| #' # property rights to housing and/or land [revised SDG indicator 1.4.2]." )#, | ||
| #' # # c("main", "outcome16_2", "16.2. Proportion of PoC covered by social protection floors/systems [SDG 1.3.1]." ) | ||
| #' # ), | ||
| #' # ridl = params$ridl, | ||
| #' # publish = params$publish ) | ||
| compass_table <- function(country , | ||
| operation, | ||
| year , | ||
| population_type, | ||
| population_rms, | ||
| rms_indicator, | ||
| ridl, | ||
| publish) { | ||
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| totalBaseline <- unhcrdatapackage::end_year_population_totals_long |> | ||
| filter(CountryAsylumCode == country, | ||
| Year == 2022 , | ||
| Population.type %in% population_type) |> | ||
| group_by(CountryAsylumName) |> | ||
| summarise(Value = sum(Value, na.rm = TRUE)) |> | ||
| ungroup() |> | ||
| dplyr::pull( Value) | ||
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| rms_indicator = as.data.frame(rms_indicator) | ||
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| ## Initialise the data frame | ||
| compass <- data.frame( t(c( a = operation, | ||
| b = population_rms, | ||
| c = "Percent", | ||
| d = totalBaseline, | ||
| e = 10, | ||
| f = 10, | ||
| g = "XXX" )) ) | ||
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| ## append all the values | ||
| for (i in (1:nrow(rms_indicator))) { | ||
| # i <- 3 | ||
| t <- as.data.frame(eval(parse(text= paste0("table( datalist[[\"", | ||
| rms_indicator[i,1] , | ||
| "\"]]$", | ||
| rms_indicator[i, 2] ,")" ) ))) | ||
| #cat( paste0(rms_indicator[i,3] , "\n")) | ||
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| #class(t) | ||
| if( nrow(t) == 0) { | ||
| t1 <- 0 } else if( nrow(t |> dplyr::filter(Var1 ==1 )) == 1) { | ||
| t1 <- eval(parse(text= paste0("as.data.frame( prop.table(table( datalist[[\"", | ||
| rms_indicator[i,1],"\"]]$", | ||
| rms_indicator[i,2],"))) |> | ||
| dplyr::filter(Var1 ==1 ) |> dplyr::pull(Freq)"))) } else { | ||
| t1 <- 0} | ||
| compass1 <- as.data.frame(t(c( a = operation, | ||
| b = population_rms, | ||
| c = "Percent", | ||
| d = totalBaseline, | ||
| e = round(t1 * 100,2), | ||
| f = round(totalBaseline *t1), | ||
| g = rms_indicator[i,3] ))) | ||
| #str(compass) | ||
| #str(compass1) | ||
| compass <- rbind( compass,compass1) | ||
| rm(compass1) | ||
| } | ||
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| compass <- compass |> | ||
| as.data.frame() |> | ||
| dplyr::slice(-1) |> | ||
| dplyr::mutate (Plan = a , | ||
| `Population Type (operational)` = b , | ||
| `Show As` = c, | ||
| `Baseline Num.` = f, | ||
| `Baseline Den.` = d, | ||
| `%` = e , | ||
| `Indicator` = g)|> | ||
| dplyr::select(Plan, | ||
| `Indicator`, | ||
| `Population Type (operational)`, | ||
| `Show As`, | ||
| `Baseline Num.`, | ||
| `Baseline Den.`, | ||
| `%` ) | ||
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| ## And now saving | ||
| ## Create a new workbook | ||
| wb <- openxlsx::createWorkbook() | ||
| ## add the cleaning log to the file | ||
| openxlsx::addWorksheet(wb, "Compass") | ||
| openxlsx::writeData(wb, "Compass", | ||
| compass, withFilter = TRUE) | ||
| ## Save workbook | ||
| openxlsx::saveWorkbook(wb, | ||
| file = here::here(paste0("compass_", | ||
| country,"_", | ||
| stringr::str_replace_all(string=population_rms, pattern=" ", repl=""), | ||
| ".xlsx") ), | ||
| overwrite = TRUE) | ||
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| ## Now push to RILD | ||
| if( publish == "yes"){ | ||
| p <- riddle::dataset_show(param$ridl) | ||
| list_of_resources <- p[["resources"]][[1]] | ||
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| time <- format(Sys.Date(), '%d%b%y') | ||
| ### Publish the analysis plan #### | ||
| namecompass = paste0("compass_", country,"_", | ||
| stringr::str_replace_all(string=population_rms, pattern=" ", repl="")) | ||
| ### Check if the name is already in the resources | ||
| if(namecompass %in% list_of_resources$name) { | ||
| ## get the resource id | ||
| resourceid <- list_of_resources |> | ||
| dplyr::filter ( name == namecompass) |> | ||
| dplyr::pull(id) | ||
| ## get the new resource version | ||
| curversion <- list_of_resources |> | ||
| dplyr::filter ( name == namecompass) |> | ||
| dplyr::pull(version) | ||
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| ## Build resource metadata | ||
| metadatacompass <- riddle::resource_metadata( | ||
| type = "attachment", | ||
| url = paste0(namecompass, ".xlsx"), | ||
| name = namecompass, | ||
| description = paste0("Compass output generated from RMS on ", time, | ||
| ". Built using kobocruncher "), | ||
| format = "xlsx", | ||
| version = (curversion + 1), | ||
| visibility = "public", | ||
| file_type = "other", | ||
| ## Revise here based on the name from your crunching report | ||
| upload = httr::upload_file(here::here(paste0(namecompass, ".xlsx"))) | ||
| ) | ||
| riddle::resource_update(id = resourceid, | ||
| res_metadata = metadatacompass) | ||
| } else { | ||
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| metadatacompass <- riddle::resource_metadata( | ||
| type = "attachment", | ||
| url = paste0(namecompass, ".xlsx"), | ||
| name = namecompass, | ||
| description = paste0("Compass output generated from RMS on ", time, | ||
| ". Built using kobocruncher "), | ||
| format = "xlsx", | ||
| visibility = "public", | ||
| file_type = "other", | ||
| ## Revise here based on the name from your crunching report | ||
| upload = httr::upload_file(here::here(paste0(namecompass, ".xlsx"))) | ||
| ) | ||
| riddle::resource_create(package_id = p$id, | ||
| res_metadata = metadatacompass) | ||
| } | ||
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| } | ||
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| return(compass) | ||
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| } |
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