Msna indicators som

.gitignore

@@ -3,5 +3,7 @@
 .RData
 .Ruserdata
 /data/*
-.xlsx*
+*.xlsx
+*.html
 inst/doc
+!/**/.gitkeep

R/load_core_hh_indicators.R

@@ -1,10 +1,11 @@
 #' load_core_hh_indicators
 #'
-#' @param country_code 
+#' @param input_df The fetched data frame using the `fetch_msna` function
+#' @param country_code The country code
 #'
 #' @return named list containing variable column names and labels
 
-load_core_hh_indicators <-  function(country_code="irq"){
+load_core_hh_indicators <-  function(input_df, country_code="irq"){
   if (country_code=="irq"){
     res <- list(
       `Food Consumption Score (numeric)`= "fcs",
@@ -23,6 +24,42 @@ load_core_hh_indicators <-  function(country_code="irq"){
 
   }
   if(country_code=="som"){
+    res <- list(
+      `Respondent Gender` = "respondent_gender",
+      `Respondent Age` = "respondent_age",
+      `Region` = "region",
+      `District` = "district",
+      `Reside in an IDP settlement` = "idp_settlement",
+      `Village/settlement/IDP site` = "settlements",
+      `Household Size` = "hh_size",
+      `Household's total cash income from all income sources` = "total_house_income",
+      `If yes, what is yoour household's current total amount of debt in USD` = "total_hh_debt",
+      `Drinking` = "drinking_water",
+      `Cooking` = "cooking_water",
+      `Personal hygiene (washing or bathing)` = "hygiene_water",
+      `Other domestic purposes (cleaning house, floor, etc.)` = "domestice_water",
+      `FSL shocks Unusually high food prices` = "hh_fsl_shocks/high_food_prices",
+      `FSL shocks Drought/irregular rains, prolonged dry spell` = "hh_fsl_shocks/drought",
+      `FSL shocks Unusually high level of crop pests and disease` = "hh_fsl_shocks/crop_disease",
+      `FSL shocks Disease outbreak in the settlement` = "hh_fsl_shocks/disease_outbreak",
+      `FSL shocks Too much rain, flooding` = "hh_fsl_shocks/flooding",
+      `FSL shocks Livestock disease outbreak` = "hh_fsl_shocks/livestock_disease",
+      `No food to eat of any kind in your house because of lack of resources to get food` = "hh_no_food",
+      `How often did this happen in the past [4 weeks/30 days]` = "hh_no_food_freq",
+      `Go to sleep at night hungry because there was not enough food` = "hh_hunger",
+      `How often did this happen in the past [4 weeks/30 days]` = "hh_hunger_freq",
+      `Go a whole day and night without eating anything at all because there was not enough food` = "fs_not_enough_food",
+      `Livestock decrease Disease outbreak` = "reason_livestock_decrease/disease_outbreak",
+      `Livestock decrease Flooding` = "reason_livestock_decrease/flooding_flooding",
+      `Livestock decrease Drought` = "reason_livestock_decrease/drought_drought",
+      `Recent displacement Flooding (riverine and flash flood)` = "factors_recent_displacement/flooding",
+      `Recent displacement Drought (lack of food, water, livestock loss)` = "factors_recent_displacement/drought",
+      `Recent displacement Desert locust invasion` = "factors_recent_displacement/desert_locust",
+      `Have access to your current shelter in the next 6 months` = "shelter_access",
+      `Latitude` = "Lat",
+      `Longitude` = "Lon",
+      `uuid` = "uuid"
+    )
   }
   if(country_code=="nga"){
     res <- list(
@@ -31,7 +68,13 @@ load_core_hh_indicators <-  function(country_code="irq"){
     )
 
   }
-  return(res)
+
+  # select the given columns on the fetched msna dataset
+  df_msna_cols <- input_df |>
+    select(any_of(purrr::map_chr(res, ~.x)), starts_with("rs_")) |>
+    mutate(country_code = country_code)
+
+  return(df_msna_cols)
 }
 
 

README.Rmd

@@ -37,7 +37,7 @@ You will need to decide on the variables in the HH data set that should be analy
 
 ```{r, eval =F}
 
-load_core_hh_indicators <-  function(country_code="irq"){
+load_core_hh_indicators <-  function(input_df, country_code="irq"){
   if (country_code=="irq"){
     res <- list(
       # labels on left - column names on right
@@ -64,7 +64,13 @@ load_core_hh_indicators <-  function(country_code="irq"){
     )
 
   }
-  return(res)
+
+  # select the given columns on the fetched msna dataset
+  df_msna_cols <- input_df |>
+    select(any_of(purrr::map_chr(res, ~.x))) |>
+    mutate(country_code = country_code)
+
+  return(df_msna_cols)
 }
 
 

README.md

@@ -38,8 +38,7 @@ provided. If you have the same variables as another country make sure
 you copy there label to use in your list.
 
 ``` r
-
-load_core_hh_indicators <-  function(country_code="irq"){
+load_core_hh_indicators <-  function(input_df, country_code="irq"){
   if (country_code=="irq"){
     res <- list(
       # labels on left - column names on right
@@ -66,6 +65,12 @@ load_core_hh_indicators <-  function(country_code="irq"){
     )
 
   }
-  return(res)
+
+  # select the given columns on the fetched msna dataset
+  df_msna_cols <- input_df |>
+    select(any_of(purrr::map_chr(res, ~.x))) |>
+    mutate(country_code = country_code)
+
+  return(df_msna_cols)
 }
 ```