Write simple compass indicator table — fct_compass

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.
         
         The output can conveniently be upoaded as an indicator ressource in ridl

Usage

fct_compass_table(
  country,
  operation,
  year,
  population_type,
  population_rms,
  rms_indicator,
  ridl,
  publish
)

Arguments

country: iso3 code for the country (easier to recall than the M49 used in the API)
operation: operation name
year: year to use to extract the baseline from Population Statistics
population_type: The list of population type for baseline calculation
population_rms: The list of population type covered by RMS
rms_indicator: list with indicators and their related frame to pull the value
ridl: name of ridl data container to push the data to
publish: yes / no

Value

frame with all compass indicators

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 )