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Tidy an SDG Data Frame

Source: R/sdg.R
sdg_clean.Rd

Selects, renames, and type-casts the most useful columns from an SDG observation table returned by sdg_data(), producing a compact tibble in the unified DSIR cleaned-indicator schema — the same schema produced by gho_clean(), so the two outputs can be combined directly with bind_indicators().

Usage

sdg_clean(df)

Arguments

df

A data frame returned by sdg_data().

Value

A tibble with 15 columns: source (always "sdg"), id, indicator, location, iso3, location_name, year, value, value_num, low, high, series, dim1 (NA), dim2 (NA), dim3 (NA). Sorted by location then year. Empty input returns an empty tibble with the same columns and types.

Details

The mapping (SDG source → unified column) is:

  • indicator (list-column, flattened) → id (e.g. "3.4.1")

  • seriesDescription → indicator (human-readable label; NA if the API response does not include it)

  • geoAreaCode → location (UN M49 numeric, as character); also iso3 via m49_to_iso3() for WHO Member States — region / world aggregates and non-Member areas get iso3 = NA

  • location_name is resolved by looking up iso3 against who_countries (so a WHO Member State has the same location_name here and in gho_clean() output), with a fallback to the SDG API's raw geoAreaName for non-Member-State rows (e.g. regional / world aggregates)

  • timePeriodStart → year (integer)

  • value → value (character; raw) and value_num (numeric; NA for non-numeric entries like "<0.1" or aggregate notes)

  • lowerBound, upperBound → low, high (numeric)

  • series → series

Three columns are always present but never populated for SDG output: dim1, dim2, dim3 (GHO-only concepts).

See also

sdg_data(), gho_clean(), bind_indicators(), m49_to_iso3().

Examples

# \donttest{
sdg_data("3.2.1", area = "156", year_from = 2015) |>
  sdg_clean()
#> Fetching:
#> <https://unstats.un.org/sdgs/UNSDGAPIV5/v1/sdg/Indicator/Data?indicator=3.2.1&pageSize=1000&areaCode=156&page=1>
#> # A tibble: 120 × 15
#>    source id    indicator     location iso3  location_name  year value value_num
#>    <chr>  <chr> <chr>         <chr>    <chr> <chr>         <int> <chr>     <dbl>
#>  1 sdg    3.2.1 Infant death… 156      CHN   China          2015 64505  64505   
#>  2 sdg    3.2.1 Infant death… 156      CHN   China          2015 84118  84118   
#>  3 sdg    3.2.1 Infant death… 156      CHN   China          2015 1486… 148623   
#>  4 sdg    3.2.1 Under-five m… 156      CHN   China          2015 10.0…     10.1 
#>  5 sdg    3.2.1 Under-five m… 156      CHN   China          2015 11.3…     11.3 
#>  6 sdg    3.2.1 Under-five m… 156      CHN   China          2015 10.7…     10.7 
#>  7 sdg    3.2.1 Infant morta… 156      CHN   China          2015 7.68…      7.69
#>  8 sdg    3.2.1 Infant morta… 156      CHN   China          2015 8.69…      8.70
#>  9 sdg    3.2.1 Infant morta… 156      CHN   China          2015 8.20…      8.21
#> 10 sdg    3.2.1 Under-five d… 156      CHN   China          2015 84820  84820   
#> # ℹ 110 more rows
#> # ℹ 6 more variables: low <dbl>, high <dbl>, series <chr>, dim1 <chr>,
#> #   dim2 <chr>, dim3 <chr>
# }