add_populations() adds relevant populations to each indicator and country,
so these can be used to calculate indicator-level aggregations of the
billions. The column specified by population will be generated and
filled with relevant populations for that country and indicator. If the column
already exists, only missing values will be replaced by the function.
Usage
add_populations(
df,
population = "population",
pop_year = 2025,
scenario_col = NULL,
transform_value_col = "transform_value",
ind_ids = billion_ind_codes("all", include_calculated = TRUE)
)Arguments
- df
Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
- population
Column name of column to create with population figures.
- pop_year
Year used to pull in HPOP populations, defaults to 2025.
- scenario_col
Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.
- transform_value_col
Column name of column(s) with transformed indicator values, used to calculate contributions.
- ind_ids
Named vector of indicator codes for input indicators to the Billion. Although separate indicator codes can be used than the standard, they must be supplied as a named vector where the names correspond to the output of
billion_ind_codes().
Details
Essentially, the function wraps around add_hep_populations() and
add_hpop_populations() and add the country population to UHC indicators.
As HEP indicators where population is relevant are all generated by billionaiRe,
the transform_value_col is required.
See also
Add populations
add_hep_populations(),
add_hpop_populations(),
pop_links