Accelerate transfats by targeting 100 by 2025.
Usage
accelerate_transfats(
df,
ind_ids = billion_ind_codes("hpop"),
scenario_col = "scenario",
default_scenario = "default",
scenario_name = "acceleration",
start_year = 2018,
start_year_trim = start_year + 1,
end_year = 2025,
value_col = "value",
...
)Arguments
- df
Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
- 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().- scenario_col
Column name of column with scenario identifiers. Useful for calculating contributions on data in long format rather than wide format.
- default_scenario
name of the default scenario.
- scenario_name
name of scenario
- start_year
Year from which the acceleration scenario begins, inclusive.
- start_year_trim
(integer) year to start trimming from.
- end_year
End year(s) for contribution calculation, defaults to 2019 to 2025.
- value_col
Column name of column with indicator values. This column will be used to return the results.
- ...
additional parameters to be passed to scenario function
See also
HPOP acceleration scenarios
accelerate_adult_obese(),
accelerate_alcohol(),
accelerate_child_obese(),
accelerate_child_viol(),
accelerate_devontrack(),
accelerate_fuel(),
accelerate_hpop_sanitation_rural(),
accelerate_hpop_sanitation_urban(),
accelerate_hpop_sanitation(),
accelerate_hpop_tobacco(),
accelerate_ipv(),
accelerate_overweight(),
accelerate_pm25(),
accelerate_road(),
accelerate_stunting(),
accelerate_suicide(),
accelerate_wasting(),
accelerate_water_rural(),
accelerate_water_urban(),
accelerate_water()