Put hpop_tobacco on SDG trajectory by running a custom version of
scenario_percent_baseline. The custom scenario_percent_baseline is
taking similar parameters to scenario_percent_baseline's
percent_change = -30, baseline_year = 2010, but values are added to the
start_year value, rather than the baseline_year values.
Usage
sdg_hpop_tobacco(
df,
ind_ids = billion_ind_codes("hpop"),
scenario_col = "scenario",
start_year = 2018,
end_year = 2025,
start_year_trim = start_year,
end_year_trim = end_year,
default_scenario = "default",
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.
- start_year
Base year for contribution calculation, defaults to 2018.
- end_year
End year(s) for contribution calculation, defaults to 2019 to 2025.
- start_year_trim
(integer) year to start trimming from.
- end_year_trim
(integer) year to end trimming.
- default_scenario
name of the default scenario.
- value_col
Column name of column with indicator values.
- ...
additional parameters to be passed to scenario function
See also
HPOP SDG scenarios
sdg_adult_obese(),
sdg_alcohol(),
sdg_child_obese(),
sdg_child_viol(),
sdg_devontrack(),
sdg_fuel(),
sdg_hpop_sanitation_rural(),
sdg_hpop_sanitation_urban(),
sdg_hpop_sanitation(),
sdg_ipv(),
sdg_overweight(),
sdg_pm25(),
sdg_road(),
sdg_stunting(),
sdg_suicide(),
sdg_transfats(),
sdg_wasting(),
sdg_water_rural(),
sdg_water_urban(),
sdg_water()