trim_values: Trim values
In gpw13/billionaiRe: Calculate the WHO Triple Billions

trim_values

R Documentation

Trim values

Description

Trim values

Usage

trim_values(
  df,
  col,
  value_col = "value",
  baseline_col = value_col,
  trim = TRUE,
  small_is_best = FALSE,
  keep_better_values = FALSE,
  upper_limit = 100,
  lower_limit = 0,
  trim_years = TRUE,
  start_year_trim = 2018,
  end_year_trim = 2025
)

Arguments

`df`	Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
`col`	column to trim values from. Will be removed before returning the data frame.
`value_col`	Column name of column with indicator values. This column will be used to return the results.
`baseline_col`	Column name with baseline values. This is used to ensure that trimmed values do not get worst values than baseline.
`trim`	logical to indicate if the data should be trimmed between `upper_limit` and `lower_limit`.
`small_is_best`	Logical to identify if a lower value is better than a higher one (e.g. lower obesity in a positive public health outcome, so obesity rate should have small_is_best = TRUE).
`keep_better_values`	logical to indicate if "better" values should be kept from `value_col` if they are present. Follows the direction set in `small_is_best`. For instance, if small_is_best is TRUE, then `value_col` lower than `col` will be kept.
`upper_limit`	upper limit at which the indicator should be caped.
`lower_limit`	lower_limit limit at which the indicator should be caped.
`trim_years`	logical to indicate if years before `start_year_trim` and after `end_year_trim` should be removed
`start_year_trim`	(integer) year to start trimming from.
`end_year_trim`	(integer) year to end trimming.

Value

trimed data frame, removing the col column, and putting the trimmed values in value_col

General scenario functions add_scenario(), calculate_aarc(), calculate_aroc(), exec_scenario(), fill_cols_scenario(), flat_extrapolation(), get_aarr(), get_baseline_value(), get_baseline_year(), get_last_value(), get_last_year_scenario(), get_latest_aarc(), get_percent_change_aarc(), get_target_aarc(), remove_unwanted_scenarios(), trim_years()