Recycle data between scenarios

recycle_data() recycles data between the scenarios present in df to reduce size of tables stored. The function wraps around recycle_data_scenario_single() for all the scenarios present in the scenario_col column.

Usage

recycle_data(
  df,
  billion = c("hep", "hpop", "uhc"),
  value_col = "value",
  start_year = 2018,
  end_year = 2025,
  scenario_col = "scenario",
  default_scenario = "default",
  scenario_reported_estimated = "routine",
  scenario_covid_shock = "covid_shock",
  scenario_reference_infilling = "reference_infilling",
  include_projection = TRUE,
  recycle_campaigns = TRUE,
  ind_ids = NULL,
  trim_years = TRUE,
  start_year_trim = start_year,
  end_year_trim = end_year
)

recycle_data_scenario_single(
  df,
  scenario,
  billion = c("hep", "hpop", "uhc"),
  value_col = "value",
  start_year = 2018,
  end_year = 2025,
  scenario_col = "scenario",
  default_scenario = "default",
  scenario_reported_estimated = "routine",
  scenario_covid_shock = "covid_shock",
  scenario_reference_infilling = "reference_infilling",
  include_projection = TRUE,
  recycle_campaigns = TRUE,
  ind_ids = NULL,
  trim_years = FALSE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  assert_data_calculations = TRUE
)

make_default_scenario(
  df,
  scenario = "default",
  billion = c("all", "hep", "hpop", "uhc"),
  value_col = "value",
  start_year = 2018,
  end_year = 2025,
  scenario_col = "scenario",
  default_scenario = "default",
  scenario_reported_estimated = "routine",
  scenario_covid_shock = "covid_shock",
  scenario_reference_infilling = "reference_infilling",
  include_projection = TRUE,
  recycle_campaigns = TRUE,
  ind_ids = NULL,
  trim_years = FALSE,
  start_year_trim = start_year,
  end_year_trim = end_year,
  assert_data_calculations = TRUE
)

Arguments

df: Data frame in long format, where 1 row corresponds to a specific country, year, and indicator.
billion: name of billion to recycle data for.
value_col: Column name of column with indicator values.
start_year: Base year for contribution calculation, defaults to 2018.
end_year: End year(s) for contribution calculation, defaults to 2019 to 2025.
scenario_col: Column name of column with scenario identifiers.
default_scenario: name of the default scenario.
scenario_reported_estimated: name of the reported/estimated scenario.
scenario_covid_shock: name of the scenario with the COVID-19 shock years.
scenario_reference_infilling: name of the WHO technical programs projections/imputations scenario.
include_projection: Boolean to include or not projections in recycling
recycle_campaigns: Boolean to include or not campaigns in recycling
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().
trim_years: logical to indicate if years before start_year and after end_year should be removed
start_year_trim: (integer) year to start trimming from.
end_year_trim: (integer) year to end trimming.
scenario: name of scenario to recycle for.
assert_data_calculations: Boolean if true then output data frame will be tested to see if it contains the minimal required data to run the calculations.

Details

make_default_scenario() wraps around recycle_data_scenario_single() to create a default scenario based on the parameters passed to the function.

recycle_data_scenario_single() reuses values present in the specified scenarios in default_scenario, scenario_reported_estimated, scenario_covid_shock and scenario_reference_infilling for the specified scenarios.

To do so, it looks at:

values in default_scenario but not in the scenario specified
values in scenario_reported_estimated or scenario_covid_shock but not in the scenario specified or default_scenario.
values in scenario_reference_infilling but not in the scenario specified, scenario_reported_estimated, scenario_covid_shock, or scenario_reference_infilling

For more information see:

vignette("scenarios", package = "billionaiRe")

Usage

Arguments

Details

See also