recycle_data | R Documentation |
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.
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
)
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
|
trim_years |
logical to indicate if years before |
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. |
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")
Functions to recycle the data
remove_recycled_data()
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