Process datalibweb data: merge PFW data and clean variables

Usage

process_data(inv, aux_list, recode_spec = NULL, verbose = TRUE, ...)

Arguments

inv: A one-row data.frame or data.table from the completed DLW validation inventory containing survey_id, status == "valid", and data_available == "Yes". Rows missing validation fields or having status != "valid" or data_available != "Yes" are rejected before loading.
aux_list: Named list of auxiliary data frames; expected keys: "pfw", "cpi", "ppp", "pop", "gdp", "pce".
recode_spec: Optional pre-resolved recode spec (as returned by sync_recode_spec()) threaded to pd_dlw_clean()/apply_recode_spec() so the spec is read once upstream rather than once per survey. Default NULL.
verbose: Logical. Print progress messages. Default TRUE.
...: other parameters

Value

Invisibly, a list with element pip_names (character vector of saved clean pip_id names) when cleaning, post-format validation, and saving succeed, or NULL when an error or validation failure is logged and caught.

Examples

if (FALSE) { # \dontrun{
release <- "20250203"
pipfun::setup_working_release(release)

pfw <- pipload::load_aux_data("pfw")

gd  <- pipload::load_aux_data("CHN", 2015)
gd  <- survey_id_to_attr(gd, unique(gd$survey_id))
process_data(gd, pfw)

md   <- pipload::load_aux_data(country = "PRY", 2012)
md  <- survey_id_to_attr(md, unique(md$survey_id))
process_data(md, pfw)
} # }