Convert a tibble (or
data.frame) of extract definitions, such as that
returned by get_recent_extracts_info_tbl(), to a list of
ipums_extract objects. For an overview of ipumsr microdata API
functionality, see vignette("ipums-api", package = "ipumsr").
extract_tbl_to_list(extract_tbl, validate = TRUE)A tibble (or
data.frame) where each row contains the definition of
one extract.
Logical (TRUE or FALSE) value indicating whether to
check that each row of extract_tbl contains a valid and complete extract
definition. Defaults to TRUE.
A list of length equal to the number of rows of extract_tbl.
Other ipums_api:
add_to_extract(),
define_extract_cps(),
define_extract_from_json(),
define_extract_usa(),
download_extract(),
extract_list_to_tbl(),
get_extract_info(),
get_last_extract_info(),
get_recent_extracts_info,
ipums_data_collections(),
is_extract_ready(),
remove_from_extract(),
save_extract_as_json(),
set_ipums_api_key(),
submit_extract(),
wait_for_extract()
if (FALSE) {
# Get tibble of recent extracts
tbl_of_last_10_extracts <- get_recent_extracts_info_tbl("usa")
# Filter down to extracts with "income" in the description
description_mentions_income <- grepl(
"[Ii]ncome",
tbl_of_last_10_extracts$description
)
income_extracts <- tbl_of_last_10_extracts[description_mentions_income, ]
# Convert tibble of extracts to list of extracts
income_extracts <- extract_tbl_to_list(income_extracts)
# Now it's easier to operate on those elements as extract objects:
revised_income_extract <- add_to_extract(
income_extracts[[1]],
samples = "us2018a"
)
submitted_revised_income_extract <- submit_extract(revised_income_extract)
}