Browse definitions of previously submitted extract requests

Retrieve definitions of an arbitrary number of previously submitted extract requests for a given IPUMS collection, starting from the most recent extract request.

To check the status of a particular extract request, use get_extract_info().

Learn more about the IPUMS API in vignette("ipums-api").

Usage

get_extract_history(
  collection = NULL,
  how_many = 10,
  delay = 0,
  api_key = Sys.getenv("IPUMS_API_KEY")
)

Arguments

collection

Character string of the IPUMS collection for which to retrieve extract history. Defaults to the current default collection, if it exists. See set_ipums_default_collection().

For a list of codes used to refer to each collection, see ipums_data_collections().

how_many

The number of extract requests for which to retrieve information. Defaults to the 10 most recent extracts.

delay

Number of seconds to delay between successive API requests, if multiple requests are needed to retrieve all records.

A delay is highly unlikely to be necessary and is intended only as a fallback in the event that you cannot retrieve your extract history without exceeding the API rate limit.

api_key

API key associated with your user account. Defaults to the value of the IPUMS_API_KEY environment variable. See set_ipums_api_key().

Value

A list of ipums_extract objects

See also

get_extract_info() to get the current status of a specific extract request.

Examples

if (FALSE) { # \dontrun{
# Get information for most recent extract requests.
# By default gets the most recent 10 extracts
get_extract_history("usa")

# Return only the most recent 3 extract definitions
get_extract_history("cps", how_many = 3)

# To get the most recent extract (for instance, if you have forgotten its
# extract number), use `get_last_extract_info()`
get_last_extract_info("nhgis")
} # }

# To browse your extract history by particular criteria, you can
# loop through the extract objects. We'll create a sample list of 2 extracts:
extract1 <- define_extract_micro(
  collection = "usa",
  description = "2013 ACS",
  samples = "us2013a",
  variables = var_spec(
    "SEX",
    case_selections = "2",
    data_quality_flags = TRUE
  )
)

extract2 <- define_extract_micro(
  collection = "usa",
  description = "2014 ACS",
  samples = "us2014a",
  variables = list(
    var_spec("RACE"),
    var_spec(
      "SEX",
      case_selections = "1",
      data_quality_flags = FALSE
    )
  )
)

extracts <- list(extract1, extract2)

# `purrr::keep()`` is particularly useful for filtering:
purrr::keep(extracts, ~ "RACE" %in% names(.x$variables))
#> [[1]]
#> Unsubmitted IPUMS USA extract 
#> Description: 2014 ACS
#> 
#> Samples: (1 total) us2014a
#> Variables: (2 total) RACE, SEX
#> 

purrr::keep(extracts, ~ grepl("2014 ACS", .x$description))
#> [[1]]
#> Unsubmitted IPUMS USA extract 
#> Description: 2014 ACS
#> 
#> Samples: (1 total) us2014a
#> Variables: (2 total) RACE, SEX
#> 

# You can also filter on variable-specific criteria
purrr::keep(extracts, ~ isTRUE(.x$variables[["SEX"]]$data_quality_flags))
#> [[1]]
#> Unsubmitted IPUMS USA extract 
#> Description: 2013 ACS
#> 
#> Samples: (1 total) us2013a
#> Variables: (1 total) SEX
#> 

# To filter based on all variables in an extract, you'll need to
# create a nested loop. For instance, to find all extracts that have
# any variables with data_quality_flags:
purrr::keep(
  extracts,
  function(extract) {
    any(purrr::map_lgl(
      names(extract$variables),
      function(var) isTRUE(extract$variables[[var]]$data_quality_flags)
    ))
  }
)
#> [[1]]
#> Unsubmitted IPUMS USA extract 
#> Description: 2013 ACS
#> 
#> Samples: (1 total) us2013a
#> Variables: (1 total) SEX
#> 

# To peruse your extract history without filtering, `purrr::map()` is more
# useful
purrr::map(extracts, ~ names(.x$variables))
#> [[1]]
#> [1] "SEX"
#> 
#> [[2]]
#> [1] "RACE" "SEX" 
#> 

purrr::map(extracts, ~ names(.x$samples))
#> [[1]]
#> [1] "us2013a"
#> 
#> [[2]]
#> [1] "us2014a"
#> 

purrr::map(extracts, ~ .x$variables[["RACE"]]$case_selections)
#> [[1]]
#> NULL
#> 
#> [[2]]
#> NULL
#> 

# Once you have identified a past extract, you can easily download or
# resubmit it
if (FALSE) { # \dontrun{
extracts <- get_extract_history("nhgis")

extract <- purrr::keep(
  extracts,
  ~ "CW3" %in% names(.x$time_series_tables)
)

download_extract(extract[[1]])
} # }