Returns one row per (column, member) for every labelled data dimension
ivt_tidy() emits, in its stored member-ordinal order. This is the level
table collect_ivt() uses to convert dimension columns into factors whose
levels cover all members – including members filtered out of the data –
and it is written next to the cached Parquet by ivt_write_parquet() /
get_statcan_ivt() (as <name>_members.parquet).
Usage
ivt_members(
x,
trim_labels = TRUE,
dim_names = c("slug", "label"),
language = "en"
)Arguments
- x
An
ivtobject fromread_ivt().- trim_labels
Trim the hierarchy-indentation whitespace from
levelthe same wayivt_tidy()does by default (TRUE).- dim_names
How the data-dimension
columnnames are formed, matchingivt_tidy():"slug"(default, the terse structural slug) or"label"(the full dimension name). Must match the tidy output the levels will be joined to.- language
Language for the
columnnames (label mode), matchingivt_tidy():"en"(default) or"fr". The table always carries both the Englishleveland the Frenchlevel_fr, so a single sidecar serves both languages; only the label-derivedcolumnnames followlanguage.
Value
A tibble with columns column (the tidy column name), dimension
(the full English dimension name),
dimension_fr (the French dimension name, NA when none – used by
label_ivt_columns()), member_id (1-based StatCan member id), ordinal
(the codebook
member-ordinal; equals member_id when the file stores no ordinal block),
label (the stored label, untrimmed), level (the label as it appears in
the tidy output), level_fr (the French label, NA when the file carries
none for that column), depth (hierarchy depth implied by the label
indentation), parent_id (the member_id of this member's parent in
that hierarchy – the nearest preceding member at a shallower depth, NA
for top-level members), and description/description_fr (the member's
_Description prose – the indicator definition carried by the facet /
quantity dimension of the older survey tables, e.g. a total fertility rate's
"... the number of children born per 1,000 women ...", which states the
value's units; NA for the many dimensions/tables that carry none).
Details
The geography columns are not levelled. Geography is an identity axis
rather than a category: geo_uid is the language-neutral key you join on, the
member list runs to tens of thousands of entries on the large tables, and its
ordinal is a hierarchy traversal rather than an analytic order. Per-member
geography context – names, identifiers, quality flags, and the label
hierarchy as geo_depth/geo_parent_id – lives in metadata$geographies
instead.
Examples
path <- system.file("extdata", "98100044.ivt", package = "canivt")
ivt <- read_ivt(path)
ivt_members(ivt)
#> # A tibble: 18 × 12
#> column dimension dimension_fr member_id ordinal label level level_fr depth
#> <chr> <chr> <chr> <int> <int> <chr> <chr> <chr> <int>
#> 1 type Type of … Type de log… 1 1 "Tot… Tota… Total -… 0
#> 2 type Type of … Type de log… 2 2 " H… Heal… Établis… 1
#> 3 type Type of … Type de log… 3 3 " … Hosp… Hôpitaux 2
#> 4 type Type of … Type de log… 4 4 " … Nurs… Établis… 2
#> 5 type Type of … Type de log… 5 5 " … Resi… Résiden… 2
#> 6 type Type of … Type de log… 6 6 " … Faci… Établis… 2
#> 7 type Type of … Type de log… 7 7 " … Resi… Établis… 2
#> 8 type Type of … Type de log… 8 8 " C… Corr… Établis… 1
#> 9 type Type of … Type de log… 9 9 " S… Shel… Refuges 1
#> 10 type Type of … Type de log… 10 10 " S… Serv… Logemen… 1
#> 11 type Type of … Type de log… 11 11 " … Lodg… Maisons… 2
#> 12 type Type of … Type de log… 12 12 " … Hote… Hôtels,… 2
#> 13 type Type of … Type de log… 13 13 " … Othe… Autres … 2
#> 14 type Type of … Type de log… 14 14 " R… Reli… Établis… 1
#> 15 type Type of … Type de log… 15 15 " H… Hutt… Colonie… 1
#> 16 type Type of … Type de log… 16 16 " O… Othe… Autres … 1
#> 17 collecti… Collecti… Logements c… 1 1 "Col… Coll… Logemen… 0
#> 18 collecti… Collecti… Logements c… 2 2 "Pop… Popu… Populat… 0
#> # ℹ 3 more variables: parent_id <int>, description <chr>, description_fr <chr>