Brazilian school-enrollment series — get

Returns harmonized school-enrollment counts and rates, optionally broken down by color/race, administrative network, institutional type, or teaching modality. Series are pulled from all enrollment datasets shipped with the package and concatenated into the canonical long-format schema.

Usage

get_enrollment(
  level = NULL,
  network = NULL,
  institution_type = NULL,
  modality = NULL,
  year = NULL,
  geo_level = c("BR", "UF"),
  geo = NULL,
  dimension = c("none", "race"),
  indicator = NULL,
  source = NULL,
  include_derived = FALSE,
  wide = FALSE,
  lang = c("en", "pt")
)

Arguments

level: Character vector with one or more stage codes: "fundamental_anos_iniciais", "fundamental_anos_finais", "fundamental", "medio", "superior". NULL (default) means no filter.
network: Character vector with administrative-network codes ("federal", "estadual", "municipal", "publica", "privada", plus the post-2009 private subcategories "privada_particular", "privada_comunitaria_confessional_filantropica", "privada_lucrativa", "privada_nao_lucrativa", "especial", "total"). NULL (default) means no filter.
institution_type: Character vector restricting the institutional category (only meaningful for level = "superior"). See inst/dict/schema.yaml for the controlled vocabulary. NULL (default) means no filter; pass "total" to keep only rows that aggregate across institutional types.
modality: Character vector: "presencial", "ead", "total". NULL (default) means no filter.
year: Integer vector or two-element c(min, max) range. NULL for all years.
geo_level: One of "BR" (national, default) or "UF" (state).
geo: Character vector of 2-letter UF codes when geo_level = "UF". NULL (default) returns all UFs.
dimension: Inequality breakdown. One of "none" (default, totals only) or "race". Future versions add "sex", "income", "location".
indicator: Character vector. "count" for counts, "rate" for gross enrollment rates. NULL returns both.
source: Character vector of source keys (see inst/dict/vocabularies/sources.yaml). NULL returns all available sources. Tip: when the same (year, level, network) is covered by multiple sources (common in the tertiary panel), pass source = "..." to lock down a single series.
include_derived: Logical. If FALSE (default), excludes the so-called reconstructed totals — rows where the value was computed by combining components from different sources (typically the in-person enrollment from a single-source paper plus the EAD enrollment from INEP, for 2000-2008 where the original sources under-reported the combined total). Set to TRUE to include them. The composition is documented in source_note; the source column for these rows carries the composite key "<presencial_source>+<ead_source>". Has no effect on datasets that do not carry an is_derived flag.
wide: Logical. If TRUE, pivots the indicator column to wide form (one column per indicator). Default FALSE.
lang: One of "en" (default) or "pt". When "pt", factor levels are translated using inst/dict/i18n.yaml.

Value

A tibble following the canonical schema in inst/dict/schema.yaml. Optional columns (institution_type, modality, is_derived) are present whenever any of the loaded datasets carries them; for rows coming from datasets without that column the value defaults to "total" (or FALSE for is_derived).

Examples

# National series, ensino fundamental, all years
get_enrollment(level = "fundamental", geo_level = "BR")
#> # A tibble: 156 × 16
#>     year geo_level geo_code geo_name level     network institution_type modality
#>    <int> <chr>     <chr>    <chr>    <chr>     <chr>   <chr>            <chr>   
#>  1  1933 BR        BR       Brasil   fundamen… total   total            total   
#>  2  1934 BR        BR       Brasil   fundamen… total   total            total   
#>  3  1935 BR        BR       Brasil   fundamen… total   total            total   
#>  4  1936 BR        BR       Brasil   fundamen… total   total            total   
#>  5  1937 BR        BR       Brasil   fundamen… total   total            total   
#>  6  1938 BR        BR       Brasil   fundamen… total   total            total   
#>  7  1939 BR        BR       Brasil   fundamen… total   total            total   
#>  8  1940 BR        BR       Brasil   fundamen… total   total            total   
#>  9  1941 BR        BR       Brasil   fundamen… total   total            total   
#> 10  1942 BR        BR       Brasil   fundamen… total   total            total   
#> # ℹ 146 more rows
#> # ℹ 8 more variables: dim_race <chr>, age_group <chr>, indicator <chr>,
#> #   value <dbl>, unit <chr>, source <chr>, source_note <chr>, is_derived <lgl>

# Tertiary enrollment, all sources, compare them
get_enrollment(level = "superior", network = "total", modality = "total")
#> # A tibble: 370 × 16
#>     year geo_level geo_code geo_name level    network institution_type modality
#>    <int> <chr>     <chr>    <chr>    <chr>    <chr>   <chr>            <chr>   
#>  1  1940 BR        BR       Brasil   superior total   total            total   
#>  2  1941 BR        BR       Brasil   superior total   total            total   
#>  3  1942 BR        BR       Brasil   superior total   total            total   
#>  4  1943 BR        BR       Brasil   superior total   total            total   
#>  5  1944 BR        BR       Brasil   superior total   total            total   
#>  6  1945 BR        BR       Brasil   superior total   total            total   
#>  7  1946 BR        BR       Brasil   superior total   total            total   
#>  8  1947 BR        BR       Brasil   superior total   total            total   
#>  9  1948 BR        BR       Brasil   superior total   total            total   
#> 10  1949 BR        BR       Brasil   superior total   total            total   
#> # ℹ 360 more rows
#> # ℹ 8 more variables: dim_race <chr>, age_group <chr>, indicator <chr>,
#> #   value <dbl>, unit <chr>, source <chr>, source_note <chr>, is_derived <lgl>

# Tertiary private particular only, post-2000
get_enrollment(level = "superior", network = "privada_particular",
               year = c(2000, 2024))
#> # A tibble: 50 × 16
#>     year geo_level geo_code geo_name level    network  institution_type modality
#>    <int> <chr>     <chr>    <chr>    <chr>    <chr>    <chr>            <chr>   
#>  1  2000 BR        BR       Brasil   superior privada… faculty_school_… presenc…
#>  2  2000 BR        BR       Brasil   superior privada… integrated_facu… presenc…
#>  3  2000 BR        BR       Brasil   superior privada… total            presenc…
#>  4  2000 BR        BR       Brasil   superior privada… university       presenc…
#>  5  2000 BR        BR       Brasil   superior privada… university_cent… presenc…
#>  6  2001 BR        BR       Brasil   superior privada… faculty_school_… presenc…
#>  7  2001 BR        BR       Brasil   superior privada… integrated_facu… presenc…
#>  8  2001 BR        BR       Brasil   superior privada… technology_cent… presenc…
#>  9  2001 BR        BR       Brasil   superior privada… total            presenc…
#> 10  2001 BR        BR       Brasil   superior privada… total            presenc…
#> # ℹ 40 more rows
#> # ℹ 8 more variables: dim_race <chr>, age_group <chr>, indicator <chr>,
#> #   value <dbl>, unit <chr>, source <chr>, source_note <chr>, is_derived <lgl>

# Compare with derived rows included
get_enrollment(level = "superior", network = "total",
               year = c(2000, 2008), include_derived = TRUE)
#> # A tibble: 113 × 16
#>     year geo_level geo_code geo_name level    network institution_type modality
#>    <int> <chr>     <chr>    <chr>    <chr>    <chr>   <chr>            <chr>   
#>  1  2000 BR        BR       Brasil   superior total   total            total   
#>  2  2001 BR        BR       Brasil   superior total   total            total   
#>  3  2002 BR        BR       Brasil   superior total   total            total   
#>  4  2003 BR        BR       Brasil   superior total   total            total   
#>  5  2004 BR        BR       Brasil   superior total   total            total   
#>  6  2005 BR        BR       Brasil   superior total   total            total   
#>  7  2006 BR        BR       Brasil   superior total   total            total   
#>  8  2007 BR        BR       Brasil   superior total   total            total   
#>  9  2008 BR        BR       Brasil   superior total   total            total   
#> 10  2000 BR        BR       Brasil   superior total   total            total   
#> # ℹ 103 more rows
#> # ℹ 8 more variables: dim_race <chr>, age_group <chr>, indicator <chr>,
#> #   value <dbl>, unit <chr>, source <chr>, source_note <chr>, is_derived <lgl>