Skip to contents

Download spatial data of Census Weighting Areas (area de ponderacao) of the Brazilian Population Census

Source: R/read_weighting_area.R
read_weighting_area.Rd

Only 2010 data is currently available.

Usage

read_weighting_area(
  code_weighting = "all",
  year = 2010,
  simplified = TRUE,
  showProgress = TRUE,
  cache = TRUE
)

Arguments

code_weighting

The 7-digit code of a Municipality. If the two-digit code or a two-letter uppercase abbreviation of a state is passed, (e.g. 33 or "RJ") the function will load all weighting areas of that state. If code_weighting="all", all weighting areas of the country are loaded.

year

Numeric. Year of the data. Defaults to 2010.

simplified

Logic FALSE or TRUE, indicating whether the function should return the data set with 'original' spatial resolution or a data set with 'simplified' geometry. Defaults to TRUE. For spatial analysis and statistics users should set simplified = FALSE. Borders have been simplified by removing vertices of borders using st_simplify{sf} preserving topology with a dTolerance of 100.

showProgress

Logical. Defaults to TRUE display progress bar.

cache

Logical. Whether the function should read the data cached locally, which is faster. Defaults to cache = TRUE. By default, geobr stores data files in a temporary directory that exists only within each R session. If cache = FALSE, the function will download the data again and overwrite the local file.

Value

An "sf" "data.frame" object

See also

Other area functions: read_amazon(), read_biomes(), read_capitals(), read_comparable_areas(), read_country(), read_disaster_risk_area(), read_health_facilities(), read_health_region(), read_immediate_region(), read_indigenous_land(), read_intermediate_region(), read_meso_region(), read_metro_area(), read_micro_region(), read_municipal_seat(), read_municipality(), read_neighborhood(), read_pop_arrangements(), read_region(), read_schools(), read_semiarid(), read_state(), read_statistical_grid(), read_urban_area(), read_urban_concentrations()

Examples

# Read specific weighting area at a given year
w <- read_weighting_area(code_weighting=5201108005004, year=2010)
#> Using year/date 2010

# Read all weighting areas of a state at a given year
w <- read_weighting_area(code_weighting=53, year=2010) # or
#> Using year/date 2010
w <- read_weighting_area(code_weighting="DF", year=2010)
#> Using year/date 2010
plot(w)


# Read all weighting areas of a municipality at a given year
w <- read_weighting_area(code_weighting=5201108, year=2010)
#> Using year/date 2010
plot(w)


# Read all weighting areas of the country at a given year
w <- read_weighting_area(code_weighting="all", year=2010)
#> Using year/date 2010
#> Loading data for the whole country. This might take a few minutes.