Download spatial data of IBGE's statistical grid — read_statistical

Official gridded population estimate of Brazil.

Usage

read_statistical_grid(
  year,
  code_muni,
  output = "sf",
  showProgress = TRUE,
  cache = TRUE,
  verbose = TRUE
)

Arguments

year: Numeric. Year of the data in YYYY format. It defaults to NULL and reads the data from the latest year available.
code_muni: The 7-digit code of a municipality. If code_muni = "all" (Default), the function downloads all the data available in the country. Alternatively, if a two-digit state code or a two-letter uppercase abbreviation of a state is passed (e.g. 33 or "RJ"), all data of that state are downloaded. Municipality codes can be consulted with the geobr::lookup_muni() function.
output: String. Type of object returned by the function. Defaults to "sf", which loads the data into memory as an sf object. Alternatively, "duckdb" returns a lazy spatial table backed by DuckDB via the duckspatial package, and "arrow" returns an Arrow dataset. Both "duckdb" and "arrow" support out-of-memory processing of large data sets.
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.
verbose: A logical. If TRUE (the default), the function prints informative messages and shows download progress bar. If FALSE, the function is silent.

Value

An "sf" "data.frame" OR an ArrowObject

Examples


# Read the grid covering a given state at a given year
grid_rio <- read_statistical_grid(
  year = 2022,
  code_muni = "RJ"
  )
#> ℹ Using year/date 2022

# Read the grid covering a given municipality at a given year
grid_ssalvador <- read_statistical_grid(
  year = 2022,
  code_muni = 2927408
  )
#> ℹ Using year/date 2022