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Download CNEFE datasets from Brazilian Census (IBGE)

Repository created to help access data from CNEFE, the National Register of Addresses for Statistical Purposes (Cadastro Nacional de Estabelecimentos para Fins Estatísticos) of the 2010 Census, developed by IBGE - Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística). Data provided by IBGE consists of a countrywide georeferenced register of addresses, which classifies addresses by type (residential, non-residential, etc.).

More Info from the official website or Here

Although it is possible to access and download the CNEFE files directly from IBGE's server (here), the large volume of files makes it impractical to deal with this database. This repository presents auxiliary functions that allow you to easily download the IBGE data and process them in a fast way, generating a manipulable database with few lines of code.

Installation in R

devtools::install_github("matheusfsiqueira/cnefe_R")
  library(cnefe_R)

Usage

The package is very simple to use, consisting of three functions:

  • download_CNEFE: downloads selected CNEFE datasets from IBGE server and saves to local directory;
  • process_CNEFE: properly reads text files from CNEFE, tidies data and treats geographical coordinates of addresses. In case of missing data, imputes coordinates from census tract;
  • get_CNEFE: calls previous functions together: downloads, processes and treats CNEFE data, providing a ready-to-use output for your needs/applications.

Downloading CNEFE data

Function download_CNEFE has only 3 arguments.

  • State abbreviation (see note below), or "all" to download data from all states (may take some time);
  • Relative destination path (defaults to working directory);
  • Overwrite files, or otherwise use previously downloaded data if available.
library(cnefeR)

download <- download_CNEFE(state="all",
                          dest_path="",
                          overwrite=FALSE)

Function outputs a string vector of the local paths of zip files downloaded from IBGE server.

Processing CNEFE data

Function process_CNEFE has 3 arguments as well.

  • Relative destination path of downloaded CNEFE files (defaults to working directory);
  • State abbreviation (see note below), or "all" to process data from all downloaded states (may cause high memory usage);
  • Output type, one of "df","sf". Sf option converts addresses to simple features (spatial format).
library(cnefeR)

process <- process_CNEFE(dest_path="",
                         state="all",
                         output_type="df")

If you are processing a single brazilian state, function outputs a data frame or sf object; If you are processing "all", output is a list of data frames or a list of sf objects.

Download and process CNEFE data

Function get_CNEFE combines previous functions, downloading and processing CNEFE data from selected state(s). Arguments are:

  • State abbreviation (see note below), or "all" to process data from all downloaded states (may cause high memory usage);
  • Relative destination path of downloaded CNEFE files (defaults to working directory);
  • Output type, one of "df","sf". Sf option converts addresses to simple features (spatial format).
library(cnefeR)

cnefeData <- get_CNEFE(state="all",
                      dest_path="",
                      output_type="df")

If you are processing a single brazilian state, function outputs a data frame or sf object; If you are processing "all", output is a list of data frames or a list of sf objects.

Brazilian state abbreviations

For brazilian users, this should be trivial. Just as a reminder:

State Abbreviation
Acre AC
Alagoas AL
Amazonas AM
Amapá AP
Bahia BA
Ceará CE
Distrito Federal DF
Espírito Santo ES
Goiás GO
Maranhão MA
Minas Gerais MG
Mato Grosso do Sul MS
Mato Grosso MT
Pará PA
Paraíba PB
Pernambuco PE
Piauí PI
Paraná PR
Rio de Janeiro RJ
Rio Grande do Norte RN
Rondônia RO
Roraima RR
Rio Grande do Sul RS
Santa Catarina SC
Sergipe SE
São Paulo SP
Tocantins TO

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Download and process CNEFE datasets from IBGE using R

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