Tools for collecting municipal-level data from several Brazilian governmental social programs.
Collects data from Public APIs that contains information related to the following programs:
- Bolsa Familia Program OK [CRAN]
- PETI (Child Labour Erradication Program) OK [CRAN]
- Seguro Defeso OK [CRAN]
- FIES (Governmental Student Loans) Soon
- PROUNI (University for Everyone Program) Soon
#You can install the latest version (under development and probably bit unstable, but with more functions) here on GitHub:
install.packages('devtools')
devtools::install_github('kimjoaoun/owdbr')
## or directly from CRAN
install.packages('owdbr')
The package has some simple functions that needs to be understood by the user. Only with the knowledge of these, one can make a good use of it. All these functions were written in a way to support multiple requests at once, in order to facilitate the download of data from multiple municipalities.
The first step in using the package is running the uflist()
function, this function takes no arguments and it returns a tibble with four columns: the first one is the num
(with the numeric identifier of the State); the second one being the State
column, with the full name of the State; The UF
column, which contains the UF code, that is a short name (abbreviation?) for a State; and finally, the region
column, which contains the region of the State.
The function accepts the "region" arguments with the following inputs "Norte", "Sul", "Nordeste", "Centro-Oeste" and "Sudeste", the region argument filter the States by the desired region, for example:
x <- uflist(region = 'Sul')
This input returns a tibble only with the states in the south region.
Then, having the list of the States, one should run the num
of the desired state(s) inside the munlist() function. It's going to request the list of all the municipalities in the desired State and then it will return them in a tibble object. (Why a tibble? Click here.
This list is needed because each municipality has a unique identifier, and this one is needed to request municipal-level data from Government's APIs.
use: help(munlist)
to get the meaning of each column in the tibble returned by the function.
Finally, to request the data, one should run the get(pbf/peti/sd)_mun()
function in those numbers that are in the codigo_municipio_completo
column that was generated by the munlist()
function.
In the above example we are going to collect Bolsa Familia Program data from all municipalities in the state of Rondônia.
library(dplyr)
states <- uflist()
View(states)
In the generated tibble, we can see that the num
of the State of Rondônia is 11, so if we plan to collect data from this State, one should do the following:
munis <- munlist(11)
Then, after a few seconds, the tibble with the list of municipalities in the state of Rondônia is returned and then we import the desired data by running:
data.pbf <- getpbf_mun(munis$codigo_municipio_completo,
AAAA = 2015,
MM = 10,
PAGE = 1
YEARLY = FALSE)
If one desire data for an entire year, one can run:
data.pbf <- getpbf_mun(munis$codigo_municipio_completo,
AAAA= 2015,
YEARLY=TRUE)
Huge thanks to: Pedro Cavalcante and Eduarda Oliveira for helping me out.
To cite package ‘owdbr’ in publications use:
Joao Pedro Oliveira dos Santos (2019). owdbr: Open Welfare Data Brazil. R package version 1.0.0.35. https://CRAN.R-project.org/package=owdbr
A BibTeX entry for LaTeX users is:
@Manual{,
title = {owdbr: Open Welfare Data Brazil},
author = {Joao Pedro {Oliveira dos Santos}},
year = {2019},
note = {R package version 1.0.0.35},
url = {https://CRAN.R-project.org/package=owdbr},
}
In Brazilian ABNT formatting rules:
OLIVEIRA SANTOS, J; Open Welfare Data Brazil: Tools for collecting municipal-level data from several Brazilian governmental social programs. Versão 1.0.1.0. Rio de Janeiro, 20 Jun. 2019. Disponível em: https://github.com/kimjoaoun/owdbr/. Acesso em: *???*.
Please note that the 'owdbr' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.