Package: ibger 0.2.1

André Leite

ibger: Access the 'IBGE' Aggregate Data API from 'R'

'Tidyverse'-friendly interface to the Brazilian Institute of Geography and Statistics ('IBGE') aggregate data 'API' <https://servicodados.ibge.gov.br/api/docs/agregados?versao=3>. Query aggregates, variables, localities, periods, and metadata from surveys and censuses conducted by 'IBGE'.

Authors:André Leite [aut, cre], Marcos Wasiliew [aut], Hugo Vasconcelos [aut], Carlos Amorim [aut], Diogo Bezerra [aut], Allan Quadros [rev], Diana García-Cortés [rev]

ibger_0.2.1.tar.gz
ibger_0.2.1.zip(r-4.7-any)ibger_0.2.1.zip(r-4.6-any)ibger_0.2.1.zip(r-4.5-any)
ibger_0.2.1.tgz(r-4.6-any)ibger_0.2.1.tgz(r-4.5-any)
ibger_0.2.1.tar.gz(r-4.7-any)ibger_0.2.1.tar.gz(r-4.6-any)
ibger_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ibger/json (API)

# Install 'ibger' in R:
install.packages('ibger', repos = c('https://packages.ropensci.org', 'https://cloud.r-project.org'))

Reviews:rOpenSci Software Review #787

Bug tracker:https://github.com/ropensci/ibger/issues

Pkgdown/docs site:https://docs.ropensci.org

On CRAN:

Conda:

6.11 score 5 stars 259 downloads 14 exports 21 dependencies

Last updated from:b6c58f1324 (on main). Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK122
pkgdown docsOK211
source / vignettesOK238
linux-releaseOK141
macos-releaseOK110
macos-oldrelOK109
windows-develOK146
windows-releaseOK130
windows-oldrelOK112
wasm-releaseOK112

Exports:fetch_sidra_urlibge_aggregatesibge_clear_cacheibge_exploreribge_localitiesibge_metadataibge_periodsibge_subjectsibge_survey_metadataibge_survey_periodsibge_surveysibge_variablesparse_ibge_valueparse_sidra_url

Dependencies:askpassclicurldplyrgenericsgluehttr2lifecyclemagrittropensslpillarpkgconfigpurrrR6rlangsystibbletidyselectutf8vctrswithr

Getting started with ibger
Overview | Installation | A typical workflow | Step 1 — Find an aggregate | Step 2 — Inspect the metadata | Step 3 — Retrieve data | Specifying localities | Specifying periods | Filtering with classifications | Automatic validation | Large queries | Browsing the survey catalog | Special values
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-10-13
Started: 2026-02-11

Real-world example: IPCA inflation
Introduction | Step 1 — Explore the aggregate | Step 2 — Monthly IPCA for Brazil | Plot the monthly variation | Step 3 — Compare accumulation measures | Step 4 — Breakdown by product group | Step 5 — Metropolitan area comparison | Step 6 — Building a complete dataset | Large queries | Handling special values
Rendered fromipca-example.Rmdusingknitr::rmarkdown

Last update: 2026-09-22
Started: 2026-02-11

Understanding the IBGE Aggregate Data API
Introduction | Core concepts | Aggregates | Variables | Classifications and categories | Geographic levels and localities | Periods and periodicities | Request limits | View modes | How ibger maps to the API | Further reading
Rendered fromapi-concepts.Rmdusingknitr::rmarkdown

Last update: 2026-09-22
Started: 2026-02-11

Tracking state GDP components with IBGE data
Overview | Setup | Helper: convert period codes to dates | 1) IPCA (7060) — Health insurance | 1.1 Discovering the right IDs | 1.2 Fetching the data | 1.3 Wide format for inspection | 1.4 Plot | 2) IPCA (7060) — Vehicle insurance | 3) PMS (8693) — Transportation and postal services | 4) PNAD Contínua (5434) — Accommodation and food services | 5) PMS (8693) — Professional and administrative services | 6) PNAD Contínua (5434) — Domestic services | 7) PIM-PF (8888) — Industrial production (selected CNAE sectors) | 8) Construction (8886) — Typical construction inputs | 9) PMC (8884 / 8757 / 8880) — Retail trade indices | 9.1 Vehicles, motorcycles, parts and accessories (8884) | 9.2 Construction materials (8757) | 9.3 Retail trade (8880) | Next steps
Rendered fromtutorial.Rmdusingknitr::rmarkdown

Last update: 2026-08-01
Started: 2026-02-11