README.md

In bacenR: Access Data from Brazilian Central Bank: IFdata, Active Institutions, Balance Sheets and Normative Acts

bacenR

The goal of bacenR is to provide R functions to download and work with data from the Brazilian Central Bank (Bacen).

• The datasets available through bacenR include:
• Normative legislation
• Financial statements of financial institutions
• List of financial institutions regulated by Bacen in activity
• Ifdata resources / IFdata

To get data about IPCA, Selic, GDP, Government Debt, and others, check the packages:

• BacenAPI
• rbcb

Summary

• Install
• Usage
• To-do
• Author
• How to cite
• Support

Install

You can install the stable version of bacenR like so:

install.packages("bacenR")

Or, you can install the development version of bacenR like so:

# install.packages("pak") # if you don't have pak installed yet
pak::pak("rtheodoro/bacenR")

Usage

This is a basic example of use:

# Load the package
library(bacenR)

# Download normative legislation related to Credit Cooperatives
normative_data <- get_normative_data(
    terms = c("Cooperativas de Crédito", "Cooperativa de Crédito"), 
    ini_date = "2020-01-01", 
    end_date = Sys.Date()
)

# Download texts of the normative legislation
normative_txt <- get_normative_txt(normative_data)

# Download financial statements of banks and credit cooperatives
get_balance_sheets(
   institution = c("BANCOS", "COOPERATIVAS"),
   months = c(6, 12),
   first_year = 1993,
   final_year = 2023,
   out_dir = "data_raw",
   overwrite = FALSE
)

# Unified treatment of downloaded financial statements
tidy_balance_sheets(
    path_raw = "data_raw", 
    out_dir = "out",
    doc_filter = 4010, 
    save = TRUE
)

# Download list of financial institutions regulated by Bacen
get_institutions(
  institution = c("CONGLOMERADOS", "COOPERATIVAS"),
  years = 2011:2025,
  months = 12,
  out_dir = "data",
  cleanup_zip = TRUE,
  verbose = TRUE
)


# Tidy the institutions data
tidy_institutions(
  path_raw = "data_raw",
  out_dir = "data"
)

# Get data from IFdata Reports
cc_ativa_pj_modalidade_20142024 <- bacenR::get_ifdata_reports(
  year = c(2014:2024),
  month = 12,
  report = 13,
  type_institution = 2
)

# Tidy data from IFdata Reports
tidy_cc_ativa_pj_modalidade_20142024 <- bacenR::tidy_ifdata_reports(
  cc_ativa_pj_modalidade_20142024
)

# Get data from IFdata Registry (Cadastro)
data <- get_ifdata_registry(
  year = c(2023, 2024), 
  month = c(3, 6, 9, 12)
)

To-do

More details about the to-do list can be found in the GitHub project board.

• Functions to collect more datasets from Bacen
  • Institutions authorized, regulated, or supervised
  • Board members
  • Datasets from Bacen.API

Feel free to contribute to this list by opening issues or pull requests on GitHub!

Author

Ricardo Theodoro:

• Economist, Ph.D. candidate and Master's degree holder in Accounting at FEARP/USP.

• Researcher at OBSCOOP/USP

• Contact information:

  • LinkedIn: Ricardo Theodoro

  • Twitter/X: \@rxtheodoro

  • BlueSky: \@rtheodoro

  • Email: rtheodoro\@usp.br

How to cite

To cite bacenR in publications, please use:

citation("bacenR")

@manual{,
  title = "bacenR: Access Data from Brazilian Central Bank - IFdata, Active Institutions, Balance Sheets and Normative Acts",
  author = "Ricardo Theodoro",
  year = "2026",
  version = "v0.4.4",
  doi = "10.32614/CRAN.package.bacenR",
  url = "https://github.com/rtheodoro/bacenR"
}

Support

If this package is useful and saves you time, please consider starring this GitHub repository.

You can also give a penny to charity.

bacenR documentation built on Oct. 24, 2026, 1:07 a.m.