pixr

Access Brazilian Central Bank PIX Open Data API from R

Overview

pixr provides a tidyverse-style interface to the Brazilian Central Bank (BCB) PIX Open Data API. Retrieve statistics on PIX keys, transactions by municipality, transaction breakdowns, and fraud statistics.

Installation

# install.packages("remotes")
remotes::install_github("StrategicProjects/pixr")

Configuration

Timeout

The default timeout for API requests is 120 seconds. You can change it:

# Using the helper function
pix_timeout(180)  # Set to 3 minutes

# Or via options
options(pixr.timeout = 180)

API Endpoints

Each endpoint has a different parameter name and format:

Endpoint	Parameter	Format	R Function
`ChavesPix`	`Data`	`YYYY-MM-DD`	`get_pix_keys()`
`TransacoesPixPorMunicipio`	`DataBase`	`YYYYMM`	`get_pix_transactions_by_municipality()`
`EstatisticasTransacoesPix`	`Database`	`YYYYMM`	`get_pix_transaction_stats()`
`EstatisticasFraudesPix`	`Database`	`YYYYMM`	`get_pix_fraud_stats()`

Quick Start

library(pixr)

# PIX Keys Stock (uses date in YYYY-MM-DD format)
keys <- get_pix_keys(date = "2025-12-01")

# Transaction Statistics (uses database in YYYYMM format)
stats <- get_pix_transaction_stats(database = "202509")

# Transactions by Municipality
muni <- get_pix_transactions_by_municipality(database = "202512")

# Fraud Statistics (MED)
fraud <- get_pix_fraud_stats(database = "202509")

OData Filter and OrderBy

All functions support OData filter and orderby parameters:

# Filter by state and order by municipality name (descending)
maranhao <- get_pix_transactions_by_municipality(
  database = "202512",
  filter = "Estado eq 'MARANHÃO'",
  orderby = "Municipio desc",
  top = 10
)

# Filter by transaction nature
p2p <- get_pix_transaction_stats(
  database = "202509",
  filter = "NATUREZA eq 'P2P'"
)

# Multiple filters using 'and'
filtered <- get_pix_transaction_stats(
  database = "202509",
  filter = "NATUREZA eq 'P2P' and PAG_REGIAO eq 'NORDESTE'"
)

# Filter PIX keys by type
cpf_keys <- get_pix_keys(
  date = "2025-12-01",
  filter = "TipoChave eq 'CPF'",
  orderby = "qtdChaves desc",
  top = 100
)

OData Filter Syntax

Operator	Description	Example
`eq`	Equal	`"Estado eq 'SÃO PAULO'"`
`ne`	Not equal	`"NATUREZA ne 'P2P'"`
`gt`	Greater than	`"VALOR gt 1000"`
`ge`	Greater or equal	`"QUANTIDADE ge 100"`
`lt`	Less than	`"VALOR lt 5000"`
`le`	Less or equal	`"QUANTIDADE le 50"`
`and`	Logical AND	`"NATUREZA eq 'P2P' and PAG_REGIAO eq 'SUDESTE'"`
`or`	Logical OR	`"Estado eq 'SP' or Estado eq 'RJ'"`

Available Functions

Data Retrieval Functions

Function	Description
`get_pix_keys()`	PIX keys stock by participant
`get_pix_keys_summary()`	Top institutions by key count
`get_pix_keys_by_type()`	Keys aggregated by type
`get_pix_transaction_stats()`	Detailed transaction statistics
`get_pix_summary()`	Aggregated summaries by grouping
`get_pix_transaction_stats_multi()`	Stats for multiple months
`get_pix_transactions_by_municipality()`	Transactions by municipality
`get_pix_transactions_by_state()`	Aggregated by state
`get_pix_transactions_by_region()`	Aggregated by region
`get_pix_fraud_stats()`	Fraud statistics (MED)

Utility Functions

Function	Description
`pix_endpoints()`	List available API endpoints
`pix_columns()`	Column info for each endpoint
`pix_timeout()`	Get or set request timeout
`pix_url()`	Build API URL for debugging
`pix_query()`	Custom OData queries

Examples

PIX Keys

library(pixr)
library(dplyr)

# Get keys stock for December 2025
keys <- get_pix_keys(date = "2025-12-01")

# Top 20 institutions
get_pix_keys_summary(date = "2025-12-01", n_top = 20)

# Aggregate by key type
keys |>
  group_by(TipoChave, NaturezaUsuario) |>
  summarise(total = sum(qtdChaves), .groups = "drop")

Transaction Statistics

# Get statistics for September 2025
stats <- get_pix_transaction_stats(database = "202509")

# Summary by transaction nature (P2P, P2B, etc.)
get_pix_summary(database = "202509", group_by = "NATUREZA")

# Multiple months
q3_data <- get_pix_transaction_stats_multi(
  databases = c("202507", "202508", "202509")
)

Transactions by Municipality

# Get all municipalities
muni <- get_pix_transactions_by_municipality(database = "202512")

# Filter by state
sp <- muni |> filter(Estado == "SÃO PAULO")

# Aggregate by state
get_pix_transactions_by_state(database = "202512")

# Aggregate by region
get_pix_transactions_by_region(database = "202512")

Debugging

# See the URL that would be called
pix_url("ChavesPix", params = list(Data = "2025-12-01"), top = 10)
pix_url("EstatisticasTransacoesPix", params = list(Database = "202509"))