realestatebr

realestatebr aims to provide an unified interface to Brazilian real estate information, delivering data from different sources in a tidy format. The package is organized by source, with each source having multiple associated tables (datasets).

Installation

# install.packages("remotes")
remotes::install_github("viniciusoike/realestatebr")

Quick Start

There are two key functions in realestatebr: get_dataset() and list_datasets(). The former retrieves data, while the latter lists all available datasets. get_dataset() expects a name and a (optional) table argument. If no table is specified, the function returns the first available table.

library(realestatebr)

# Discover available datasets
datasets <- list_datasets()

# Get specific table
sbpe <- get_dataset(name = "abecip", table = "sbpe")

# Get property price indices
fipezap <- get_dataset("rppi", "fipezap")

Available Datasets

Some of the available datasets are listed below.

Dataset	Producer	Description
abecip	ABECIP	Housing credit flows, financed units, home equity
abrainc	ABRAINC/FIPE	Primary market indicators (launches, sales)
bcb_realestate	BCB	Real estate credit and market data
secovi	SECOVI-SP	São Paulo market indicators
rppi	Multiple	Property price indices (sale/rent, 50+ cities)
rppi_bis	BIS	International property price indices (60+ countries)
bcb_series	BCB	Economic time series
cbic	CBIC	Cement consumption and production

Caching

How Caching Works

On first use, datasets are automatically downloaded from GitHub releases and cached in your user directory. Subsequent uses load data instantly from cache, even offline.

# First use: downloads and caches (~3-5 seconds)
data1 <- get_dataset("abecip")

# Subsequent uses: loads from cache (instant)
data2 <- get_dataset("abecip")

Managing Cache

# Check cache location
get_user_cache_dir()

# List cached datasets
list_cached_files()

# Clear specific dataset
clear_user_cache("abecip")

# Clear all cache (with confirmation)
clear_user_cache()

# Update cache from GitHub
update_cache_from_github("abecip")

Data Sources

The source parameter controls where data comes from.

# Auto (default): cache → GitHub → fresh
data <- get_dataset("abecip")

# User cache only (instant, offline)
data <- get_dataset("abecip", source = "cache")

# GitHub releases (requires piggyback package)
data <- get_dataset("abecip", source = "github")

# Fresh download from original source
data <- get_dataset("abecip", source = "fresh")

Example: Property Price Indices

library(ggplot2)
library(realestatebr)
library(dplyr, warn.conflicts = FALSE)

# Get FipeZap index
fipezap <- get_dataset("rppi", table = "fipezap")

# Brazil national index
rppi_spo <- fipezap |>
  filter(
    name_muni == "São Paulo",
    market == "residential",
    rooms == "total",
    variable == "acum12m",
    date >= as.Date("2019-01-01")
  )

ggplot(rppi_spo, aes(x = date, y = value, color = rent_sale)) +
  geom_line(lwd = 0.8) +
  geom_hline(yintercept = 0) +
  scale_x_date(date_breaks = "1 year", date_labels = "%Y") +
  scale_y_continuous(labels = seq(-0.05, 0.15, by = 0.05) * 100, ) +
  labs(
    title = "Brazil Property Price Index",
    x = NULL,
    y = "YoY chg. (%)",
    color = ""
  ) +
  theme_minimal() +
  theme(
    legend.position = "bottom",
    palette.colour.discrete = c("#2C6BB3", "#1abc9c", "#f39c12")
  )

International Comparison

# Get BIS international data
bis <- get_dataset("rppi_bis")

# Compare countries
bis_compare <- bis |>
  filter(
    reference_area %in% c("Brazil", "United States", "Japan"),
    is_nominal == FALSE,
    unit == "Index, 2010 = 100",
    date >= as.Date("2010-01-01")
  )

ggplot(bis_compare, aes(x = date, y = value, color = reference_area)) +
  geom_line(lwd = 0.8) +
  geom_hline(yintercept = 100) +
  labs(
    title = "Real Property Prices - International",
    x = NULL,
    y = "Index (2010 = 100)",
    color = "") +
  theme_minimal() +
  theme(
    legend.position = "bottom",
    palette.colour.discrete = c("#2C6BB3", "#1abc9c", "#f39c12")
  )

Learn More

• Getting Started vignette
• Working with RPPI vignette