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readrba <img src="man/figures/logo.png" align="right" height="139" />

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Get data from the Reserve Bank of Australia in a tidy tibble.

Installation

Install from CRAN using:

install.packages("readrba")

Or install the development version from GitHub:

remotes::install_github("mattcowgill/readrba")

Examples

library(ggplot2)
#> Warning: package 'ggplot2' was built under R version 4.4.3
library(dplyr)
#> Warning: package 'dplyr' was built under R version 4.4.3
library(readrba)

Quick examples

With just a few lines of code, you can get a data series from the RBA and visualise it!

Here’s the unemployment rate:

unemp_rate <- read_rba(series_id = "GLFSURSA") 
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs

unemp_rate %>%
  ggplot(aes(x = date, y = value)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Unemployment rate (actual)")

<img src="man/figures/README-unnamed-chunk-4-1.png" width="672" />

And you can also easily get the RBA’s public forecasts - from 1990 to present - and visualise those. Here’s every public forecast of the unemployment rate the RBA has made over the past three decades:

unemp_forecasts <- rba_forecasts() %>%
  filter(series == "unemp_rate")
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs

unemp_forecasts %>%
  ggplot(aes(x = date, 
             y = value, 
             group = forecast_date, 
             col = forecast_date)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Unemployment rate (RBA forecasts)")

<img src="man/figures/README-unnamed-chunk-5-1.png" width="672" />

Reading RBA data

There primary function in {readrba} is read_rba().

Here’s how you fetch the current version of a single RBA statistical table: table G1, consumer price inflation using read_rba():

cpi_table <- read_rba(table_no = "g1")
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs

The object returned by read_rba() is a tidy tibble (ie. in ‘long’ format):

head(cpi_table)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1922-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 2 1922-09-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 3 1922-12-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2025-07-31
#> 4 1923-03-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2025-07-31
#> 5 1923-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 6 1923-09-30 Consumer price…   2.9 Quarterly Original    Inde… ABS /… 2025-07-31
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

You can also request multiple tables. They’ll be returned together as one tidy tibble:

rba_data <- read_rba(table_no = c("a1", "g1"))
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning: All formats failed to parse. No formats found.

head(rba_data)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 2013-07-03 Australian dol… 37899 Weekly    Original    $ mi… RBA    2025-08-01
#> 2 2013-07-10 Australian dol… 35106 Weekly    Original    $ mi… RBA    2025-08-01
#> 3 2013-07-17 Australian dol… 32090 Weekly    Original    $ mi… RBA    2025-08-01
#> 4 2013-07-24 Australian dol… 39592 Weekly    Original    $ mi… RBA    2025-08-01
#> 5 2013-07-31 Australian dol… 41286 Weekly    Original    $ mi… RBA    2025-08-01
#> 6 2013-08-07 Australian dol… 37974 Weekly    Original    $ mi… RBA    2025-08-01
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

unique(rba_data$table_title)
#> [1] "A1 Reserve Bank Of Australia - Balance Sheet"
#> [2] "G1 Consumer Price Inflation"

You can also retrieve data based on the unique RBA time series identifier(s). For example, to getch the consumer price index series only:

cpi_series <- read_rba(series_id = "GCPIAG")
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
head(cpi_series)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1922-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 2 1922-09-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 3 1922-12-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2025-07-31
#> 4 1923-03-31 Consumer price…   2.7 Quarterly Original    Inde… ABS /… 2025-07-31
#> 5 1923-06-30 Consumer price…   2.8 Quarterly Original    Inde… ABS /… 2025-07-31
#> 6 1923-09-30 Consumer price…   2.9 Quarterly Original    Inde… ABS /… 2025-07-31
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>
unique(cpi_series$series_id)
#> [1] "GCPIAG"

The convenience function read_rba_seriesid() is a wrapper around read_rba(). This means read_rba_seriesid("GCPIAG") is equivalent to read_rba(series_id = "GCPIAG").

By default, read_rba() fetches the current version of whatever table you request. You can specify the historical version of a table, if it’s available, using the cur_hist argument:

hist_a11 <- read_rba(table_no = "a1.1", cur_hist = "historical")
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning in utils::download.file(url = url, destfile = destfile, mode = mode, :
#> the 'wininet' method is deprecated for http:// and https:// URLs
#> Warning: All formats failed to parse. No formats found.
#> Warning: All formats failed to parse. No formats found.

head(hist_a11)
#> # A tibble: 6 × 11
#>   date       series          value frequency series_type units source pub_date  
#>   <date>     <chr>           <dbl> <chr>     <chr>       <chr> <chr>  <date>    
#> 1 1994-06-01 Australian dol… 13680 Weekly    Original    $ mi… RBA    2023-05-05
#> 2 1994-06-08 Australian dol… 13055 Weekly    Original    $ mi… RBA    2023-05-05
#> 3 1994-06-15 Australian dol… 13086 Weekly    Original    $ mi… RBA    2023-05-05
#> 4 1994-06-22 Australian dol… 12802 Weekly    Original    $ mi… RBA    2023-05-05
#> 5 1994-06-29 Australian dol… 13563 Weekly    Original    $ mi… RBA    2023-05-05
#> 6 1994-07-06 Australian dol… 12179 Weekly    Original    $ mi… RBA    2023-05-05
#> # ℹ 3 more variables: series_id <chr>, description <chr>, table_title <chr>

Browsing RBA data

Two functions are provided to help you find the table number or series ID you need. These are browse_rba_tables() and browse_rba_series(). Each returns a tibble with information about the available RBA data.

browse_rba_tables()
#> # A tibble: 125 × 5
#>    title                              no    url   current_or_historical readable
#>    <chr>                              <chr> <chr> <chr>                 <lgl>   
#>  1 RBA Balance Sheet                  A1    http… current               TRUE    
#>  2 Monetary Policy Changes            A2    http… current               TRUE    
#>  3 Monetary Policy Operations – Curr… A3    http… current               TRUE    
#>  4 Holdings of Australian Government… A3.1  http… current               TRUE    
#>  5 Securities Lending Repurchase and… A3.2  http… current               TRUE    
#>  6 Foreign Exchange Transactions and… A4    http… current               TRUE