How to format currency in gt tables in R

how-to

gt tables

Learn format currency in gt tables in r with clear examples and explanations.

Published

April 3, 2026

Introduction

The gt package provides powerful tools for creating beautiful, publication-ready tables in R. One of its most useful features is fmt_currency(), which automatically formats numeric values as currency with proper symbols, decimal places, and locale-specific formatting. This function is essential when creating financial reports, dashboards, or any data presentation involving monetary values.

Loading Required Libraries

First, let’s load the necessary packages for this tutorial:

library(gt)
library(tidyverse)

Creating a Basic Data Table

Let’s start with a simple dataset containing stock symbols and their prices:

stock_data <- tibble(
  symbol = c("GOOG", "META", "MSFT"), 
  price = c(168, 465, 425)
)
stock_data

This creates a basic tibble with three tech stocks and their current prices in dollars.

Converting to a gt Table

Now let’s convert our data frame into a gt table for better presentation:

stock_data |>
  gt()

The gt() function transforms our tibble into a formatted HTML table, but the prices still appear as plain numbers without currency formatting.

Basic Currency Formatting

To format all numeric columns as currency, we can use fmt_currency() without specifying columns:

stock_data |>
  gt() |>
  fmt_currency()

This applies dollar formatting to all numeric columns, adding the $ symbol and two decimal places.

Targeting Specific Columns

For more control, specify which columns to format using the columns parameter:

stock_data |>
  gt() |>
  fmt_currency(columns = price)

This approach is safer when you have multiple numeric columns but only want to format certain ones as currency.

Working with Multiple Currencies

Let’s create a more complex example with multiple currency columns:

stock_data_multi <- tibble(
  symbol = c("GOOG", "META", "MSFT"), 
  price_USD = c(168, 465, 425)
) |>
  mutate(price_INR = price_USD * 80)

stock_data_multi

This creates a dataset with prices in both US dollars and Indian rupees.

Exploring Available Currency Options

Before formatting different currencies, let’s see what currency symbols are available:

info_currencies(type = "symbol")

This function shows all supported currency symbols and their corresponding names in the gt package.

Formatting Multiple Currencies

Now let’s format each currency column appropriately:

stock_data_multi |>
  gt() |>
  fmt_currency(columns = price_USD) |>
  fmt_currency(columns = price_INR, currency = "rupee")

Each fmt_currency() call can target different columns and apply different currency symbols, making it easy to create multi-currency tables.

Dynamic Currency Formatting

For more advanced use cases, you can format currencies dynamically based on data in your table:

multi_locale_data <- tibble(
  amount = rep(50.84, 5),
  currency = c("JPY", "USD", "GHS", "KRW", "CNY"),
  locale = c("ja", "en", "ee", "ko", "zh")
)

multi_locale_data

This creates a dataset with the same amount in different currencies and their corresponding locales.

Using Locale-Based Formatting

Finally, let’s format the currencies using their appropriate locales and hide the helper columns:

multi_locale_data |>
  gt() |>
  fmt_currency(
    columns = amount,
    locale = from_column(column = "locale")
  ) |>
  cols_hide(columns = locale)

The from_column() function tells gt to use values from the locale column to determine formatting, while cols_hide() removes the helper column from the final display.

Summary

The fmt_currency() function in gt provides flexible currency formatting options, from basic dollar formatting to complex multi-locale presentations. Key features include targeting specific columns, using different currency symbols, and dynamic formatting based on data values. These tools make it easy to create professional financial reports and data presentations with properly formatted monetary values.

--- title: "How to format currency in gt tables in R" description: "Learn format currency in gt tables in r with clear examples and explanations." date: 2026-04-03 categories: ['how-to', 'gt tables'] format: html: code-fold: false code-tools: true --- ## Introduction The `gt` package provides powerful tools for creating beautiful, publication-ready tables in R. One of its most useful features is `fmt_currency()`, which automatically formats numeric values as currency with proper symbols, decimal places, and locale-specific formatting. This function is essential when creating financial reports, dashboards, or any data presentation involving monetary values. ## Loading Required Libraries First, let's load the necessary packages for this tutorial: ```r library(gt) library(tidyverse) ``` ## Creating a Basic Data Table Let's start with a simple dataset containing stock symbols and their prices: ```r stock_data <- tibble( symbol = c("GOOG", "META", "MSFT"), price = c(168, 465, 425) ) stock_data ``` This creates a basic tibble with three tech stocks and their current prices in dollars. ## Converting to a gt Table Now let's convert our data frame into a `gt` table for better presentation: ```r stock_data |> gt() ``` The `gt()` function transforms our tibble into a formatted HTML table, but the prices still appear as plain numbers without currency formatting. ## Basic Currency Formatting To format all numeric columns as currency, we can use `fmt_currency()` without specifying columns: ```r stock_data |> gt() |> fmt_currency() ``` This applies dollar formatting to all numeric columns, adding the $ symbol and two decimal places. ## Targeting Specific Columns For more control, specify which columns to format using the `columns` parameter: ```r stock_data |> gt() |> fmt_currency(columns = price) ``` This approach is safer when you have multiple numeric columns but only want to format certain ones as currency. ## Working with Multiple Currencies Let's create a more complex example with multiple currency columns: ```r stock_data_multi <- tibble( symbol = c("GOOG", "META", "MSFT"), price_USD = c(168, 465, 425) ) |> mutate(price_INR = price_USD * 80) stock_data_multi ``` This creates a dataset with prices in both US dollars and Indian rupees. ## Exploring Available Currency Options Before formatting different currencies, let's see what currency symbols are available: ```r info_currencies(type = "symbol") ``` This function shows all supported currency symbols and their corresponding names in the `gt` package. ## Formatting Multiple Currencies Now let's format each currency column appropriately: ```r stock_data_multi |> gt() |> fmt_currency(columns = price_USD) |> fmt_currency(columns = price_INR, currency = "rupee") ``` Each `fmt_currency()` call can target different columns and apply different currency symbols, making it easy to create multi-currency tables. ## Dynamic Currency Formatting For more advanced use cases, you can format currencies dynamically based on data in your table: ```r multi_locale_data <- tibble( amount = rep(50.84, 5), currency = c("JPY", "USD", "GHS", "KRW", "CNY"), locale = c("ja", "en", "ee", "ko", "zh") ) multi_locale_data ``` This creates a dataset with the same amount in different currencies and their corresponding locales. ## Using Locale-Based Formatting Finally, let's format the currencies using their appropriate locales and hide the helper columns: ```r multi_locale_data |> gt() |> fmt_currency( columns = amount, locale = from_column(column = "locale") ) |> cols_hide(columns = locale) ``` The `from_column()` function tells `gt` to use values from the locale column to determine formatting, while `cols_hide()` removes the helper column from the final display. ## Summary The `fmt_currency()` function in `gt` provides flexible currency formatting options, from basic dollar formatting to complex multi-locale presentations. Key features include targeting specific columns, using different currency symbols, and dynamic formatting based on data values. These tools make it easy to create professional financial reports and data presentations with properly formatted monetary values.