Appendix A — Quick reference

This appendix provides a consolidated reference for the gt package, including informational functions that display helpful lookup tables, descriptions of all built-in datasets, and a quick guide to the most commonly used helper functions.

A.1 Date and time style references

A.1.1 `info_date_style()`

Displays all 41 available date formatting styles for use with fmt_date() and fmt_datetime().

info_date_style()

The resulting table shows:

style number: the numeric identifier for each style
style name: the string identifier (e.g., "iso", "month_day_year")
example output: how each style renders a sample date
flexible: whether the style adapts to locale settings

Use style names (or numbers) in your formatting calls:

fmt_date(columns = date_col, date_style = "month_day_year")
fmt_date(columns = date_col, date_style = 14)

A.1.2 `info_time_style()`

Displays all available time formatting styles for use with fmt_time() and fmt_datetime().

info_time_style()

The table shows similar information to date styles: style numbers, names, example output, and locale flexibility.

A.2 Currency reference

A.2.1 `info_currencies()`

Displays a comprehensive table of all supported currencies, including their codes, symbols, and names.

info_currencies()

The table includes:

currency code: the 3-letter ISO 4217 code (e.g., "USD", "EUR", "JPY")
currency symbol: the symbol used in formatting (e.g., $, €, ¥)
currency name: the full name of the currency

Use currency codes with fmt_currency():

fmt_currency(columns = price, currency = "EUR")
fmt_currency(columns = price, currency = "JPY")

A.3 Locale reference

A.3.1 `info_locales()`

Displays all supported locales for internationalized formatting. Locales affect number formatting, date formatting, and translated text.

info_locales()

The table shows locale codes and their corresponding languages/regions. Use these codes with:

the locale argument in gt()
the locale argument in formatting functions
the locale argument in fmt_spelled_num()

gt(data, locale = "de")
fmt_number(columns = value, locale = "fr")
fmt_date(columns = date, locale = "ja")

A.4 Color palette reference

A.4.1 `info_paletteer()`

The paletteer package provides access to hundreds of color palettes from various R packages. The info_paletteer() function displays available palettes that work well with data_color().

info_paletteer()

The table groups palettes by their source package and shows color swatches for each palette. Use palette names with data_color():

data_color(
  columns = value,
  palette = "viridis::plasma"
)

Palette names follow the format "package::palette".

A.5 Flag reference

A.5.1 `info_flags()`

Displays all available country flags that can be rendered with fmt_flag(), along with their country codes.

info_flags()

The table shows:

country code (2-letter): ISO 3166-1 alpha-2 codes
country code (3-letter): ISO 3166-1 alpha-3 codes
country name: full country name
flag preview: the rendered flag icon

Use these codes with fmt_flag():

fmt_flag(columns = country_code)

A.6 Icon reference

A.6.1 `info_icons()`

Displays all available Font Awesome icons for use with fmt_icon().

info_icons()

The table shows icon names and rendered previews. Use icon names in your data or with fmt_icon():

dplyr::tibble(
  category = c("file", "folder", "image"),
  icon_name = c("file-alt", "folder", "image")
) |>
  gt() |>
  fmt_icon(columns = icon_name)

A.7 Google Fonts reference

A.7.1 `info_google_fonts()`

Displays recommended Google Fonts for use with gt tables, along with information about how to use them.

info_google_fonts()

Use Google Fonts with opt_table_font() or google_font():

gt(data) |>
  opt_table_font(font = google_font("Roboto"))

gt(data) |>
  tab_style(
    style = cell_text(font = google_font("Fira Code")),
    locations = cells_body(columns = code_col)
  )

A.8 Unit conversion reference

A.8.1 `info_unit_conversions()`

Displays all unit conversions supported by the unit_conversion() helper function. This is useful when you need to convert between measurement units.

info_unit_conversions()

The table shows:

unit class: the category of measurement (length, mass, volume, etc.)
from units: available source units
to units: available target units
conversion factors: the multipliers used

Use with unit_conversion():

# Get conversion factor from miles to kilometers
unit_conversion(from = "mi", to = "km")

# Apply in a table
dplyr::tibble(distance_miles = c(10, 25, 100)) |>
  gt() |>
  cols_add(distance_km = distance_miles * unit_conversion("mi", "km")) |>
  fmt_number(columns = everything(), decimals = 1)

A.9 Built-in datasets

The gt package includes 18 datasets for learning and experimentation. These datasets appear throughout the documentation and examples.

A.9.1 Small example datasets

These compact datasets are ideal for quick experiments and learning the basics of gt.

Dataset	Description	Rows	Use Case
`exibble`	A toy tibble with various data types	8	Testing formatters
`gtcars`	Specifications for 47 luxury/supercars	47	Car comparisons
`pizzaplace`	A year of pizza sales	49,574	Sales analysis

A.9.2 Country and population data

These datasets provide demographic information useful for geographic visualizations and population analysis.

Dataset	Description	Rows	Use Case
`countrypops`	Country populations 1960-2024	~13,000	Time series, maps
`towny`	Ontario municipality populations	414	Canadian demographics
`peeps`	Personal information for fictional people	100	Contact directories

A.9.3 Scientific and technical data

These datasets contain scientific measurements and constants, suitable for demonstrating technical table formatting.

Dataset	Description	Rows	Use Case
`sza`	Solar zenith angles by location/time	816	Heatmaps
`constants`	Fundamental physical constants	30	Scientific tables
`reactions`	Atmospheric reaction rates	1,344	Chemistry data
`photolysis`	Photolysis rates for organic compounds	1,590	Chemistry data
`nuclides`	Nuclear data for isotopes	3,384	Nuclear chemistry

A.9.4 Financial and geographic data

These datasets cover financial markets and location-based information for diverse table examples.

Dataset	Description	Rows	Use Case
`sp500`	S&P 500 daily data 1950-2015	16,607	Financial analysis
`metro`	Paris Metro stations	308	Geographic data
`gibraltar`	May 2023 Gibraltar weather	744	Weather data
`films`	Cannes Film Festival competition	1,607	Entertainment data

A.9.5 Clinical trial data

These datasets follow pharmaceutical industry conventions, useful for creating clinical study tables.

Dataset	Description	Rows	Use Case
`rx_adsl`	ADSL-style clinical trial data	182	Clinical tables
`rx_addv`	ADDV-style clinical trial data	910	Clinical tables
`illness`	Lab tests for illness tracking	39	Medical data

A.9.6 Using built-in datasets

All datasets are automatically available when you load the gt package, requiring no additional data import steps.

# View first few rows
head(exibble)

# A tibble: 6 × 9
       num char    fctr  date       time  datetime         currency row   group
     <dbl> <chr>   <fct> <chr>      <chr> <chr>               <dbl> <chr> <chr>
1    0.111 apricot one   2015-01-15 13:35 2018-01-01 02:22    50.0  row_1 grp_a
2    2.22  banana  two   2015-02-15 14:40 2018-02-02 14:33    18.0  row_2 grp_a
3   33.3   coconut three 2015-03-15 15:45 2018-03-03 03:44     1.39 row_3 grp_a
4  444.    durian  four  2015-04-15 16:50 2018-04-04 15:55 65100    row_4 grp_a
5 5550     <NA>    five  2015-05-15 17:55 2018-05-05 04:00  1326.   row_5 grp_b
6   NA     fig     six   2015-06-15 <NA>  2018-06-06 16:11    13.3  row_6 grp_b

# Use in a table
gtcars |>
  dplyr::select(mfr, model, year, hp, mpg_c) |>
  dplyr::slice(1:5) |>
  gt()

mfr	model	year	hp	mpg_c
Ford	GT	2017	647	11
Ferrari	458 Speciale	2015	597	13
Ferrari	458 Spider	2015	562	13
Ferrari	458 Italia	2014	562	13
Ferrari	488 GTB	2016	661	15

A.10 Helper functions quick reference

A.10.1 Text and content helpers

These functions allow you to include formatted text in table headers, labels, and notes.

Function	Purpose	Example
`md()`	Interpret text as Markdown	`tab_header(title = md("Bold Title"))`
`html()`	Interpret text as HTML	`tab_header(title = html("<em>Styled</em>"))`
`latex()`	Interpret text as LaTeX	`tab_source_note(latex("\\textit{Note}"))`

A.10.2 Unit helpers

These functions specify measurement units for sizing columns and other table elements.

Function	Purpose	Example
`px()`	Specify pixels	`cols_width(col ~ px(150))`
`pct()`	Specify percentage	`cols_width(col ~ pct(25))`

A.10.3 Dynamic value helpers

These functions enable data-driven formatting by referencing values from other columns or defining custom formats.

Function	Purpose	Example
`from_column()`	Reference column values	`fmt_number(decimals = from_column("precision"))`
`currency()`	Custom currency symbol	`fmt_currency(currency = currency(symbol = "BTC"))`

A.10.4 Color helpers

These functions help manipulate colors for consistent styling across your tables.

Function	Purpose	Example
`adjust_luminance()`	Lighten/darken colors	`adjust_luminance("steelblue", steps = 1)`

A.10.5 Font helpers

These functions provide access to web fonts and system font stacks for typography customization.

Function	Purpose	Example
`google_font()`	Specify Google Font	`opt_table_font(font = google_font("Roboto"))`
`default_fonts()`	Get default font stack	`default_fonts()`
`system_fonts()`	Get system font stack	`system_fonts("humanist")`

A.10.6 Location helpers (for `tab_style()`, `tab_footnote()`, etc.)

These functions target specific regions of the table for styling, footnotes, or other modifications.

Function	Target
`cells_title()`	Table title and subtitle
`cells_stubhead()`	Stubhead label
`cells_column_labels()`	Column labels
`cells_column_spanners()`	Column spanner labels
`cells_row_groups()`	Row group labels
`cells_stub()`	Stub (row labels)
`cells_body()`	Body cells
`cells_summary()`	Group summary cells
`cells_grand_summary()`	Grand summary cells
`cells_stub_summary()`	Stub cells in summaries
`cells_stub_grand_summary()`	Stub cells in grand summary
`cells_footnotes()`	Footnote area
`cells_source_notes()`	Source note area

A.10.7 Style helpers (for `tab_style()`)

These functions define visual properties that can be applied to targeted table locations.

Function	Purpose
`cell_text()`	Text styling (color, size, weight, etc.)
`cell_fill()`	Background color
`cell_borders()`	Border styling

A.10.8 Selection helpers (for column selection)

These tidyselect-compatible functions help you specify which columns to target in formatting and styling operations.

Function	Purpose
`stub()`	Select stub column
`row_group()`	Select row group column
`everything()`	Select all columns
`starts_with()`	Columns starting with prefix
`ends_with()`	Columns ending with suffix
`contains()`	Columns containing string
`matches()`	Columns matching regex
`where()`	Columns matching predicate

A.10.9 Utility helpers

These functions provide miscellaneous utilities for table IDs, LaTeX output, and special character handling.

Function	Purpose
`random_id()`	Generate a random table ID
`escape_latex()`	Escape special LaTeX characters
`gt_latex_dependencies()`	Get LaTeX package requirements