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With numeric values in a gt table we can transform those to index values, usually based on letters. These characters can be derived from a specified locale and they are intended for ordering (often leaving out characters with diacritical marks).


  columns = everything(),
  rows = everything(),
  case = c("upper", "lower"),
  index_algo = c("repeat", "excel"),
  pattern = "{x}",
  locale = NULL



The gt table data object

obj:<gt_tbl> --- required

This is the gt table object that is commonly created through use of the gt() function.


Columns to target

<column-targeting expression> --- default: everything()

Can either be a series of column names provided in c(), a vector of column indices, or a select helper function. Examples of select helper functions include starts_with(), ends_with(), contains(), matches(), one_of(), num_range(), and everything().


Rows to target

<row-targeting expression> --- default: everything()

In conjunction with columns, we can specify which of their rows should undergo formatting. The default everything() results in all rows in columns being formatted. Alternatively, we can supply a vector of row captions within c(), a vector of row indices, or a select helper function. Examples of select helper functions include starts_with(), ends_with(), contains(), matches(), one_of(), num_range(), and everything(). We can also use expressions to filter down to the rows we need (e.g., [colname_1] > 100 & [colname_2] < 50).


Use uppercase or lowercase letters

singl-kw:[upper|lower] --- default: "upper"

Should the resulting index characters be rendered as uppercase ("upper") or lowercase ("lower") letters? By default, this is set to "upper".


Indexing algorithm

singl-kw:[repeat|excel] --- default: "repeat"

The indexing algorithm handles the recycling of the index character set. By default, the "repeat" option is used where characters are doubled, tripled, and so on, when moving past the character set limit. The alternative is the "excel" option, where Excel-based column naming is adapted and used here (e.g., [..., Y, Z, AA, AB, ...]).


Specification of the formatting pattern

scalar<character> --- default: "{x}"

A formatting pattern that allows for decoration of the formatted value. The formatted value is represented by the {x} (which can be used multiple times, if needed) and all other characters will be interpreted as string literals.


Locale identifier

scalar<character> --- default: NULL (optional)

An optional locale identifier that can be used for formatting values according the locale's rules. Examples include "en" for English (United States) and "fr" for French (France). We can use the info_locales() function as a useful reference for all of the locales that are supported. A locale ID can be also set in the initial gt() function call (where it would be used automatically by any function with a locale argument) but a locale value provided here will override that global locale.


An object of class gt_tbl.

Compatibility of formatting function with data values

The fmt_index() formatting function is compatible with body cells that are of the "numeric" or "integer" types. Any other types of body cells are ignored during formatting. This is to say that cells of incompatible data types may be targeted, but there will be no attempt to format them.

Targeting cells with columns and rows

Targeting of values is done through columns and additionally by rows (if nothing is provided for rows then entire columns are selected). The columns argument allows us to target a subset of cells contained in the resolved columns. We say resolved because aside from declaring column names in c() (with bare column names or names in quotes) we can use tidyselect-style expressions. This can be as basic as supplying a select helper like starts_with(), or, providing a more complex incantation like

where(~ is.numeric(.x) && max(.x, na.rm = TRUE) > 1E6)

which targets numeric columns that have a maximum value greater than 1,000,000 (excluding any NAs from consideration).

By default all columns and rows are selected (with the everything() defaults). Cell values that are incompatible with a given formatting function will be skipped over, like character values and numeric fmt_*() functions. So it's safe to select all columns with a particular formatting function (only those values that can be formatted will be formatted), but, you may not want that. One strategy is to format the bulk of cell values with one formatting function and then constrain the columns for later passes with other types of formatting (the last formatting done to a cell is what you get in the final output).

Once the columns are targeted, we may also target the rows within those columns. This can be done in a variety of ways. If a stub is present, then we potentially have row identifiers. Those can be used much like column names in the columns-targeting scenario. We can use simpler tidyselect-style expressions (the select helpers should work well here) and we can use quoted row identifiers in c(). It's also possible to use row indices (e.g., c(3, 5, 6)) though these index values must correspond to the row numbers of the input data (the indices won't necessarily match those of rearranged rows if row groups are present). One more type of expression is possible, an expression that takes column values (can involve any of the available columns in the table) and returns a logical vector. This is nice if you want to base formatting on values in the column or another column, or, you'd like to use a more complex predicate expression.


Using a summarized version of the towny dataset, let's create a gt table. Here, the fmt_index() function is used to transform incremental integer values into capitalized letters (in the ranking column). With cols_merge() that formatted column of "A" to "E" values is merged with the census_div column to create an indexed listing of census subdivisions, here ordered by increasing total municipal population.

towny |>
  dplyr::select(name, csd_type, census_div, population_2021) |>
  dplyr::group_by(census_div) |>
    population = sum(population_2021),
    .groups = "drop_last"
  ) |>
  dplyr::arrange(population) |>
  dplyr::slice_head(n = 5) |>
  dplyr::mutate(ranking = dplyr::row_number()) |>
  dplyr::select(ranking, dplyr::everything()) |>
  gt() |>
  fmt_integer() |>
  fmt_index(columns = ranking, pattern = "{x}.") |>
  cols_merge(columns = c(ranking, census_div)) |>
  cols_align(align = "left", columns = ranking) |>
    ranking = md("Census  \nSubdivision"),
    population = md("Population  \nin 2021")
  ) |>
  tab_header(title = md("The smallest  \ncensus subdivisions")) |>
  tab_options(table.width = px(325))

This image of a table was generated from the first code example in the `fmt_index()` help file.

Function ID


Function Introduced

v0.9.0 (Mar 31, 2023)