fmt_auto: Automatically format column data according to their values

View source: R/format_data.R

fmt_autoR Documentation

Automatically format column data according to their values


The fmt_auto() function will automatically apply formatting of various types in a way that best suits the data table provided. The function will attempt to format numbers such that they are condensed to an optimal width, either with scientific notation or large-number suffixing. Currency values are detected by currency codes embedded in the column name and formatted in the correct way. Although the functionality here is comprehensive it's still possible to reduce the scope of automatic formatting with the scope argument and also by choosing a subset of columns and rows to which the formatting will be applied.


  columns = everything(),
  rows = everything(),
  scope = c("numbers", "currency"),
  lg_num_pref = c("sci", "suf"),
  locale = NULL



A table object that is created using the gt() function.


The columns to format. Can either be a series of column names provided in c(), a vector of column indices, or a helper function focused on selections. The select helper functions are: starts_with(), ends_with(), contains(), matches(), one_of(), num_range(), and everything().


Optional rows to format. Providing everything() (the default) 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 helper function focused on selections. The select helper functions are: 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).


The scope of automatic formatting. By default this includes "numbers"-type values and "currency"-type values though the scope can be reduced to a single type of value to format.


The preference toward either scientific notation for very small and very large values ("sci", the default option), or, suffixed numbers ("suf", for large values only).


An optional locale identifier that can be used for formatting the value according the locale's rules. Examples include "en" for English (United States) and "fr" for French (France). The use of a locale ID will override any locale-specific values provided. We can use the info_locales() function as a useful reference for all of the locales that are supported.


An object of class gt_tbl.

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.


Use exibble to create a gt table. Format the columns automatically with fmt_auto().

exibble |>
  gt() |>
This image of a table was generated from the first code example in the `fmt_auto()` help file.

Let's now use countrypops to create another gt table. Automatically format all columns with fmt_auto() but elect to use large-number suffixing instead of scientific notation with the lg_num_pref = "suf" option.

countrypops |>
  dplyr::select(country_code_3, year, population) |>
  dplyr::filter(country_code_3 %in% c("CHN", "IND", "USA", "PAK", "IDN")) |>
  dplyr::filter(year > 1975 & year %% 5 == 0) |>
  tidyr::spread(year, population) |>
  dplyr::arrange(desc(`2020`)) |>
  gt(rowname_col = "country_code_3") |>
  fmt_auto(lg_num_pref = "suf")
This image of a table was generated from the second code example in the `fmt_auto()` help file.

Function ID


Function Introduced

In Development

See Also

Other data formatting functions: data_color(), fmt_bins(), fmt_bytes(), fmt_currency(), fmt_datetime(), fmt_date(), fmt_duration(), fmt_engineering(), fmt_flag(), fmt_fraction(), fmt_image(), fmt_index(), fmt_integer(), fmt_markdown(), fmt_number(), fmt_partsper(), fmt_passthrough(), fmt_percent(), fmt_roman(), fmt_scientific(), fmt_spelled_num(), fmt_time(), fmt_url(), fmt(), sub_large_vals(), sub_missing(), sub_small_vals(), sub_values(), sub_zero()

gt documentation built on April 3, 2023, 5:18 p.m.