Format values as integers

With numeric values in a gt table, we can perform number-based formatting so that the targeted values are always rendered as integer values. We can have fine control over integer formatting with the following options:

digit grouping separators: options to enable/disable digit separators and provide a choice of separator symbol
scaling: we can choose to scale targeted values by a multiplier value
large-number suffixing: larger figures (thousands, millions, etc.) can be autoscaled and decorated with the appropriate suffixes
pattern: option to use a text pattern for decoration of the formatted values
locale-based formatting: providing a locale ID will result in number formatting specific to the chosen locale

Usage

fmt_integer(
  data,
  columns = everything(),
  rows = everything(),
  use_seps = TRUE,
  accounting = FALSE,
  scale_by = 1,
  suffixing = FALSE,
  pattern = "{x}",
  sep_mark = ",",
  force_sign = FALSE,
  system = c("intl", "ind"),
  locale = NULL
)

Arguments

data

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

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

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_seps

Use digit group separators

scalar<logical> // default: TRUE

An option to use digit group separators. The type of digit group separator is set by sep_mark and overridden if a locale ID is provided to locale. This setting is TRUE by default.

accounting

Use accounting style

scalar<logical> // default: FALSE

An option to use accounting style for values. Normally, negative values will be shown with a minus sign but using accounting style will instead put any negative values in parentheses.

scale_by

Scale values by a fixed multiplier

scalar<numeric|integer> // default: 1

All numeric values will be multiplied by the scale_by value before undergoing formatting. Since the default value is 1, no values will be changed unless a different multiplier value is supplied. This value will be ignored if using any of the suffixing options (i.e., where suffixing is not set to FALSE).

suffixing

Specification for large-number suffixing

scalar<logical>|vector<character> // default: FALSE

The suffixing option allows us to scale and apply suffixes to larger numbers (e.g., 1924000 can be transformed to 2M). This option can accept a logical value, where FALSE (the default) will not perform this transformation and TRUE will apply thousands (K), millions (M), billions (B), and trillions (T) suffixes after automatic value scaling.

We can alternatively provide a character vector that serves as a specification for which symbols are to used for each of the value ranges. These preferred symbols will replace the defaults (e.g., c("k", "Ml", "Bn", "Tr") replaces "K", "M", "B", and "T").

Including NA values in the vector will ensure that the particular range will either not be included in the transformation (e.g., c(NA, "M", "B", "T") won't modify numbers at all in the thousands range) or the range will inherit a previous suffix (e.g., with c("K", "M", NA, "T"), all numbers in the range of millions and billions will be in terms of millions).

Any use of suffixing (where it is not set expressly as FALSE) means that any value provided to scale_by will be ignored.

If using system = "ind" then the default suffix set provided by suffixing = TRUE will be the equivalent of c(NA, "L", "Cr"). This doesn't apply suffixes to the thousands range, but does express values in lakhs and crores.

pattern

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.

sep_mark

Separator mark for digit grouping

scalar<character> // default: ","

The string to use as a separator between groups of digits. For example, using sep_mark = "," with a value of 1000 would result in a formatted value of "1,000". This argument is ignored if a locale is supplied (i.e., is not NULL).

force_sign

Forcing the display of a positive sign

scalar<logical> // default: FALSE

Should the positive sign be shown for positive values (effectively showing a sign for all values except zero)? If so, use TRUE for this option. The default is FALSE, where only negative numbers will display a minus sign. This option is disregarded when using accounting notation with accounting = TRUE.

system

Numbering system for grouping separators

singl-kw:[intl|ind] // default: "intl"

The international numbering system (keyword: "intl") is widely used and its grouping separators (i.e., sep_mark) are always separated by three digits. The alternative system, the Indian numbering system (keyword: "ind"), uses grouping separators that correspond to thousand, lakh, crore, and higher quantities.

locale

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.

Value

An object of class gt_tbl.

Compatibility of formatting function with data values

The fmt_integer() 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.

Compatibility of arguments with the `from_column()` helper function

The from_column() helper function can be used with certain arguments of fmt_integer() to obtain varying parameter values from a specified column within the table. This means that each row could be formatted a little bit differently. These arguments provide support for from_column():

use_seps
accounting
scale_by
suffixing
pattern
sep_mark
force_sign
system
locale

Please note that for all of the aforementioned arguments, a from_column() call needs to reference a column that has data of the correct type (this is different for each argument). Additional columns for parameter values can be generated with the cols_add() function (if not already present). Columns that contain parameter data can also be hidden from final display with cols_hide(). Finally, there is no limitation to how many arguments the from_column() helper is applied so long as the arguments belong to this closed set.

Adapting output to a specific `locale`

This formatting function can adapt outputs according to a provided locale value. Examples include "en" for English (United States) and "fr" for French (France). The use of a valid locale ID here means separator marks will be correct for the given locale. Should any value be provided in sep_mark, it will be overridden by the locale's preferred value.

Note that a locale value provided here will override any global locale setting performed in gt()'s own locale argument (it is settable there as a value received by all other functions that have a locale argument). As a useful reference on which locales are supported, we can use the info_locales() function to view an info table.

Examples

For this example, we'll use two columns from the exibble dataset and create a simple gt table. With the fmt_integer() function, we'll format the num column as integer values having no digit separators (with the use_seps = FALSE option).

exibble |>
  dplyr::select(num, char) |>
  gt() |>
  fmt_integer(use_seps = FALSE)

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

Let's use a modified version of the countrypops dataset to create a gt table with row labels. We will format all numeric columns with fmt_integer() and scale all values by 1 / 1E6, giving us integer values representing millions of people. We can make clear what the values represent with an informative spanner label via tab_spanner().

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(`2015`)) |>
  gt(rowname_col = "country_code_3") |>
  fmt_integer(scale_by = 1 / 1E6) |>
  tab_spanner(label = "Millions of People", columns = everything())

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

Using a subset of the towny dataset, we can do interesting things with integer values. Through cols_add() we'll add the difference column (which calculates the difference between 2021 and 2001 populations). All numeric values will be formatted with a first pass of fmt_integer(); a second pass of fmt_integer() focuses on the difference column and here we use the force_sign = TRUE option to draw attention to positive and negative difference values.

towny |>
  dplyr::select(name, population_2001, population_2021) |>
  dplyr::slice_tail(n = 10) |>
  gt() |>
  cols_add(difference = population_2021 - population_2001) |>
  fmt_integer() |>
  fmt_integer(columns = difference, force_sign = TRUE) |>
  cols_label_with(fn = function(x) gsub("population_", "", x)) |>
  tab_style(
    style = cell_fill(color = "gray90"),
    locations = cells_body(columns = difference)
  )

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

Function ID

3-2

Function Introduced

v0.3.1 (August 9, 2021)