fmt_number: Format numeric values

In gt: Easily Create Presentation-Ready Display Tables

Format numeric values

Description

With numeric values in a gt table, we can perform number-based formatting so that the targeted values are rendered with a higher consideration for tabular presentation. Furthermore, there is finer control over numeric formatting with the following options:

• decimals: choice of the number of decimal places, option to drop trailing zeros, and a choice of the decimal symbol

• 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_number(
  data,
  columns = everything(),
  rows = everything(),
  decimals = 2,
  n_sigfig = NULL,
  drop_trailing_zeros = FALSE,
  drop_trailing_dec_mark = TRUE,
  use_seps = TRUE,
  accounting = FALSE,
  scale_by = 1,
  suffixing = FALSE,
  pattern = "{x}",
  sep_mark = ",",
  dec_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 (e.g. starts_with(), ends_with(), contains(), matches(), 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 (e.g. starts_with(), ends_with(), contains(), matches(), 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).
decimals	Number of decimal places scalar<numeric|integer>(val>=0) // default: 2 This corresponds to the exact number of decimal places to use. A value such as 2.34 can, for example, be formatted with 0 decimal places and it would result in "2". With 4 decimal places, the formatted value becomes "2.3400".
n_sigfig	Number of significant figures scalar<numeric|integer>(val>=1) // default: NULL (optional) A option to format numbers to n significant figures. By default, this is NULL and thus number values will be formatted according to the number of decimal places set via decimals. If opting to format according to the rules of significant figures, n_sigfig must be a number greater than or equal to 1. Any values passed to the decimals and drop_trailing_zeros arguments will be ignored.
drop_trailing_zeros	Drop any trailing zeros ⁠scalar<logical>⁠ // default: FALSE A logical value that allows for removal of trailing zeros (those redundant zeros after the decimal mark).
drop_trailing_dec_mark	Drop the trailing decimal mark ⁠scalar<logical>⁠ // default: TRUE A logical value that determines whether decimal marks should always appear even if there are no decimal digits to display after formatting (e.g., 23 becomes 23. if FALSE). By default trailing decimal marks are not shown.
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 ⁠1.92M⁠). 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).
dec_mark	Decimal mark ⁠scalar<character>⁠ // default: "." The string to be used as the decimal mark. For example, using dec_mark = "," with the value 0.152 would result in a formatted value of "0,152"). 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 call info_locales() for 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

fmt_number() 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

from_column() can be used with certain arguments of fmt_number() 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():

• decimals

• n_sigfig

• drop_trailing_zeros

• drop_trailing_dec_mark

• use_seps

• accounting

• scale_by

• suffixing

• pattern

• sep_mark

• dec_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 cols_add() (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 and decimal marks will be correct for the given locale. Should any values be provided in sep_mark or dec_mark, they will be overridden by the locale's preferred values.

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 call info_locales() to view an info table.

Examples

Let's use the exibble dataset to create a gt table. With fmt_number(), we'll format the num column to have three decimal places (with decimals = 3) and omit the use of digit separators (with use_seps = FALSE).

exibble |>
  gt() |>
  fmt_number(
    columns = num,
    decimals = 3,
    use_seps = FALSE
  )

Use a modified version of the countrypops dataset to create a gt table with row labels. Format all columns to use large-number suffixing (e.g., where "10,000,000" becomes "10M") with the suffixing = TRUE 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(`2015`)) |>
  gt(rowname_col = "country_code_3") |>
  fmt_number(suffixing = TRUE)

In a variation of the previous table, we can combine large-number suffixing with a declaration of the number of significant digits to use. With things like population figures, n_sigfig = 3 is a very good 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(`2015`)) |>
  gt(rowname_col = "country_code_3") |>
  fmt_number(suffixing = TRUE, n_sigfig = 3)

There can be cases where you want to show numbers to a large number of decimal places but also drop the unnecessary trailing zeros for low-precision values. Let's take a portion of the towny dataset and format the latitude and longitude columns with fmt_number(). We'll have up to 5 digits displayed as decimal values, but we'll also unconditionally drop any runs of trailing zeros in the decimal part with drop_trailing_zeros = TRUE.

towny |>
  dplyr::select(name, latitude, longitude) |>
  dplyr::slice_head(n = 10) |>
  gt() |>
  fmt_number(decimals = 5, drop_trailing_zeros = TRUE) |>
  cols_merge(columns = -name, pattern = "{1}, {2}") |>
  cols_label(
    name ~ "Municipality",
    latitude = "Location"
  )

Another strategy for dealing with precision of decimals is to have a separate column of values that specify how many decimal digits to retain. Such a column can be added via cols_add() or it can be part of the input table for gt(). With that column available, it can be referenced in the decimals argument with from_column(). This approach yields a display of coordinate values that reflects the measurement precision of each value.

towny |>
  dplyr::select(name, latitude, longitude) |>
  dplyr::slice_head(n = 10) |>
  gt() |>
  cols_add(dec_digits = c(1, 2, 2, 5, 5, 2, 3, 2, 3, 3)) |>
  fmt_number(decimals = from_column(column = "dec_digits")) |>
  cols_merge(columns = -name, pattern = "{1}, {2}") |>
  cols_label(
    name ~ "Municipality",
    latitude = "Location"
  )

Function ID

3-1

Function Introduced

v0.2.0.5 (March 31, 2020)

See Also

The integer-formatting function (format rounded values (i.e., no decimals shown and input values are rounded as necessary): fmt_integer().

The vector-formatting version of this function: vec_fmt_number()

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

gt documentation built on Sept. 11, 2024, 5:15 p.m.