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>
// requiredThis 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()
andeverything()
).- rows
Rows to target
<row-targeting expression>
// default:everything()
In conjunction with
columns
, we can specify which of their rows should undergo formatting. The defaulteverything()
results in all rows incolumns
being formatted. Alternatively, we can supply a vector of row captions withinc()
, a vector of row indices, or a select helper function (e.g.starts_with()
,ends_with()
,contains()
,matches()
,num_range()
, andeverything()
). 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 with0
decimal places and it would result in"2"
. With4
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 viadecimals
. If opting to format according to the rules of significant figures,n_sigfig
must be a number greater than or equal to1
. Any values passed to thedecimals
anddrop_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
becomes23.
ifFALSE
). 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 tolocale
. This setting isTRUE
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 thedefault
value is1
, no values will be changed unless a different multiplier value is supplied. This value will be ignored if using any of thesuffixing
options (i.e., wheresuffixing
is not set toFALSE
).- 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 to1.92M
). This option can accept a logical value, whereFALSE
(the default) will not perform this transformation andTRUE
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 be 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., withc("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 asFALSE
) means that any value provided toscale_by
will be ignored.If using
system = "ind"
then the default suffix set provided bysuffixing = TRUE
will be the equivalent ofc(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 of1000
would result in a formatted value of"1,000"
. This argument is ignored if alocale
is supplied (i.e., is notNULL
).- dec_mark
Decimal mark
scalar<character>
// default:"."
The string to be used as the decimal mark. For example, using
dec_mark = ","
with the value0.152
would result in a formatted value of"0,152"
). This argument is ignored if alocale
is supplied (i.e., is notNULL
).- 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 isFALSE
, where only negative numbers will display a minus sign. This option is disregarded when using accounting notation withaccounting = 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 to the locale's rules. Examples include
"en"
for English (United States) and"fr"
for French (France). We can callinfo_locales()
for a useful reference for all of the locales that are supported. A locale ID can be also set in the initialgt()
function call (where it would be used automatically by any function with alocale
argument) but alocale
value provided here will override that global locale.
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.
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"
)
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()