With numeric values in a gt table, we can perform percentage-based
formatting. It is assumed the input numeric values are in a fractional format
since the numbers will be automatically multiplied by 100
before decorating
with a percent sign. For more control over percentage formatting, we can use
the following options:
percent sign placement: the percent sign can be placed after or before the values and a space can be inserted between the symbol and the value.
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
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
fmt_percent(
data,
columns,
rows = NULL,
decimals = 2,
drop_trailing_zeros = FALSE,
use_seps = TRUE,
pattern = "{x}",
sep_mark = ",",
dec_mark = ".",
incl_space = FALSE,
placement = "right",
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 vars()
, 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()
, and everything()
.
Optional rows to format. Not providing any value results in all
rows in columns
being formatted. Can either be a vector of row captions
provided 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()
, and everything()
.
We can also use expressions to filter down to the rows we need (e.g.,
[colname_1] > 100 & [colname_2] < 50
).
An option to specify the exact number of decimal places to
use. The default number of decimal places is 2
.
A logical value that allows for removal of trailing zeros (those redundant zeros after the decimal mark).
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.
A formatting pattern that allows for decoration of the
formatted value. The value itself is represented by {x}
and all other
characters are taken to be string literals.
The mark to use as a separator between groups of digits
(e.g., using sep_mark = ","
with 1000
would result in a formatted value
of 1,000
).
The character to use as a decimal mark (e.g., using dec_mark = ","
with 0.152
would result in a formatted value of 0,152
).
An option for whether to include a space between the value and the percent sign. The default is to not introduce a space character.
The placement of the percent sign. This can be either be
right
(the default) or left
.
An optional locale ID that can be used for formatting the value
according the locale's rules. Examples include "en_US"
for English
(United States) and "fr_FR"
for French (France). The use of a valid
locale ID will override any values provided in sep_mark
and dec_mark
.
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
.
3-3
Targeting of values is done through columns
and additionally by rows
(if
nothing is provided for rows
then entire columns are selected). A number of
helper functions exist to make targeting more effective. Conditional
formatting is possible by providing a conditional expression to the rows
argument. See the Arguments section for more information on this.
Other Format Data:
data_color()
,
fmt_currency()
,
fmt_datetime()
,
fmt_date()
,
fmt_markdown()
,
fmt_missing()
,
fmt_number()
,
fmt_passthrough()
,
fmt_scientific()
,
fmt_time()
,
fmt()
,
text_transform()
# NOT RUN {
# Use `pizzaplace` to create a gt table;
# format the `frac_of_quota` column to
# display values as percentages
tab_1 <-
pizzaplace %>%
dplyr::mutate(month = as.numeric(substr(date, 6, 7))) %>%
dplyr::group_by(month) %>%
dplyr::summarize(pizzas_sold = n()) %>%
dplyr::ungroup() %>%
dplyr::mutate(frac_of_quota = pizzas_sold / 4000) %>%
gt(rowname_col = "month") %>%
fmt_percent(
columns = vars(frac_of_quota),
decimals = 1
)
# }
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