fmt_spelled_num | R Documentation |
With numeric values in a gt table we can transform those to numbers that
are spelled out with fmt_spelled_num()
. Any values from 0
to 100
can be
spelled out so, for example, the value 23
will be formatted as "twenty-three"
.
Providing a locale ID will result in the number spelled out in the locale's
language rules. For example, should a Swedish locale ("sv"
) be provided,
the value 23
will yield "tjugotre"
. In addition to this, we can
optionally use the pattern
argument for decoration of the formatted values.
fmt_spelled_num(
data,
columns = everything(),
rows = everything(),
pattern = "{x}",
locale = NULL
)
data |
The gt table data object
This is the gt table object that is commonly created through use of the
|
columns |
Columns to target
Can either be a series of column names provided in |
rows |
Rows to target
In conjunction with |
pattern |
Specification of the formatting pattern
A formatting pattern that allows for decoration of the formatted value. The
formatted value is represented by the |
locale |
Locale identifier
An optional locale identifier that can be used for formatting values
according the locale's rules. Examples include |
An object of class gt_tbl
.
fmt_spelled_num()
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.
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 NA
s 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.
from_column()
helper functionfrom_column()
can be used with certain arguments of fmt_spelled_num()
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()
:
pattern
locale
Please note that for both 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.
The following 80 locales are supported in the locale
argument of
fmt_spelled_num()
: "af"
(Afrikaans), "ak"
(Akan), "am"
(Amharic),
"ar"
(Arabic), "az"
(Azerbaijani), "be"
(Belarusian), "bg"
(Bulgarian), "bs"
(Bosnian), "ca"
(Catalan), "ccp"
(Chakma), "chr"
(Cherokee), "cs"
(Czech), "cy"
(Welsh), "da"
(Danish), "de"
(German),
"de-CH"
(German (Switzerland)), "ee"
(Ewe), "el"
(Greek), "en"
(English), "eo"
(Esperanto), "es"
(Spanish), "et"
(Estonian), "fa"
(Persian), "ff"
(Fulah), "fi"
(Finnish), "fil"
(Filipino), "fo"
(Faroese), "fr"
(French), "fr-BE"
(French (Belgium)), "fr-CH"
(French
(Switzerland)), "ga"
(Irish), "he"
(Hebrew), "hi"
(Hindi), "hr"
(Croatian), "hu"
(Hungarian), "hy"
(Armenian), "id"
(Indonesian),
"is"
(Icelandic), "it"
(Italian), "ja"
(Japanese), "ka"
(Georgian),
"kk"
(Kazakh), "kl"
(Kalaallisut), "km"
(Khmer), "ko"
(Korean),
"ky"
(Kyrgyz), "lb"
(Luxembourgish), "lo"
(Lao), "lrc"
(Northern
Luri), "lt"
(Lithuanian), "lv"
(Latvian), "mk"
(Macedonian), "ms"
(Malay), "mt"
(Maltese), "my"
(Burmese), "ne"
(Nepali), "nl"
(Dutch),
"nn"
(Norwegian Nynorsk), "no"
(Norwegian), "pl"
(Polish), "pt"
(Portuguese), "qu"
(Quechua), "ro"
(Romanian), "ru"
(Russian), "se"
(Northern Sami), "sk"
(Slovak), "sl"
(Slovenian), "sq"
(Albanian),
"sr"
(Serbian), "sr-Latn"
(Serbian (Latin)), "su"
(Sundanese), "sv"
(Swedish), "sw"
(Swahili), "ta"
(Tamil), "th"
(Thai), "tr"
(Turkish),
"uk"
(Ukrainian), "vi"
(Vietnamese), "yue"
(Cantonese), and "zh"
(Chinese).
Let's use a summarized version of the gtcars
dataset to create a
gt table. fmt_spelled_num()
is used to transform
integer values into spelled-out numbering (in the n
column). That formatted
column of numbers-as-words is given cell background colors via data_color()
(the underlying numerical values are always available).
gtcars |> dplyr::count(mfr, ctry_origin) |> dplyr::arrange(ctry_origin) |> gt(rowname_col = "mfr", groupname_col = "ctry_origin") |> cols_label(n = "No. of Entries") |> fmt_spelled_num() |> tab_stub_indent(rows = everything(), indent = 2) |> data_color( columns = n, method = "numeric", palette = "viridis", alpha = 0.8 ) |> opt_all_caps() |> opt_vertical_padding(scale = 0.5) |> cols_align(align = "center", columns = n)
With a considerable amount of dplyr and tidyr work done to the
pizzaplace
dataset, we can create a new gt table. fmt_spelled_num()
will be used here to transform the integer values in the rank
column.
We'll do so with a special pattern
that puts the word 'Number' in front of
every spelled-out number.
pizzaplace |> dplyr::mutate(month = lubridate::month(date, label = TRUE)) |> dplyr::filter(month %in% month.abb[1:6]) |> dplyr::group_by(name, month) |> dplyr::summarize(sum = sum(price), .groups = "drop") |> dplyr::arrange(month, desc(sum)) |> dplyr::group_by(month) |> dplyr::slice_head(n = 5) |> dplyr::mutate(rank = dplyr::row_number()) |> dplyr::ungroup() |> dplyr::select(-sum) |> tidyr::pivot_wider(names_from = month, values_from = c(name)) |> gt() |> fmt_spelled_num(columns = rank, pattern = "Number {x}") |> opt_all_caps() |> cols_align(columns = -rank, align = "center") |> cols_width( rank ~ px(120), everything() ~ px(100) ) |> opt_table_font(stack = "rounded-sans") |> tab_options(table.font.size = px(14))
Let's make a table that compares how the numbers from 1
to 10
are spelled
across a small selection of languages. Here we use fmt_spelled_num()
with
each column, ensuring that the locale
value matches that of the column
name.
dplyr::tibble( num = 1:10, en = num, fr = num, de = num, es = num, pl = num, bg = num, ko = num, zh = num ) |> gt(rowname_col = "num") |> fmt_spelled_num(columns = en, locale = "en") |> fmt_spelled_num(columns = fr, locale = "fr") |> fmt_spelled_num(columns = de, locale = "de") |> fmt_spelled_num(columns = es, locale = "es") |> fmt_spelled_num(columns = pl, locale = "pl") |> fmt_spelled_num(columns = bg, locale = "bg") |> fmt_spelled_num(columns = ko, locale = "ko") |> fmt_spelled_num(columns = zh, locale = "zh") |> cols_label_with(fn = function(x) md(paste0("`", x, "`"))) |> tab_spanner( label = "Numbers in the specified locale", columns = everything() ) |> cols_align(align = "left", columns = everything()) |> cols_width( c(en, fr, de, es, pl, bg) ~ px(100), c(ko, zh) ~ px(50) ) |> opt_horizontal_padding(scale = 2) |> opt_vertical_padding(scale = 0.5)
3-11
v0.9.0
(Mar 31, 2023)
The vector-formatting version of this function:
vec_fmt_spelled_num()
.
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_number()
,
fmt_partsper()
,
fmt_passthrough()
,
fmt_percent()
,
fmt_roman()
,
fmt_scientific()
,
fmt_tf()
,
fmt_time()
,
fmt_units()
,
fmt_url()
,
sub_large_vals()
,
sub_missing()
,
sub_small_vals()
,
sub_values()
,
sub_zero()
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