fmt_bins | R Documentation |
When using cut()
(or other functions that use it in some way)
you get bins that can look like this: "(0,10]"
, "(10,15]"
, "(15,20]"
,
"(20,40]"
. This interval notation expresses the lower and upper limits of
each range. The square or round brackets define whether each of the endpoints
are included in the range ([
/]
for inclusion, (
/)
for exclusion).
Should bins of this sort be present in a table, the fmt_bins()
function can
be used to format that syntax to a form that presents better in a display
table. It's possible to format the values of the intervals with the fmt
argument, and, the separator can be modified with the sep
argument.
fmt_bins(
data,
columns = everything(),
rows = everything(),
sep = "--",
fmt = 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 |
sep |
Separator between values
The separator text that indicates the values are ranged. The default value
of |
fmt |
Formatting expressions
An optional formatting expression in formula form. If used, the RHS of |
An object of class gt_tbl
.
fmt_bins()
is compatible with body cells that are of the "character"
or
"factor"
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.
fmt
We can supply a one-sided (RHS only) expression to fmt
, and, several can be
provided in a list. The expression uses a formatting function (e.g.,
fmt_number()
, fmt_currency()
, etc.) and it must contain an initial .
that stands for the data object. If performing numeric formatting it might
look something like this:
fmt = ~ fmt_number(., decimals = 1, use_seps = FALSE)
Use the countrypops
dataset to create a gt table. Before even getting
to the gt()
call, we use cut()
in conjunction with scales::breaks_log()
to create some highly customized bins. Consequently each country's population
in the 2021 year is assigned to a bin. These bins have a characteristic type
of formatting that can be used as input to fmt_bins()
, and using that
formatting function allows us to customize the presentation of those ranges.
For instance, here we are formatting the left and right values of the ranges
with fmt_integer()
(using formula syntax).
countrypops |> dplyr::filter(year == 2021) |> dplyr::select(country_code_2, population) |> dplyr::mutate(population_class = cut( population, breaks = scales::breaks_log(n = 20)(population) ) ) |> dplyr::group_by(population_class) |> dplyr::summarize( count = dplyr::n(), countries = paste0(country_code_2, collapse = ",") ) |> dplyr::arrange(desc(population_class)) |> gt() |> fmt_flag(columns = countries) |> fmt_bins( columns = population_class, fmt = ~ fmt_integer(., suffixing = TRUE) ) |> cols_label( population_class = "Population Range", count = "", countries = "Countries" ) |> cols_width( population_class ~ px(150), count ~ px(50) ) |> tab_style( style = cell_text(style = "italic"), locations = cells_body(columns = count) )
3-17
v0.9.0
(Mar 31, 2023)
Other data formatting functions:
data_color()
,
fmt()
,
fmt_auto()
,
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_spelled_num()
,
fmt_tf()
,
fmt_time()
,
fmt_units()
,
fmt_url()
,
sub_large_vals()
,
sub_missing()
,
sub_small_vals()
,
sub_values()
,
sub_zero()
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