fmt_bins | R Documentation |
When using the cut()
function (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 |
A table object that is created using the |
columns |
The columns to format. Can either be a series of column names
provided in |
rows |
Optional rows to format. Providing |
sep |
The separator text that indicates the values are ranged. The
default value of |
fmt |
Formatting expressions in formula form. The RHS of |
An object of class gt_tbl
.
The fmt_bins()
formatting function 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 the cut()
function in conjunction with the
scales::breaks_log()
function 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 the fmt_integer()
function (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
In Development
Other data formatting functions:
data_color()
,
fmt_auto()
,
fmt_bytes()
,
fmt_currency()
,
fmt_datetime()
,
fmt_date()
,
fmt_duration()
,
fmt_engineering()
,
fmt_flag()
,
fmt_fraction()
,
fmt_image()
,
fmt_index()
,
fmt_integer()
,
fmt_markdown()
,
fmt_number()
,
fmt_partsper()
,
fmt_passthrough()
,
fmt_percent()
,
fmt_roman()
,
fmt_scientific()
,
fmt_spelled_num()
,
fmt_time()
,
fmt_url()
,
fmt()
,
sub_large_vals()
,
sub_missing()
,
sub_small_vals()
,
sub_values()
,
sub_zero()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.