Wherever there is numerical data that are zero in value, replacement text may
be better for explanatory purposes. The sub_zero()
function allows for this
replacement through its zero_text
argument.
Usage
sub_zero(data, columns = everything(), rows = everything(), zero_text = "nil")
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()
The columns to which substitution operations are constrained. Can either be a series of column names provided in
c()
, a vector of column indices, or a select helper function. Examples of select helper functions includestarts_with()
,ends_with()
,contains()
,matches()
,one_of()
,num_range()
, andeverything()
.- rows
Rows to target
<row-targeting expression>
// default:everything()
In conjunction with
columns
, we can specify which of their rows should form a constraint for targeting operations. The defaulteverything()
results in all rows incolumns
being formatted. Alternatively, we can supply a vector of row IDs withinc()
, a vector of row indices, or a select helper function. Examples of select helper functions includestarts_with()
,ends_with()
,contains()
,matches()
,one_of()
,num_range()
, andeverything()
. We can also use expressions to filter down to the rows we need (e.g.,[colname_1] > 100 & [colname_2] < 50
).- zero_text
Replacement text for zero values
scalar<character>
// default:"nil"
The text to be used in place of zero values in the rendered table. We can optionally use the
md()
andhtml()
functions to style the text as Markdown or to retain HTML elements in the text.
Targeting cells with 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 substitution
function will be skipped over. So it's safe to select all columns with a
particular substitution function (only those values that can be substituted
will be), but, you may not want that. One strategy is to work on the bulk of
cell values with one substitution function and then constrain the columns for
later passes with other types of substitution (the last operation 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
the substitution on values in the column or another column, or, you'd like to
use a more complex predicate expression.
Examples
Let's generate a simple, single-column tibble that contains an assortment of values that could potentially undergo some substitution.
tbl <- dplyr::tibble(num = c(10^(-1:2), 0, 0, 10^(4:6)))
tbl
#> # A tibble: 9 x 1
#> num
#> <dbl>
#> 1 0.1
#> 2 1
#> 3 10
#> 4 100
#> 5 0
#> 6 0
#> 7 10000
#> 8 100000
#> 9 1000000
With this table, the zero values in will be given replacement text with a
single call of sub_zero()
.
tbl |>
gt() |>
fmt_number(columns = num) |>
sub_zero()
See also
Other data formatting functions:
data_color()
,
fmt()
,
fmt_auto()
,
fmt_bins()
,
fmt_bytes()
,
fmt_currency()
,
fmt_date()
,
fmt_datetime()
,
fmt_duration()
,
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_time()
,
fmt_units()
,
fmt_url()
,
sub_large_vals()
,
sub_missing()
,
sub_small_vals()
,
sub_values()