The cells_body()
function is used to target the data cells in the table
body. The function can be used to apply a footnote with tab_footnote()
, to
add custom styling with tab_style()
, or the transform the targeted cells
with text_transform()
. The function is expressly used in each of those
functions' locations
argument. The 'body' location is present by default in
every gt table.
Usage
cells_body(columns = everything(), rows = everything())
Arguments
- columns
Columns to target
<column-targeting expression>
// default:everything()
The columns to which targeting 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
).
Overview of location helper functions
Location helper functions can be used to target cells with virtually any
function that has a locations
argument. Here is a listing of all of the
location helper functions, with locations corresponding roughly from top to
bottom of a table:
cells_title()
: targets the table title or the table subtitle depending on the value given to thegroups
argument ("title"
or"subtitle"
).cells_stubhead()
: targets the stubhead location, a cell of which is only available when there is a stub; a label in that location can be created by using thetab_stubhead()
function.cells_column_spanners()
: targets the spanner column labels with thespanners
argument; spanner column labels appear above the column labels.cells_column_labels()
: targets the column labels with itscolumns
argument.cells_row_groups()
: targets the row group labels in any available row groups using thegroups
argument.cells_stub()
: targets row labels in the table stub using therows
argument.cells_body()
: targets data cells in the table body using intersections ofcolumns
androws
.cells_summary()
: targets summary cells in the table body using thegroups
argument and intersections ofcolumns
androws
.cells_grand_summary()
: targets cells of the table's grand summary using intersections ofcolumns
androws
cells_stub_summary()
: targets summary row labels in the table stub using thegroups
androws
arguments.cells_stub_grand_summary()
: targets grand summary row labels in the table stub using therows
argument.cells_footnotes()
: targets all footnotes in the table footer (cannot be used withtab_footnote()
).cells_source_notes()
: targets all source notes in the table footer (cannot be used withtab_footnote()
).
When using any of the location helper functions with an appropriate function
that has a locations
argument (e.g., tab_style()
), multiple locations
can be targeted by enclosing several cells_*()
helper functions in a
list()
(e.g., list(cells_body(), cells_grand_summary())
).
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).
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.
Examples
Let's use a subset of the gtcars
dataset to create a gt table. Add a
footnote (with tab_footnote()
) that targets a single data cell via the use
of cells_body()
in locations
(rows = hp == max(hp)
will target a single
row in the hp
column).
gtcars |>
dplyr::filter(ctry_origin == "United Kingdom") |>
dplyr::select(mfr, model, year, hp) |>
gt() |>
tab_footnote(
footnote = "Highest horsepower.",
locations = cells_body(
columns = hp,
rows = hp == max(hp)
),
placement = "right"
) |>
opt_footnote_marks(marks = c("*", "+"))
See also
Other helper functions:
adjust_luminance()
,
cell_borders()
,
cell_fill()
,
cell_text()
,
cells_column_labels()
,
cells_column_spanners()
,
cells_footnotes()
,
cells_grand_summary()
,
cells_row_groups()
,
cells_source_notes()
,
cells_stub()
,
cells_stub_grand_summary()
,
cells_stub_summary()
,
cells_stubhead()
,
cells_summary()
,
cells_title()
,
currency()
,
default_fonts()
,
escape_latex()
,
from_column()
,
google_font()
,
gt_latex_dependencies()
,
html()
,
md()
,
nanoplot_options()
,
pct()
,
px()
,
random_id()
,
stub()
,
system_fonts()