cells_grand_summary() is used to target the cells in a grand
summary and it is useful when applying a footnote with tab_footnote() or
adding custom styles with tab_style(). The function is expressly used in
each of those functions' locations argument. The 'grand_summary' location
is generated by grand_summary_rows().
Usage
cells_grand_summary(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 (e.g.starts_with(),ends_with(),contains(),matches(),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 incolumnsbeing formatted. Alternatively, we can supply a vector of row IDs withinc(), a vector of row indices, or a select helper function (e.g.starts_with(),ends_with(),contains(),matches(),num_range(), andeverything()). We can also use expressions to filter down to the rows we need (e.g.,[colname_1] > 100 & [colname_2] < 50).
Targeting cells with columns and rows
Targeting of grand summary cells is done through the columns and rows
arguments. The columns argument allows us to target a subset of grand
summary 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 NAs from consideration).
Once the columns are targeted, we may also target the rows of the grand
summary. Grand summary cells in the stub will have ID values that 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)) that correspond to the row number of a
grand summary row.
Examples
Use a portion of the countrypops dataset to create a gt table. Add
some styling to a grand summary cells with tab_style() and
cells_grand_summary() in the locations argument.
countrypops |>
dplyr::filter(country_name == "Spain", year < 1970) |>
dplyr::select(-contains("country")) |>
gt(rowname_col = "year") |>
fmt_number(
columns = population,
decimals = 0
) |>
grand_summary_rows(
columns = population,
fns = change ~ max(.) - min(.),
fmt = ~ fmt_integer(.)
) |>
tab_style(
style = list(
cell_text(style = "italic"),
cell_fill(color = "lightblue")
),
locations = cells_grand_summary(
columns = population,
rows = 1
)
)
See also
Other location helper functions:
cells_body(),
cells_column_labels(),
cells_column_spanners(),
cells_footnotes(),
cells_row_groups(),
cells_source_notes(),
cells_stub(),
cells_stub_grand_summary(),
cells_stub_summary(),
cells_stubhead(),
cells_summary(),
cells_title(),
location-helper