Location helper for targeting group summary cells

The cells_summary() function is used to target the cells in a group summary and it is useful when applying a footnote with tab_footnote() or adding a custom style with tab_style(). The function is expressly used in each of those functions' locations argument.

cells_summary(groups = TRUE, columns = TRUE, rows = TRUE)

Arguments

groups	The names of the groups that the summary rows reside in.
columns	The names of the columns that are to be targeted.
rows	The names of the rows that are to be targeted.

Value

A list object with the classes cells_summary and location_cells.

Details

When using any of the location helper functions with an appropriate function that has a locations argument, multiple locations can be targeted by enclosing several cells_*() helper functions in a list(). The following helper functions can be used to target cells (roughly in order from the top to the bottom of a table):

• cells_title(): targets the table title or the table subtitle depending on the value given to the groups 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 the tab_stubhead() function.

• cells_column_spanners(): targets the spanner column labels, which appear above the column labels.

• cells_column_labels(): targets the column labels.

• cells_row_groups(): targets the row group labels in any available row groups using the groups argument.

• cells_stub(): targets row labels in the table stub using the rows argument.

• cells_body(): targets data cells in the table body using intersections of columns and rows.

• cells_summary(): targets summary cells in the table body using the groups argument and intersections of columns and rows.

• cells_grand_summary(): targets cells of the table's grand summary using intersections of columns and rows

Figures

Function ID

7-12

See also

Other Helper Functions: adjust_luminance(), cell_borders(), cell_fill(), cell_text(), cells_body(), cells_column_labels(), cells_column_spanners(), cells_grand_summary(), cells_row_groups(), cells_stubhead(), cells_stub(), cells_title(), currency(), escape_latex(), gt_latex_dependencies(), html(), md(), pct(), px(), random_id()

Examples

# Use `countrypops` to create a gt table; add
# some styling to the summary data cells with
# with `tab_style()`, using `cells_summary()`
# in `locations`
tab_1 <-
  countrypops %>%
  dplyr::filter(
    country_name == "Japan",
    year < 1970) %>%
  dplyr::select(-contains("country")) %>%
  dplyr::mutate(
    decade = paste0(substr(year, 1, 3), "0s")
  ) %>%
  dplyr::group_by(decade) %>%
  gt(
    rowname_col = "year",
    groupname_col = "decade"
  ) %>%
  fmt_number(
    columns = vars(population),
    decimals = 0
  ) %>%
  summary_rows(
    groups = "1960s",
    columns = vars(population),
    fns = list("min", "max"),
    formatter = fmt_number,
    decimals = 0
  ) %>%
  tab_style(
    style = list(
      cell_text(style = "italic"),
      cell_fill(color = "lightblue")
      ),
    locations = cells_summary(
      groups = "1960s",
      columns = vars(population),
      rows = 1)
  ) %>%
  tab_style(
    style = list(
      cell_text(style = "italic"),
      cell_fill(color = "lightgreen")
      ),
    locations = cells_summary(
      groups = "1960s",
      columns = vars(population),
      rows = 2)
  )