Location helper for targeting cells in a grand summary

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(), and everything()).

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 default everything() results in all rows in columns being formatted. Alternatively, we can supply a vector of row IDs within c(), a vector of row indices, or a select helper function (e.g. starts_with(), ends_with(), contains(), matches(), num_range(), and everything()). We can also use expressions to filter down to the rows we need (e.g., [colname_1] > 100 & [colname_2] < 50).

Value

A list object with the classes cells_grand_summary and location_cells.

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
    )
  )

Function ID

8-20

Function Introduced

v0.2.0.5 (March 31, 2020)

See also