cells_body: Location helper for targeting data cells in the table body

In gt: Easily Create Presentation-Ready Display Tables

Location helper for targeting data cells in the table body

Description

cells_body() 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 (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_body and location_cells.

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 NAs 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("*", "+"))

Function ID

8-18

Function Introduced

v0.2.0.5 (March 31, 2020)

See Also

Other location helper functions: 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(), location-helper

gt documentation built on April 12, 2025, 1:26 a.m.