fmt_markdown: Format Markdown text

View source: R/format_data.R

fmt_markdownR Documentation

Format Markdown text

Description

Any Markdown-formatted text in the incoming cells will be transformed to the appropriate output type during render when using fmt_markdown().

Usage

fmt_markdown(
  data,
  columns = everything(),
  rows = everything(),
  md_engine = c("markdown", "commonmark")
)

Arguments

data

A table object that is created using the gt() function.

columns

The columns to format. Can either be a series of column names provided in c(), a vector of column indices, or a helper function focused on selections. The select helper functions are: starts_with(), ends_with(), contains(), matches(), one_of(), num_range(), and everything().

rows

Optional rows to format. Providing everything() (the default) results in all rows in columns being formatted. Alternatively, we can supply a vector of row captions within c(), a vector of row indices, or a helper function focused on selections. The select helper functions are: starts_with(), ends_with(), contains(), matches(), one_of(), 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).

md_engine

The engine preference for Markdown rendering. By default, this is set to "markdown" where gt will use the markdown package for Markdown conversion to HTML and LaTeX. The other option is "commonmark" and with that the commonmark package will be used.

Value

An object of class gt_tbl.

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).

By default all columns and rows are selected (with the everything() defaults). Cell values that are incompatible with a given formatting function will be skipped over, like character values and numeric ⁠fmt_*()⁠ functions. So it's safe to select all columns with a particular formatting function (only those values that can be formatted will be formatted), but, you may not want that. One strategy is to format the bulk of cell values with one formatting function and then constrain the columns for later passes with other types of formatting (the last formatting done to a cell is what you get in the final output).

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. This is nice if you want to base formatting on values in the column or another column, or, you'd like to use a more complex predicate expression.

Examples

Create a few Markdown-based text snippets.

text_1a <- "
### This is Markdown.

Markdown’s syntax is comprised entirely of
punctuation characters, which punctuation
characters have been carefully chosen so as
to look like what they mean... assuming
you’ve ever used email.
"

text_1b <- "
Info on Markdown syntax can be found
[here](https://daringfireball.net/projects/markdown/).
"

text_2a <- "
The **gt** package has these datasets:

 - `countrypops`
 - `sza`
 - `gtcars`
 - `sp500`
 - `pizzaplace`
 - `exibble`
"

text_2b <- "
There's a quick reference [here](https://commonmark.org/help/).
"

Arrange the text snippets as a tibble using the dplyr::tribble() function. then, create a gt table and format all columns with fmt_markdown().

dplyr::tribble(
  ~Markdown, ~md,
  text_1a,   text_2a,
  text_1b,   text_2b,
) |>
  gt() |>
  fmt_markdown(columns = everything()) |>
  tab_options(table.width = px(400))
This image of a table was generated from the first code example in the `fmt_markdown()` help file.

Function ID

3-21

Function Introduced

v0.2.0.5 (March 31, 2020)

See Also

The vector-formatting version of this function: vec_fmt_markdown().

Other data formatting functions: data_color(), fmt_auto(), fmt_bins(), fmt_bytes(), fmt_currency(), fmt_datetime(), fmt_date(), fmt_duration(), fmt_engineering(), fmt_flag(), fmt_fraction(), fmt_image(), fmt_index(), fmt_integer(), fmt_number(), fmt_partsper(), fmt_passthrough(), fmt_percent(), fmt_roman(), fmt_scientific(), fmt_spelled_num(), fmt_time(), fmt_url(), fmt(), sub_large_vals(), sub_missing(), sub_small_vals(), sub_values(), sub_zero()


gt documentation built on April 3, 2023, 5:18 p.m.