Any Markdown-formatted text in the incoming cells will be transformed to the
appropriate output type during render when using
fmt_markdown( data, columns = everything(), rows = everything(), md_engine = c("markdown", "commonmark") )
A table object that is created using the
The columns to format. Can either be a series of column names
Optional rows to format. Providing
The engine preference for Markdown rendering. By default,
this is set to
An object of class
Targeting of values is done through
columns and additionally by
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
c() (with bare column names or names in quotes) we can use
tidyselect-style expressions. This can be as basic as supplying a select
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
defaults). Cell values that are incompatible with a given formatting function
will be skipped over, like
character values and numeric
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
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.
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
then, create a gt table and format all columns with
dplyr::tribble( ~Markdown, ~md, text_1a, text_2a, text_1b, text_2b, ) |> gt() |> fmt_markdown(columns = everything()) |> tab_options(table.width = px(400))
v0.2.0.5 (March 31, 2020)
The vector-formatting version of this function:
Other data formatting functions:
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