fmt_roman: Format values as Roman numerals

View source: R/format_data.R

fmt_romanR Documentation

Format values as Roman numerals


With numeric values in a gt table we can transform those to Roman numerals, rounding values as necessary.


  columns = everything(),
  rows = everything(),
  case = c("upper", "lower"),
  pattern = "{x}"



The gt table data object

⁠obj:<gt_tbl>⁠ // required

This is the gt table object that is commonly created through use of the gt() function.


Columns to target

⁠<column-targeting expression>⁠ // default: everything()

Can either be a series of column names provided in c(), a vector of column indices, or a select helper function. Examples of select helper functions include starts_with(), ends_with(), contains(), matches(), one_of(), num_range(), and everything().


Rows to target

⁠<row-targeting expression>⁠ // default: everything()

In conjunction with columns, we can specify which of their rows should undergo formatting. The default everything() 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 select helper function. Examples of select helper functions include 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).


Use uppercase or lowercase letters

⁠singl-kw:[upper|lower]⁠ // default: "upper"

Should Roman numerals should be rendered as uppercase ("upper") or lowercase ("lower") letters? By default, this is set to "upper".


Specification of the formatting pattern

⁠scalar<character>⁠ // default: "{x}"

A formatting pattern that allows for decoration of the formatted value. The formatted value is represented by the {x} (which can be used multiple times, if needed) and all other characters will be interpreted as string literals.


An object of class gt_tbl.

Compatibility of formatting function with data values

The fmt_roman() formatting function is compatible with body cells that are of the "numeric" or "integer" types. Any other types of body cells are ignored during formatting. This is to say that cells of incompatible data types may be targeted, but there will be no attempt to format them.

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.

Compatibility of arguments with the from_column() helper function

The from_column() helper function can be used with certain arguments of fmt_roman() to obtain varying parameter values from a specified column within the table. This means that each row could be formatted a little bit differently. These arguments provide support for from_column():

  • case

  • pattern

Please note that for both of the aforementioned arguments, a from_column() call needs to reference a column that has data of the correct type (this is different for each argument). Additional columns for parameter values can be generated with the cols_add() function (if not already present). Columns that contain parameter data can also be hidden from final display with cols_hide(). Finally, there is no limitation to how many arguments the from_column() helper is applied so long as the arguments belong to this closed set.


Create a tibble of small numeric values and generate a gt table. Format the roman column to appear as Roman numerals with fmt_roman().

dplyr::tibble(arabic = c(1, 8, 24, 85), roman = arabic) |>
  gt(rowname_col = "arabic") |>
  fmt_roman(columns = roman)
This image of a table was generated from the first code example in the `fmt_roman()` help file.

Formatting values to Roman numerals can be very useful when combining such output with row labels (usually through cols_merge()). Here's an example where we take a portion of the illness dataset and generate some row labels that combine (1) a row number (in lowercase Roman numerals), (2) the name of the test, and (3) the measurement units for the test (nicely formatted by way of fmt_units()):

illness |>
  dplyr::slice_head(n = 6) |>
  gt(rowname_col = "test") |>
  fmt_units(columns = units) |>
  cols_hide(columns = starts_with("day")) |>
  sub_missing(missing_text = "") |>
  cols_merge_range(col_begin = norm_l, col_end = norm_u) |>
  cols_add(i = 1:6) |>
  fmt_roman(columns = i, case = "lower", pattern = "{x}.") |>
  cols_merge(columns = c(test, i, units), pattern = "{2} {1} ({3})") |>
  cols_label(norm_l = "Normal Range") |>
  tab_stubhead(label = "Test")
This image of a table was generated from the second code example in the `fmt_roman()` help file.

Function ID


Function Introduced

v0.8.0 (November 16, 2022)

See Also

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

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_icon(), fmt_image(), fmt_index(), fmt_integer(), fmt_markdown(), fmt_number(), fmt_partsper(), fmt_passthrough(), fmt_percent(), fmt_scientific(), fmt_spelled_num(), fmt_time(), fmt_units(), fmt_url(), fmt(), sub_large_vals(), sub_missing(), sub_small_vals(), sub_values(), sub_zero()

gt documentation built on June 22, 2024, 11:11 a.m.