Format values to scientific notation

With numeric values in a gt table, we can perform formatting so that the targeted values are rendered in scientific notation, where extremely large or very small numbers can be expressed in a more practical fashion. Here, numbers are written in the form of a mantissa (m) and an exponent (n) with the construction m x 10^n or mEn. The mantissa component is a number between 1 and 10. For instance, 2.5 x 10^9 can be used to represent the value 2,500,000,000 in scientific notation. In a similar way, 0.00000012 can be expressed as 1.2 x 10^-7. Due to its ability to describe numbers more succinctly and its ease of calculation, scientific notation is widely employed in scientific and technical domains.

We have fine control over the formatting task, with the following options:

decimals: choice of the number of decimal places, option to drop trailing zeros, and a choice of the decimal symbol
scaling: we can choose to scale targeted values by a multiplier value
pattern: option to use a text pattern for decoration of the formatted values
locale-based formatting: providing a locale ID will result in formatting specific to the chosen locale

Usage

fmt_scientific(
  data,
  columns = everything(),
  rows = everything(),
  decimals = 2,
  n_sigfig = NULL,
  drop_trailing_zeros = FALSE,
  drop_trailing_dec_mark = TRUE,
  scale_by = 1,
  exp_style = "x10n",
  pattern = "{x}",
  sep_mark = ",",
  dec_mark = ".",
  force_sign_m = FALSE,
  force_sign_n = FALSE,
  locale = NULL
)

Arguments

data

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

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

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).

decimals

Number of decimal places

scalar<numeric|integer>(val>=0) // default: 2

This corresponds to the exact number of decimal places to use. A value such as 2.34 can, for example, be formatted with 0 decimal places and it would result in "2". With 4 decimal places, the formatted value becomes "2.3400". The trailing zeros can be removed with drop_trailing_zeros = TRUE. If you always need decimals = 0, the fmt_integer() function should be considered.

n_sigfig

Number of significant figures

scalar<numeric|integer>(val>=1) // default: NULL (optional)

A option to format numbers to n significant figures. By default, this is NULL and thus number values will be formatted according to the number of decimal places set via decimals. If opting to format according to the rules of significant figures, n_sigfig must be a number greater than or equal to 1. Any values passed to the decimals and drop_trailing_zeros arguments will be ignored.

drop_trailing_zeros

Drop any trailing zeros

scalar<logical> // default: FALSE

A logical value that allows for removal of trailing zeros (those redundant zeros after the decimal mark).

drop_trailing_dec_mark

Drop the trailing decimal mark

scalar<logical> // default: TRUE

A logical value that determines whether decimal marks should always appear even if there are no decimal digits to display after formatting (e.g., 23 becomes 23. if FALSE). By default trailing decimal marks are not shown.

scale_by

Scale values by a fixed multiplier

scalar<numeric|integer> // default: 1

All numeric values will be multiplied by the scale_by value before undergoing formatting. Since the default value is 1, no values will be changed unless a different multiplier value is supplied.

exp_style

Style declaration for exponent formatting

scalar<character> // default: "x10n"

Style of formatting to use for the scientific notation formatting. By default this is "x10n" but other options include using a single letter (e.g., "e", "E", etc.), a letter followed by a "1" to signal a minimum digit width of one, or "low-ten" for using a stylized "10" marker.

pattern

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.

sep_mark

Separator mark for digit grouping

scalar<character> // default: ","

The string to use as a separator between groups of digits. For example, using sep_mark = "," with a value of 1000 would result in a formatted value of "1,000". This argument is ignored if a locale is supplied (i.e., is not NULL).

dec_mark

Decimal mark

scalar<character> // default: "."

The string to be used as the decimal mark. For example, using dec_mark = "," with the value 0.152 would result in a formatted value of "0,152"). This argument is ignored if a locale is supplied (i.e., is not NULL).

force_sign_m, force_sign_n

Forcing the display of a positive sign

scalar<logical> // default: FALSE

Should the plus sign be shown for positive values of the mantissa (first component, force_sign_m) or the exponent (force_sign_n)? This would effectively show a sign for all values except zero on either of those numeric components of the notation. If so, use TRUE for either one of these options. The default for both is FALSE, where only negative numbers will display a sign.

locale

Locale identifier

scalar<character> // default: NULL (optional)

An optional locale identifier that can be used for formatting values according the locale's rules. Examples include "en" for English (United States) and "fr" for French (France). We can use the info_locales() function as a useful reference for all of the locales that are supported. A locale ID can be also set in the initial gt() function call (where it would be used automatically by any function with a locale argument) but a locale value provided here will override that global locale.

Value

An object of class gt_tbl.

Compatibility of formatting function with data values

The fmt_scientific() 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_scientific() 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():

decimals
drop_trailing_zeros
drop_trailing_dec_mark
scale_by
exp_style
pattern
sep_mark
dec_mark
force_sign_m
force_sign_n
locale

Please note that for all 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.

Adapting output to a specific `locale`

This formatting function can adapt outputs according to a provided locale value. Examples include "en" for English (United States) and "fr" for French (France). The use of a valid locale ID here means separator and decimal marks will be correct for the given locale. Should any values be provided in sep_mark or dec_mark, they will be overridden by the locale's preferred values.

Note that a locale value provided here will override any global locale setting performed in gt()'s own locale argument (it is settable there as a value received by all other functions that have a locale argument). As a useful reference on which locales are supported, we can use the info_locales() function to view an info table.

Examples

Let's use the exibble dataset to create a simple gt table. We'll elect to the num column as partially numeric and partially in scientific notation. This is done with two separate calls of fmt_number() and fmt_scientific(). We'll use the expressions num > 500 and num <= 500 in the functions' respective rows arguments to target formatting to specific cells.

exibble |>
  gt() |>
  fmt_number(
    columns = num,
    rows = num > 500,
    decimals = 1,
    scale_by = 1/1000,
    pattern = "{x}K"
  ) |>
  fmt_scientific(
    columns = num,
    rows = num <= 500,
    decimals = 1
  )

This image of a table was generated from the first code example in the `fmt_scientific()` help file.

The constants table contains a plethora of data on the fundamental physical constant and most values (in the units used) are either very small or very large, so scientific formatting is suitable. The values differ in the degree of measurement precision and separate columns (sf_value and sf_uncert) contain the exact number of significant figures for each measurement value and the associated uncertainty value. We can use the n_sigfig argument of fmt_scientific() in conjunction with the from_column() helper to get the correct number of significant digits for each value.

constants |>
  dplyr::filter(grepl("Planck", name)) |>
  gt() |>
  fmt_scientific(
    columns = value,
    n_sigfig = from_column(column = "sf_value")
  ) |>
  fmt_scientific(
    columns = uncert,
    n_sigfig = from_column(column = "sf_uncert")
  ) |>
  cols_hide(columns = starts_with("sf")) |>
  fmt_units(columns = units) |>
  sub_missing(missing_text = "")

This image of a table was generated from the second code example in the `fmt_scientific()` help file.

Function ID

3-3

Function Introduced

v0.2.0.5 (March 31, 2020)