While it is fairly straightforward to insert images into body cells (using
fmt_image()
is one way to it), there is often the need to incorporate
specialized types of graphics within a table. One such group of graphics
involves iconography representing different countries, and the fmt_flag()
function helps with inserting a flag icon (or multiple) in body cells. To
make this work seamlessly, the input cells need to contain some reference to
a country, and this is in the form of a 2-letter ISO 3166-1 country code
(e.g., Egypt has the "EG"
country code). This function will parse the
targeted body cells for those codes (and the countrypops dataset contains
all of them) and insert the appropriate flag graphics. Multiple flags can be
included per cell by separating country codes with commas (e.g., "GB,TT"
).
The sep
argument allows for a common separator to be applied between flag
icons.
Usage
fmt_flag(
data,
columns = everything(),
rows = everything(),
height = "1em",
sep = " ",
use_title = TRUE
)
Arguments
- data
The gt table data object
obj:<gt_tbl>
--- requiredThis 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 includestarts_with()
,ends_with()
,contains()
,matches()
,one_of()
,num_range()
, andeverything()
.- rows
Rows to target
<row-targeting expression>
--- default:everything()
In conjunction with
columns
, we can specify which of their rows should undergo formatting. The defaulteverything()
results in all rows incolumns
being formatted. Alternatively, we can supply a vector of row captions withinc()
, a vector of row indices, or a select helper function. Examples of select helper functions includestarts_with()
,ends_with()
,contains()
,matches()
,one_of()
,num_range()
, andeverything()
. We can also use expressions to filter down to the rows we need (e.g.,[colname_1] > 100 & [colname_2] < 50
).- height
Height of flag
scalar<character>
--- default:"1em"
The absolute height of the flag icon in the table cell. By default, this is set to
"1em"
.- sep
Separator between flags
scalar<character>
--- default:" "
In the output of flag icons within a body cell,
sep
provides the separator between each icon. By default, this is a single space character (" "
).- use_title
Display country name on hover
scalar<logical>
--- default:TRUE
An option to display a tooltip for the country name (in English) when hovering over the flag icon.
Compatibility of formatting function with data values
The fmt_flag()
formatting function is compatible with body cells that are
of the "character"
or "factor"
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 NA
s 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
Use the countrypops
dataset to create a gt table. We will only
include a few columns and rows from that table. The country_code_2
column
has 2-letter country codes in the format required for fmt_flag()
and using
that function transforms the codes in circular flag icons.
countrypops |>
dplyr::filter(year == 2021) |>
dplyr::filter(grepl("^S", country_name)) |>
dplyr::arrange(country_name) |>
dplyr::select(-country_code_3, -year) |>
dplyr::slice_head(n = 10) |>
gt() |>
cols_move_to_start(columns = country_code_2) |>
fmt_integer() |>
fmt_flag(columns = country_code_2) |>
cols_label(
country_code_2 = "",
country_name = "Country",
population = "Population (2021)"
)
Using countrypops
we can generate a table that provides populations
every five years for the Benelux countries ("BE"
, "NL"
, and "LU"
).
This requires some manipulation with dplyr and tidyr before
introducing the table to gt. With fmt_flag()
we can obtain flag icons
in the country_code_2
column. After that, we can merge the flag icons into
the stub column, generating row labels that have a combination of icon and
text.
countrypops |>
dplyr::filter(country_code_2 %in% c("BE", "NL", "LU")) |>
dplyr::filter(year %% 10 == 0) |>
dplyr::select(country_name, country_code_2, year, population) |>
tidyr::pivot_wider(names_from = year, values_from = population) |>
dplyr::slice(1, 3, 2) |>
gt(rowname_col = "country_name") |>
tab_header(title = "Populations of the Benelux Countries") |>
tab_spanner(columns = everything(), label = "Year") |>
fmt_integer() |>
fmt_flag(columns = country_code_2) |>
cols_merge(
columns = c(country_name, country_code_2),
pattern = "{2} {1}"
)
The fmt_flag()
function works well even when there are multiple country
codes within the same cell. It can operate on comma-separated codes without
issue. When rendered to HTML, hovering over each of the flag icons results in
tooltip text showing the name of the country.
countrypops |>
dplyr::filter(year == 2021, population < 100000) |>
dplyr::select(country_code_2, population) |>
dplyr::mutate(population_class = cut(
population,
breaks = scales::breaks_pretty(n = 5)(population)
)
) |>
dplyr::group_by(population_class) |>
dplyr::summarize(
countries = paste0(country_code_2, collapse = ",")
) |>
dplyr::arrange(desc(population_class)) |>
gt() |>
tab_header(title = "Countries with Small Populations") |>
fmt_flag(columns = countries) |>
fmt_bins(
columns = population_class,
fmt = ~ fmt_integer(., suffixing = TRUE)
) |>
cols_label(
population_class = "Population Range",
countries = "Countries"
) |>
cols_width(population_class ~ px(150))
See also
Other data formatting functions:
data_color()
,
fmt_auto()
,
fmt_bins()
,
fmt_bytes()
,
fmt_currency()
,
fmt_datetime()
,
fmt_date()
,
fmt_duration()
,
fmt_engineering()
,
fmt_fraction()
,
fmt_image()
,
fmt_index()
,
fmt_integer()
,
fmt_markdown()
,
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()