fmt_flag {gt} | R Documentation |
Generate flag icons for countries from their country codes
Description
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
This is the gt table object that is commonly created through use of the
|
columns |
Columns to target
Can either be a series of column names provided in |
rows |
Rows to target
In conjunction with |
height |
Height of flag
The absolute height of the flag icon in the table cell. By default, this is
set to |
sep |
Separator between flags
In the output of flag icons within a body cell, |
use_title |
Display country name on hover
An option to display a tooltip for the country name (in English) when hovering over the flag icon. |
Value
An object of class gt_tbl
.
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.
Compatibility of arguments with the from_column()
helper function
The from_column()
helper function can be used with certain arguments of
fmt_flag()
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()
:
-
height
-
sep
-
use_title
Please note that for each 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.
Flag icons that can be used
You can view the entire set of supported flag icons as an informative table
by using the info_flags()
function. In the information table that is
provided, you'll see every flag icon and the associated identifier that can
be used with fmt_flag()
.
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))
Function ID
3-21
Function Introduced
v0.9.0
(Mar 31, 2023)
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_icon()
,
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_units()
,
fmt_url()
,
fmt()
,
sub_large_vals()
,
sub_missing()
,
sub_small_vals()
,
sub_values()
,
sub_zero()