## Example

With icon_sets(), you can conditionally format values using icons from Font Awesome.

When icon_sets() is placed within the cell argument of colDef, circle icons are added to each of the values in the each column and are colored from blue, grey, to orange from smallest values to largest values.

data <- sample_n(penguins, 50) %>%
filter(!is.na(bill_length_mm)) %>%
select(species, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g)

reactable(
data,
defaultColDef = colDef(
cell = icon_sets(data)
)
)

## Using Icons from Font Awesome

icon_sets() accepts any free icon available from the Font Awesome icon gallery. For example, since the data we’re displaying is bill and flipper measurements of penguins, we may want to use ruler icons from Font Awesome to visually show this.

We can also apply multiple icons to a column. For example, we can assign balance scale icons that lean to the left or right for the lightest and heaviest penguins:

reactable(
data,
columns = list(
bill_length_mm = colDef(cell = icon_sets(data, icons = c("ruler"))),
bill_depth_mm = colDef(cell = icon_sets(data, icons = c("ruler-vertical"))),
flipper_length_mm = colDef(cell = icon_sets(data, icons = c("ruler-horizontal"))),
body_mass_g = colDef(cell = icon_sets(data, icons = c("balance-scale-left", "balance-scale", "balance-scale-right")))
)
)

## Icon Colors

The number of colors used in icon_sets() determines how the values from low to high are assigned.

The default number of colors used in icon_sets() is three. Therefore, the data is split into three groups: low, medium, and high.

If only one color is provided, the values will all be assigned the same color. If two colors are provided, the first color will represent the lower 50% of the values and the second color will represent the upper 50% of the values. If four colors are provided, the first color will represent the lowest 25%, the next color will represent values between 25-50%, and so on.

You can use as many colors as you would like and icon_sets() will automatically assign the colors from low to high.

library(viridis)

reactable(
data,
defaultColDef = colDef(
cell = icon_sets(data, colors = viridis::viridis(5))
)
)

The opacity of the colors can be controlled by assigning a value between 0 (fully transparent) and 1 (fully opaque).

library(viridis)

reactable(
data,
defaultColDef = colDef(
cell = icon_sets(data, opacity = 0.5, colors = viridis::viridis(5))
)
)

## Icon Positioning

The icons can be positioned in five different ways relative to the values in the cells: left, right, above, below, or over (which hides the values).

The default icon position is to the right of the values, but can easily be changed to any of the other available positions like so:

reactable(
data,
defaultColDef = colDef(
align = "center",
cell = icon_sets(data, icon_position = "left")
)
)
reactable(
data,
defaultColDef = colDef(
align = "center",
cell = icon_sets(data, icon_position = "above")
)
)
reactable(
data,
defaultColDef = colDef(
align = "center",
cell = icon_sets(data, icon_position = "below")
)
)
reactable(
data,
defaultColDef = colDef(
align = "center",
cell = icon_sets(data, icon_position = "over")
)
)

## Adjusting the Size of the Icons

The size of the icons can be adjusted by providing a numeric value within icon_size. The default icon size represented in px is 16.

car_data <- MASS::Cars93 %>%
filter(Type %in% c("Compact", "Sporty", "Van")) %>%
select(c("Make", "Type", "MPG.city", "MPG.highway")) %>%

reactable(
car_data,
defaultColDef = colDef(
align = "center",
cell = icon_sets(car_data, icon_size = 28, icons = "gas-pump", colors = c("red", "grey", "darkgreen"))
)
)

## Assigning Icons from Another Column

Icons can be conditionally assigned to text/values from another column using icon_ref within icon_sets().

One method of creating the column containing the icon references is by using dplyr::case_when() to assign icons within a created column. Once that column exists in the dataset, it simply can be referenced within icon_ref as shown below within the Type column.

car_types <- car_data %>%
mutate(car_icons = dplyr::case_when(
Type == "Compact" ~ "car",
Type == "Sporty" ~ "flag-checkered",
Type == "Van" ~ "shuttle-van",
TRUE ~ "other"
))

car_types %>%
reactable(
.,
defaultSorted = "Type",
defaultColDef = colDef(
align = "center",
cell = icon_sets(., icon_size = 28, icons = "gas-pump", colors = c("red", "grey", "darkgreen"))
),
columns = list(
car_icons = colDef(show = FALSE),
Type = colDef(
align = "right",
cell = icon_sets(., icon_ref = "car_icons", icon_size = 28, colors = "black")
)
)
)

You also have the option of hiding the text next to the icons by including icon_position = "over":

car_types %>%
reactable(
.,
defaultSorted = "Type",
defaultColDef = colDef(
align = "center",
cell = icon_sets(., icon_size = 28, icons = "gas-pump", colors = c("red", "grey", "darkgreen"))
),
columns = list(
car_icons = colDef(show = FALSE),
Type = colDef(
cell = icon_sets(., icon_ref = "car_icons", icon_position = "over", icon_size = 28, colors = "black")
)
)
)

## Assigning Icon Colors from Another Column

Now that we have icons assigned to the type of vehicle, we can also assign colors from another column with icon_color_ref using the same approach as icon_ref, but instead of conditionally assigning icons, we assign colors:

car_types <- car_types %>%
mutate(car_colors = dplyr::case_when(
Type == "Compact" ~ "dodgerblue",
Type == "Sporty" ~ "black",
Type == "Van" ~ "gold",
TRUE ~ "other"
))

car_types %>%
reactable(
.,
defaultSorted = "Type",
defaultColDef = colDef(
align = "center",
cell = icon_sets(., icon_size = 28, icons = "gas-pump", colors = c("red", "grey", "darkgreen"))
),
columns = list(
car_colors = colDef(show = FALSE),
car_icons = colDef(show = FALSE),
Type = colDef(
cell = icon_sets(., icon_color_ref = "car_colors", icon_ref = "car_icons", icon_position = "over", icon_size = 28, colors = "black")
)
)
)