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Basic Usage

To create a data table, use reactable() on a data frame or matrix. The table will be sortable and paginated by default:

Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
4.6
3.4
1.4
0.3
setosa
5
3.4
1.5
0.2
setosa
4.4
2.9
1.4
0.2
setosa
4.9
3.1
1.5
0.1
setosa
1–10 of 150 rows
...

Column definitions

Columns can be customized by providing a named list of column definitions created by colDef() to columns:

reactable(
  iris[1:5, ],
  columns = list(
    Sepal.Length = colDef(name = "Sepal Length"),
    Sepal.Width = colDef(name = "Sepal Width"),
    Species = colDef(align = "center")
  )
)
Sepal Length
Sepal Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

For convenience, you can also specify a default colDef() to use for all columns in defaultColDef:

reactable(
  iris[1:5, ],
  defaultColDef = colDef(
    header = function(value) gsub(".", " ", value, fixed = TRUE),
    cell = function(value) format(value, nsmall = 1),
    align = "center",
    minWidth = 70,
    headerStyle = list(background = "#f7f7f8")
  ),
  columns = list(
    Species = colDef(minWidth = 140)  # overrides the default
  ),
  bordered = TRUE,
  highlight = TRUE
)
Sepal Length
Sepal Width
Petal Length
Petal Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3.0
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5.0
3.6
1.4
0.2
setosa

Sorting

Tables are sortable by default. You can sort a column by clicking on its header, or sort multiple columns by holding the shift key while sorting.

Sorting toggles between ascending and descending order by default. To clear the sort, hold the shift key while sorting, and the sorting will additionally toggle between ascending, descending, and unsorted order.

Note: Ascending order means the lowest, first, or earliest values will appear first. Descending order means the largest, last, or latest values will appear first.

Default sorted columns

You can set the default sorted columns by providing a vector of column names to defaultSorted:

reactable(iris[48:52, ], defaultSorted = c("Species", "Petal.Length"))
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
4.6
3.2
1.4
0.2
setosa
5
3.3
1.4
0.2
setosa
5.3
3.7
1.5
0.2
setosa
6.4
3.2
4.5
1.5
versicolor
7
3.2
4.7
1.4
versicolor

You can also provide a named list to customize the default sort orders. Use "asc" for ascending order, or "desc" for descending order:

reactable(iris[48:52, ], defaultSorted = list(Species = "asc", Petal.Length = "desc"))
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.3
3.7
1.5
0.2
setosa
4.6
3.2
1.4
0.2
setosa
5
3.3
1.4
0.2
setosa
7
3.2
4.7
1.4
versicolor
6.4
3.2
4.5
1.5
versicolor

Default sort order

Columns are sorted in ascending order first by default. To change the default sort order for all columns in the table, set defaultSortOrder in reactable() to "asc" for ascending order, or "desc" for descending order.

To change the sort order of an individual column, set defaultSortOrder in its colDef() to "asc" or "desc". The default sort order of the column takes precedence over the table.

reactable(
  iris[48:52, ],
  defaultSortOrder = "desc",
  columns = list(
    Species = colDef(defaultSortOrder = "asc")
  ),
  defaultSorted = c("Species", "Petal.Length")
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.3
3.7
1.5
0.2
setosa
4.6
3.2
1.4
0.2
setosa
5
3.3
1.4
0.2
setosa
7
3.2
4.7
1.4
versicolor
6.4
3.2
4.5
1.5
versicolor

Sort missing values last

You can ignore missing values when sorting by setting sortNALast on a column:

reactable(
  data.frame(
    n = c(1, 2, 3, -Inf, Inf),
    x = c(2, 3, 1, NA, NaN),
    y = c("aa", "cc", "bb", NA, NA)
  ),
  defaultColDef = colDef(sortNALast = TRUE),
  defaultSorted = "x"
)
n
x
y
3
1
bb
1
2
aa
2
3
cc
-Infinity
Infinity

No sorting

You can disable sorting by setting sortable to FALSE on the table or column. When only some columns are sortable, it can help to indicate sortable columns using showSortable:

reactable(
  iris[1:5, ],
  sortable = FALSE,
  showSortable = TRUE,
  columns = list(
    Petal.Width = colDef(sortable = TRUE),
    Petal.Length = colDef(sortable = TRUE)
  )
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Hide sort icons

You can hide sort icons by setting showSortIcon to FALSE. This is only recommended when you want to use a custom sort indicator.

reactable(iris[1:5, ], showSortIcon = FALSE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Filtering

You can make columns filterable by setting filterable = TRUE in reactable():

data <- MASS::Cars93[1:20, c("Manufacturer", "Model", "Type", "AirBags", "Price")]

reactable(data, filterable = TRUE, minRows = 10)
Manufacturer
Model
Type
AirBags
Price
Acura
Integra
Small
None
15.9
Acura
Legend
Midsize
Driver & Passenger
33.9
Audi
90
Compact
Driver only
29.1
Audi
100
Midsize
Driver & Passenger
37.7
BMW
535i
Midsize
Driver only
30
Buick
Century
Midsize
Driver only
15.7
Buick
LeSabre
Large
Driver only
20.8
Buick
Roadmaster
Large
Driver only
23.7
Buick
Riviera
Midsize
Driver only
26.3
Cadillac
DeVille
Large
Driver only
34.7
1–10 of 20 rows

To make specific columns filterable (or not), set filterable to TRUE or FALSE in colDef():

reactable(
  data,
  filterable = TRUE,
  columns = list(
    Price = colDef(filterable = FALSE)
  ),
  defaultPageSize = 5
)
Manufacturer
Model
Type
AirBags
Price
Acura
Integra
Small
None
15.9
Acura
Legend
Midsize
Driver & Passenger
33.9
Audi
90
Compact
Driver only
29.1
Audi
100
Midsize
Driver & Passenger
37.7
BMW
535i
Midsize
Driver only
30
1–5 of 20 rows

Custom filtering

Column filtering can be customized using the filterMethod and filterInput arguments in colDef(). See the Custom Filtering guide for more details and examples.

This example shows basic usage of a custom filter method, changing filtering on the Manufacturer column to be case-sensitive rather than case-insensitive. (Try filtering for “bmw” and then “BMW”).

data <- MASS::Cars93[, c("Manufacturer", "Model", "Type", "Price")]

reactable(
  data,
  columns = list(
    Manufacturer = colDef(
      filterable = TRUE,
      # Filter by case-sensitive text match
      filterMethod = JS("function(rows, columnId, filterValue) {
        return rows.filter(function(row) {
          return row.values[columnId].indexOf(filterValue) !== -1
        })
      }")
    )
  ),
  defaultPageSize = 5
)
Manufacturer
Model
Type
Price
Acura
Integra
Small
15.9
Acura
Legend
Midsize
33.9
Audi
90
Compact
29.1
Audi
100
Midsize
37.7
BMW
535i
Midsize
30
1–5 of 93 rows
...

Searching

You can make the entire table searchable by setting searchable = TRUE in reactable():

data <- MASS::Cars93[1:20, c("Manufacturer", "Model", "Type", "AirBags", "Price")]

reactable(data, searchable = TRUE, minRows = 10)
Manufacturer
Model
Type
AirBags
Price
Acura
Integra
Small
None
15.9
Acura
Legend
Midsize
Driver & Passenger
33.9
Audi
90
Compact
Driver only
29.1
Audi
100
Midsize
Driver & Passenger
37.7
BMW
535i
Midsize
Driver only
30
Buick
Century
Midsize
Driver only
15.7
Buick
LeSabre
Large
Driver only
20.8
Buick
Roadmaster
Large
Driver only
23.7
Buick
Riviera
Midsize
Driver only
26.3
Cadillac
DeVille
Large
Driver only
34.7
1–10 of 20 rows

Custom searching

The table search method can be customized using the searchMethod argument in reactable(). See the Custom Filtering guide for details and examples.

Pagination

You can change the default page size by configuring defaultPageSize:

reactable(iris[1:6, ], defaultPageSize = 4)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 6 rows

You can also set the minimum rows per page using minRows. This may be useful when rows don’t completely fill the page, or if the table has filtering:

reactable(iris[1:6, ], defaultPageSize = 4, minRows = 4, searchable = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 6 rows

Page size options

You can show a dropdown of page sizes for users to choose from using showPageSizeOptions. The page size options can be customized through pageSizeOptions:

reactable(
  iris[1:12, ],
  showPageSizeOptions = TRUE,
  pageSizeOptions = c(4, 8, 12),
  defaultPageSize = 4
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 12 rows
Show

Alternative pagination types

You can use an alternative pagination type by setting paginationType to:

  • "jump" to show a page jump
  • "simple" to show previous/next buttons only

Page jump

reactable(iris[1:50, ], paginationType = "jump", defaultPageSize = 4)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 50 rows
of 13

Simple

reactable(iris[1:50, ], paginationType = "simple", defaultPageSize = 4)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 50 rows
1 of 13

Hide page info

You can hide page info by setting showPageInfo to FALSE:

reactable(iris[1:12, ], showPageInfo = FALSE, defaultPageSize = 4)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
reactable(iris[1:12, ], showPageInfo = FALSE, showPageSizeOptions = TRUE, defaultPageSize = 4)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
Show

Always show pagination

By default, pagination is hidden if the table only has one page. To keep the pagination shown, set showPagination to TRUE. This is especially useful if you want to keep the page info showing the number of rows in the table.

reactable(iris[1:5, ], showPagination = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
1–5 of 5 rows

No pagination

Tables are paginated by default, but you can disable pagination by setting pagination to FALSE:

reactable(iris[1:20, ], pagination = FALSE, highlight = TRUE, height = 250)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
4.6
3.4
1.4
0.3
setosa
5
3.4
1.5
0.2
setosa
4.4
2.9
1.4
0.2
setosa
4.9
3.1
1.5
0.1
setosa
5.4
3.7
1.5
0.2
setosa
4.8
3.4
1.6
0.2
setosa
4.8
3
1.4
0.1
setosa
4.3
3
1.1
0.1
setosa
5.8
4
1.2
0.2
setosa
5.7
4.4
1.5
0.4
setosa
5.4
3.9
1.3
0.4
setosa
5.1
3.5
1.4
0.3
setosa
5.7
3.8
1.7
0.3
setosa
5.1
3.8
1.5
0.3
setosa

Tip: Disabling pagination is not recommended for large tables with many interactive elements (such as links, expand buttons, or selection checkboxes), as that can make it difficult for keyboard users to navigate the page.

Grouping and Aggregation

You can group rows in a table by specifying one or more columns in groupBy:

data <- MASS::Cars93[10:22, c("Manufacturer", "Model", "Type", "Price", "MPG.city")]

reactable(data, groupBy = "Manufacturer")
Manufacturer
Model
Type
Price
MPG.city
Cadillac (2)
Chevrolet (8)
Chrylser (1)
Chrysler (2)

When rows are grouped, you can aggregate data in a column using an aggregate function:

data <- MASS::Cars93[14:38, c("Type", "Price", "MPG.city", "DriveTrain", "Man.trans.avail")]

reactable(
  data,
  groupBy = "Type",
  columns = list(
    Price = colDef(aggregate = "max"),
    MPG.city = colDef(aggregate = "mean", format = colFormat(digits = 1)),
    DriveTrain = colDef(aggregate = "unique"),
    Man.trans.avail = colDef(aggregate = "frequency")
  )
)
Type
Price
MPG.city
DriveTrain
Man.trans.avail
Sporty (5)
38
20.0
Rear, 4WD, Front
Yes (5)
Midsize (3)
20.2
21.0
Front
No (3)
Van (4)
19.9
16.3
Front, 4WD
No (3), Yes
Large (5)
29.5
19.0
Rear, Front
No (5)
Compact (3)
15.8
22.3
Front
No, Yes (2)
Small (5)
12.2
27.0
Front
Yes (5)

You can use one of the built-in aggregate functions:

colDef(aggregate = "sum")        # Sum of numbers
colDef(aggregate = "mean")       # Mean of numbers
colDef(aggregate = "max")        # Maximum of numbers
colDef(aggregate = "min")        # Minimum of numbers
colDef(aggregate = "median")     # Median of numbers
colDef(aggregate = "count")      # Count of values
colDef(aggregate = "unique")     # Comma-separated list of unique values
colDef(aggregate = "frequency")  # Comma-separated counts of unique values

Or a custom aggregate function in JavaScript:

colDef(
  aggregate = JS("
    function(values, rows) {
      // input:
      //  - values: an array of all values in the group
      //  - rows: an array of row data values for all rows in the group (optional)
      //
      // output:
      //  - an aggregated value, e.g. a comma-separated list
      return values.join(', ')
    }
  ")
)

Multiple groups

data <- data.frame(
  State = state.name,
  Region = state.region,
  Division = state.division,
  Area = state.area
)

reactable(
  data,
  groupBy = c("Region", "Division"),
  columns = list(
    Division = colDef(aggregate = "unique"),
    Area = colDef(aggregate = "sum", format = colFormat(separators = TRUE))
  ),
  bordered = TRUE
)
Region
Division
State
Area
South (3)
East South Central, West South Central, South Atlantic
899,556
West (2)
Pacific, Mountain
1,783,960
Northeast (2)
New England, Middle Atlantic
169,353
North Central (2)
East North Central, West North Central
765,530

Custom aggregate function

Custom aggregate functions are useful when none of the built-in aggregate functions apply, or when you want to aggregate values from multiple columns. For example, when calculating aggregate averages or percentages.

Within a custom aggregate function, you can access the values in the column using the values argument, and the values in other columns using the rows argument:

columns = list(
  Price = colDef(
    aggregate = JS("function(values, rows) {
      values
      // [46.8, 27.6, 57]

      rows
      // [
      //   { "Model": "Dynasty", "Manufacturer": "Dodge", "Price": 46.8, "Units": 2 },
      //   { "Model": "Colt", "Manufacturer": "Dodge", "Price": 27.6, "Units": 5 },
      //   { "Model": "Caravan", "Manufacturer": "Dodge", "Price": 57, "Units": 5 }
      // ]
    }")
  )
)

Here’s an example that calculates an aggregate average price by dividing the the sum of two columns, Price and Units:

library(dplyr)

set.seed(10)

data <- sample_n(MASS::Cars93[23:40, ], 30, replace = TRUE) %>%
  mutate(Price = Price * 3, Units = sample(1:5, 30, replace = TRUE)) %>%
  mutate(Avg.Price = Price / Units) %>%
  select(Model, Manufacturer, Price, Units, Avg.Price)

reactable(
  data,
  groupBy = "Manufacturer",
  columns = list(
    Price = colDef(aggregate = "sum", format = colFormat(currency = "USD")),
    Units = colDef(aggregate = "sum"),
    Avg.Price = colDef(
      # Calculate the aggregate Avg.Price as `sum(Price) / sum(Units)`
      aggregate = JS("function(values, rows) {
        let totalPrice = 0
        let totalUnits = 0
        rows.forEach(function(row) {
          totalPrice += row['Price']
          totalUnits += row['Units']
        })
        return totalPrice / totalUnits
      }"),
      format = colFormat(currency = "USD")
    )
  )
)
Manufacturer
Model
Price
Units
Avg.Price
Ford (13)
$556.20
29
$19.18
Eagle (7)
$298.80
22
$13.58
Dodge (5)
$242.70
14
$17.34
Geo (5)
$187.50
17
$11.03

Include sub rows in pagination

By default, sub rows are excluded from pagination and always shown on the same page when expanded. To include sub rows in pagination, you can set paginateSubRows to TRUE. This is recommended for grouped tables with a large number of rows where expanded rows may not all fit on one page.

data <- MASS::Cars93[, c("Manufacturer", "Model", "Type", "Price", "MPG.city")]

reactable(data, groupBy = "Type", paginateSubRows = TRUE)
Type
Manufacturer
Model
Price
MPG.city
Small (21)
Midsize (22)
Compact (16)
Large (11)
Sporty (14)
Van (9)
1–6 of 6 rows

Column Formatting

You can format data in a column by providing colFormat() options to the format argument in colDef().

The formatters for numbers, dates, times, and currencies are locale-sensitive and automatically adapt to language preferences of the user’s browser. This means, for example, that users will see dates formatted in their own timezone or numbers formatted in their own locale.

To use a specific locale for data formatting, provide a vector of BCP 47 language tags in the locales argument. See a list of common BCP 47 language tags for reference.

Note: Column formatters change how data is displayed without affecting the underlying data. Sorting, filtering, and grouping will still work on the original data.

data <- data.frame(
  price_USD = c(123456.56, 132, 5650.12),
  price_INR = c(350, 23208.552, 1773156.4),
  number_FR = c(123456.56, 132, 5650.12),
  temp = c(22, NA, 31),
  percent = c(0.9525556, 0.5, 0.112),
  date = as.Date(c("2019-01-02", "2019-03-15", "2019-09-22"))
)

reactable(data, columns = list(
  price_USD = colDef(format = colFormat(prefix = "$", separators = TRUE, digits = 2)),
  price_INR = colDef(format = colFormat(currency = "INR", separators = TRUE, locales = "hi-IN")),
  number_FR = colDef(format = colFormat(locales = "fr-FR")),
  temp = colDef(format = colFormat(suffix = " °C")),
  percent = colDef(format = colFormat(percent = TRUE, digits = 1)),
  date = colDef(format = colFormat(date = TRUE, locales = "en-GB"))
))
price_USD
price_INR
number_FR
temp
percent
date
$123,456.56
₹350.00
123456.56
22 °C
95.3%
Wed Jan 02 2019
$132.00
₹23,208.55
132
50.0%
Fri Mar 15 2019
$5,650.12
₹1,773,156.40
5650.12
31 °C
11.2%
Sun Sep 22 2019

Date formatting

datetimes <- as.POSIXct(c("2019-01-02 3:22:15", "2019-03-15 09:15:55", "2019-09-22 14:20:00"),
                        tz = "America/New_York")
data <- data.frame(
  datetime = datetimes,
  date = datetimes,
  time = datetimes,
  time_24h = datetimes,
  datetime_pt_BR = datetimes
)

reactable(data, columns = list(
  datetime = colDef(format = colFormat(datetime = TRUE)),
  date = colDef(format = colFormat(date = TRUE)),
  time = colDef(format = colFormat(time = TRUE)),
  time_24h = colDef(format = colFormat(time = TRUE, hour12 = FALSE)),
  datetime_pt_BR = colDef(format = colFormat(datetime = TRUE, locales = "pt-BR"))
))
datetime
date
time
time_24h
datetime_pt_BR
Wed Jan 02 2019 08:22:15 GMT+0000 (UTC)
Wed Jan 02 2019
08:22:15 GMT+0000 (UTC)
08:22:15 GMT+0000 (UTC)
Wed Jan 02 2019 08:22:15 GMT+0000 (UTC)
Fri Mar 15 2019 13:15:55 GMT+0000 (UTC)
Fri Mar 15 2019
13:15:55 GMT+0000 (UTC)
13:15:55 GMT+0000 (UTC)
Fri Mar 15 2019 13:15:55 GMT+0000 (UTC)
Sun Sep 22 2019 18:20:00 GMT+0000 (UTC)
Sun Sep 22 2019
18:20:00 GMT+0000 (UTC)
18:20:00 GMT+0000 (UTC)
Sun Sep 22 2019 18:20:00 GMT+0000 (UTC)

Currency formatting

data <- data.frame(
  USD = c(12.12, 2141.213, 0.42, 1.55, 34414),
  EUR = c(10.68, 1884.27, 0.37, 1.36, 30284.32),
  INR = c(861.07, 152122.48, 29.84, 110, 2444942.63),
  JPY = c(1280, 226144, 44.36, 164, 3634634.61),
  MAD = c(115.78, 20453.94, 4.01, 15, 328739.73)
)

reactable(data, columns = list(
  USD = colDef(
    format = colFormat(currency = "USD", separators = TRUE, locales = "en-US")
  ),
  EUR = colDef(
    format = colFormat(currency = "EUR", separators = TRUE, locales = "de-DE")
  ),
  INR = colDef(
    format = colFormat(currency = "INR", separators = TRUE, locales = "hi-IN")
  ),
  JPY = colDef(
    format = colFormat(currency = "JPY", separators = TRUE, locales = "ja-JP")
  ),
  MAD = colDef(
    format = colFormat(currency = "MAD", separators = TRUE, locales = "ar-MA")
  )
))
USD
EUR
INR
JPY
MAD
$12.12
€10.68
₹861.07
¥1,280
MAD 115.78
$2,141.21
€1,884.27
₹152,122.48
¥226,144
MAD 20,453.94
$0.42
€0.37
₹29.84
¥44
MAD 4.01
$1.55
€1.36
₹110.00
¥164
MAD 15.00
$34,414.00
€30,284.32
₹2,444,942.63
¥3,634,635
MAD 328,739.73

Formatting aggregated cells

Column formatters apply to both standard and aggregated cells by default. If you want to format aggregated cells separately, provide a named list of cell and aggregated options:

colDef(
  format = list(
    cell = colFormat(...),       # Standard cells
    aggregated = colFormat(...)  # Aggregated cells
  )
)

For example, only the aggregated States are formatted here:

data <- data.frame(
  States = state.name,
  Region = state.region,
  Area = state.area
)

reactable(
  data,
  groupBy = "Region",
  columns = list(
    States = colDef(
      aggregate = "count",
      format = list(
        aggregated = colFormat(suffix = " states")
      )
    ),
    Area = colDef(
      aggregate = "sum",
      format = colFormat(suffix = " mi²", separators = TRUE)
    )
  )
)
Region
States
Area
South (16)
16 states
899,556 mi²
West (13)
13 states
1,783,960 mi²
Northeast (9)
9 states
169,353 mi²
North Central (12)
12 states
765,530 mi²

Displaying missing values

Missing values are ignored by formatters and shown as empty cells by default. You can customize their display text by setting na on a column:

reactable(
  data.frame(
    n = c(1, 2, NA, 4, 5),
    x = c(55, 27, NA, NaN, 19),
    y = c(1, NA, 0.25, 0.55, NA)
  ),
  columns = list(
    x = colDef(na = "–", format = colFormat(prefix = "$")),
    y = colDef(na = "NA", format = colFormat(percent = TRUE))
  )
)
n
x
y
1
$55
100%
2
$27
NA
25%
4
55%
5
$19
NA

Custom data formatting

If none of the built-in formatters apply to your data, you can use a custom cell renderer instead.

Custom Rendering

You can customize how data is displayed using an R or JavaScript function that returns custom content. R render functions support Shiny HTML tags (or htmltools) and HTML widgets, while JavaScript render functions allow for more dynamic behavior.

You can also render content as HTML using colDef(html = TRUE). Note that all raw HTML is escaped by default.

See Custom Rendering for details on how to use render functions, and the Demo Cookbook for even more examples of custom rendering.

Note: Custom rendering changes how data is displayed without affecting the underlying data. Sorting, filtering, and grouping will still work on the original data.

Cell rendering

R render function

data <- MASS::Cars93[1:5, c("Manufacturer", "Model", "Type", "AirBags", "Price")]

reactable(data, columns = list(
  Model = colDef(cell = function(value, index) {
    # Render as a link
    url <- sprintf("https://wikipedia.org/wiki/%s_%s", data[index, "Manufacturer"], value)
    htmltools::tags$a(href = url, target = "_blank", as.character(value))
  }),
  AirBags = colDef(cell = function(value) {
    # Render as an X mark or check mark
    if (value == "None") "\u274c No" else "\u2714\ufe0f Yes"
  }),
  Price = colDef(cell = function(value) {
    # Render as currency
    paste0("$", format(value * 1000, big.mark = ","))
  })
))
Manufacturer
Model
Type
AirBags
Price
Acura
Small
❌ No
$15,900
Acura
Midsize
✔️ Yes
$33,900
Audi
Compact
✔️ Yes
$29,100
Audi
Midsize
✔️ Yes
$37,700
BMW
Midsize
✔️ Yes
$30,000

JavaScript render function

data <- MASS::Cars93[1:5, c("Manufacturer", "Model", "Type", "AirBags", "Price")]

reactable(data, columns = list(
  Model = colDef(html = TRUE, cell = JS('
    function(cellInfo) {
      // Render as a link
      const url = `https://wikipedia.org/wiki/${cellInfo.row["Manufacturer"]}_${cellInfo.value}`
      return `<a href="${url}" target="_blank">${cellInfo.value}</a>`
    }
  ')),
  AirBags = colDef(cell = JS("
    function(cellInfo) {
      // Render as an X mark or check mark
      return cellInfo.value === 'None' ? '\u274c No' : '\u2714\ufe0f Yes'
    }
  ")),
  Price = colDef(cell = JS("
    function(cellInfo) {
      // Render as currency
      return '$' + (cellInfo.value * 1000).toLocaleString()
    }
  "))
))
Manufacturer
Model
Type
AirBags
Price
Acura
Small
❌ No
$15,900
Acura
Midsize
✔️ Yes
$33,900
Audi
Compact
✔️ Yes
$29,100
Audi
Midsize
✔️ Yes
$37,700
BMW
Midsize
✔️ Yes
$30,000

Embedding HTML widgets

library(dplyr)
library(sparkline)

data <- chickwts %>%
  group_by(feed) %>%
  summarise(weight = list(weight)) %>%
  mutate(boxplot = NA, sparkline = NA)

reactable(data, columns = list(
  weight = colDef(cell = function(values) {
    sparkline(values, type = "bar", chartRangeMin = 0, chartRangeMax = max(chickwts$weight))
  }),
  boxplot = colDef(cell = function(value, index) {
    sparkline(data$weight[[index]], type = "box")
  }),
  sparkline = colDef(cell = function(value, index) {
    sparkline(data$weight[[index]])
  })
))
feed
weight
boxplot
sparkline
casein
horsebean
linseed
meatmeal
soybean
sunflower

Grouped cell rendering

data <- MASS::Cars93[10:22, c("Manufacturer", "Model", "Type", "Price", "MPG.city")]

reactable(
  data,
  groupBy = c("Manufacturer", "Type"),
  columns = list(
    Manufacturer = colDef(
      # Render grouped cells without the row count
      grouped = JS("function(cellInfo) {
        return cellInfo.value
      }")
    ),
    Type = colDef(
      # Render grouped cells with the row count, only if there are multiple sub rows
      grouped = JS("function(cellInfo) {
        if (cellInfo.subRows.length > 1) {
          return cellInfo.value + ' (' + cellInfo.subRows.length + ')'
        }
        return cellInfo.value
      }")
    )
  )
)
Manufacturer
Type
Model
Price
MPG.city
Cadillac
Chevrolet
Chrylser
Chrysler

Aggregated cell rendering

library(dplyr)

set.seed(10)

data <- sample_n(tail(MASS::Cars93, 9), 30, replace = TRUE) %>%
  select(Manufacturer, Model, Type, Sales = Price)

reactable(
  data,
  groupBy = "Manufacturer",
  searchable = TRUE,
  columns = list(
    Model = colDef(aggregate = "unique"),
    Type = colDef(
      # Render aggregated value as a comma-separated list of unique values
      aggregated = JS("function(cellInfo) {
        const values = cellInfo.subRows.map(function(row) { return row['Type'] })
        const unique = values.reduce(function(obj, v) { obj[v] = true; return obj }, {})
        return Object.keys(unique).join(', ')
      }")
    ),
    Sales = colDef(
      aggregate = "sum",
      # Render aggregated cell as currency
      aggregated = JS("function(cellInfo) {
        return '$' + cellInfo.value.toFixed(2)
      }")
    )
  )
)
Manufacturer
Model
Type
Sales
Volvo (8)
850, 240
Midsize, Compact
$193.60
Volkswagen (13)
Corrado, Passat, Eurovan, Fox
Sporty, Compact, Van, Small
$268.30
Toyota (9)
Previa, Camry, Celica
Van, Midsize, Sporty
$173.00

Header rendering

This example requires reactable v0.3.0 or above.

library(htmltools)

reactable(
  iris[1:5, ],
  defaultColDef = colDef(header = function(value) {
    units <- div(style = "color: #737373", "cm")
    div(title = value, value, units)
  }),
  columns = list(
    Petal.Width = colDef(
      name = "Petal Width",
      html = TRUE,
      align = "left",
      header = JS('function(column) {
        return column.name + `<div style="color: #737373">cm</div>`
      }')
    ),
    Species = colDef(header = function(value) {
      tags$a(href = "https://wikipedia.org/wiki/List_of_Iris_species", value)
    })
  )
)
Sepal.Length
cm
Sepal.Width
cm
Petal.Length
cm
Petal Width
cm
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Custom metadata

New in v0.4.0

You can pass arbitrary data from R to JavaScript render functions using the meta argument in reactable().

meta should be a named list of values that can also be JS() expressions or functions. Custom metadata can be accessed from JavaScript using the state.meta property, and updated using updateReactable() in Shiny or Reactable.setMeta() in the JavaScript API.

Use custom metadata to:

  • Simplify JavaScript render functions that need access to data outside of the table
  • Dynamically change how data is formatted without rerendering the table
  • Share JavaScript code or data between different render functions
library(htmltools)

data <- MASS::Cars93[1:6, c("Manufacturer", "Model", "Type", "Price", "MPG.city")]

exchange_rates <- list(
  USD = 1,
  CAD = 1.30,
  JPY = 137.56
)

tbl <- reactable(
  data,
  columns = list(
    Price = colDef(
      cell = JS("function(cellInfo, state) {
        const { currency, exchangeRates } = state.meta
        const converted = cellInfo.value * exchangeRates[currency]
        return converted.toLocaleString(undefined, { style: 'currency', currency: currency })
      }")
    )
  ),
  meta = list(
    currency = "USD",
    exchangeRates = exchange_rates
  ),
  elementId = "cars-currency-table"
)

browsable(
  tagList(
    tags$label(
      "Currency",
      tags$select(
        onchange = "Reactable.setMeta('cars-currency-table', { currency: event.target.value })",
        lapply(names(exchange_rates), tags$option)
      )
    ),

    tags$hr("aria-hidden" = "true"),

    tbl
  )
)
Manufacturer
Model
Type
Price
MPG.city
Acura
Integra
Small
$15.90
25
Acura
Legend
Midsize
$33.90
18
Audi
90
Compact
$29.10
20
Audi
100
Midsize
$37.70
19
BMW
535i
Midsize
$30.00
22
Buick
Century
Midsize
$15.70
22

Footers

You can add column footers using the footer argument in colDef().

footer can either be custom content to render (e.g., a character string or HTML tag), or a custom render function. See Custom Rendering to learn more about using custom render functions.

R render function

library(dplyr)
library(htmltools)

data <- MASS::Cars93[18:47, ] %>%
  select(Manufacturer, Model, Type, Sales = Price)

reactable(
  data,
  defaultPageSize = 5,
  columns = list(
    Manufacturer = colDef(footer = "Total"),
    Sales = colDef(footer = function(values) sprintf("$%.2f", sum(values)))
  ),
  defaultColDef = colDef(footerStyle = list(fontWeight = "bold"))
)
Manufacturer
Model
Type
Sales
Chevrolet
Caprice
Large
18.8
Chevrolet
Corvette
Sporty
38
Chrylser
Concorde
Large
18.4
Chrysler
LeBaron
Compact
15.8
Chrysler
Imperial
Large
29.5
1–5 of 30 rows

JavaScript render function

This example requires reactable v0.3.0 or above.

reactable(
  data,
  searchable = TRUE,
  defaultPageSize = 5,
  minRows = 5,
  columns = list(
    Manufacturer = colDef(footer = "Total"),
    Sales = colDef(
      footer = JS("function(column, state) {
        let total = 0
        state.sortedData.forEach(function(row) {
          total += row[column.id]
        })
        return '$' + total.toFixed(2)
      }")
    )
  ),
  defaultColDef = colDef(footerStyle = list(fontWeight = "bold"))
)
Manufacturer
Model
Type
Sales
Chevrolet
Caprice
Large
18.8
Chevrolet
Corvette
Sporty
38
Chrylser
Concorde
Large
18.4
Chrysler
LeBaron
Compact
15.8
Chrysler
Imperial
Large
29.5
1–5 of 30 rows

Embedding HTML widgets

library(sparkline)

reactable(
  iris[1:20, ],
  defaultPageSize = 5,
  bordered = TRUE,
  defaultColDef = colDef(footer = function(values) {
    if (!is.numeric(values)) return()
    sparkline(values, type = "box", width = 100, height = 30)
  })
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
1–5 of 20 rows

Expandable Row Details

This example requires reactable v0.3.0 or above.

You can make rows expandable with additional content through details, which takes an R or JavaScript render function. See Custom Rendering for details on how to use render functions.

reactable(iris[1:5, ], details = function(index) {
  htmltools::div(
    "Details for row: ", index,
    htmltools::tags$pre(paste(capture.output(iris[index, ]), collapse = "\n"))
  )
})
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

The details column can be customized by providing a colDef() instead. This can be used to add a column name, render HTML content, or change the column width:

reactable(iris[1:5, ], details = colDef(
  name = "More",
  details = JS("function(rowInfo) {
    return `Details for row: ${rowInfo.index}` +
      `<pre>${JSON.stringify(rowInfo.values, null, 2)}</pre>`
  }"),
  html = TRUE,
  width = 60
))
More
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Nested tables

With R render functions, you can render HTML tags, HTML widgets, and even nested tables:

data <- unique(CO2[, c("Plant", "Type")])

reactable(data, details = function(index) {
  plant_data <- CO2[CO2$Plant == data$Plant[index], ]
  htmltools::div(style = "padding: 1rem",
    reactable(plant_data, outlined = TRUE)
  )
})
Plant
Type
Qn1
Quebec
Qn2
Quebec
Qn3
Quebec
Qc1
Quebec
Qc2
Quebec
Qc3
Quebec
Mn1
Mississippi
Mn2
Mississippi
Mn3
Mississippi
Mc1
Mississippi
1–10 of 12 rows

Conditional row details

R render functions support conditional rendering. If a render function returns NULL, the row won’t be expandable:

reactable(iris[1:5, ], details = function(index) {
  if (index %in% c(3, 5)) {
    reactable(data.frame(x = c(1, 2, 3), y = c("a", "b", "c")), fullWidth = FALSE)
  }
})
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Multiple row details

This example requires reactable v0.3.0 or above.

You can add details to individual columns, and even show multiple details for a row:

reactable(iris[1:5, ],
  details = function(index) {
    if (index %in% c(3, 5)) {
      reactable(data.frame(x = c(1, 2, 3), y = c("a", "b", "c")), fullWidth = FALSE)
    }
  },
  columns = list(
    Petal.Length = colDef(details = function(index) {
      paste("Petal.Length: ", iris[index, "Petal.Length"])
    }),
    Sepal.Length = colDef(format = colFormat(digits = 1), details = JS("
      function(rowInfo) {
        return 'Sepal.Length: ' + rowInfo.values['Sepal.Length']
      }
    "))
  )
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5.0
3.6
1.4
0.2
setosa

Default expanded rows

You can expand all rows by default by setting defaultExpanded to TRUE:

reactable(
  iris[1:12, ],
  defaultPageSize = 4,
  details = function(index) paste("Details for row:", index),
  defaultExpanded = TRUE
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
1–4 of 12 rows

Conditional Styling

You can conditionally style a table using functions that return inline styles or CSS classes. Just like with custom rendering, style functions can either be in R or JavaScript.

See Conditional Styling for details on how to use style functions, and the Demo Cookbook for even more examples of conditional styling.

Cell styling

R style function

reactable(sleep[1:6, ], columns = list(
  extra = colDef(
    style = function(value) {
      if (value > 0) {
        color <- "#008000"
      } else if (value < 0) {
        color <- "#e00000"
      } else {
        color <- "#777"
      }
      list(color = color, fontWeight = "bold")
    }
  )
))
extra
group
ID
0.7
1
1
-1.6
1
2
-0.2
1
3
-1.2
1
4
-0.1
1
5
3.4
1
6

JavaScript style function

This example requires reactable v0.3.0 or above.

reactable(sleep[1:6, ], columns = list(
  extra = colDef(
    style = JS("function(rowInfo) {
      const value = rowInfo.values['extra']
      let color
      if (value > 0) {
        color = '#008000'
      } else if (value < 0) {
        color = '#e00000'
      } else {
        color = '#777'
      }
      return { color: color, fontWeight: 'bold' }
    }")
  )
))
extra
group
ID
0.7
1
1
-1.6
1
2
-0.2
1
3
-1.2
1
4
-0.1
1
5
3.4
1
6

Row styling

R style function

reactable(sleep[1:6, ], 
  rowStyle = function(index) {
    if (sleep[index, "extra"] < -1) {
      list(background = "rgba(0, 0, 0, 0.05)")
    }
  },
  rowClass = function(index) {
    if (sleep[index, "extra"] < -1) {
      "bold"
    }
  }
)
.bold {
  font-weight: bold;
}
extra
group
ID
0.7
1
1
-1.6
1
2
-0.2
1
3
-1.2
1
4
-0.1
1
5
3.4
1
6

JavaScript style function

This example requires reactable v0.3.0 or above.

reactable(sleep[1:6, ],
  rowStyle = JS("function(rowInfo) {
    if (rowInfo.values['extra'] < -1) {
      return { background: 'rgba(0, 0, 0, 0.05)' }
    }
  }"),
  rowClass = JS("function(rowInfo) {
    if (rowInfo.values['extra'] < -1) {
      return 'bold'
    }
  }")
)
extra
group
ID
0.7
1
1
-1.6
1
2
-0.2
1
3
-1.2
1
4
-0.1
1
5
3.4
1
6

Custom metadata

New in v0.4.0

You can pass arbitrary data from R to JavaScript style functions using the meta argument in reactable().

meta should be a named list of values that can also be JS() expressions or functions. Custom metadata can be accessed from JavaScript using the state.meta property, and updated using updateReactable() in Shiny or Reactable.setMeta() in the JavaScript API.

Use custom metadata to:

  • Simplify JavaScript style functions that need access to data outside of the table
  • Dynamically change how data is styled without rerendering the table
  • Share JavaScript code or data between different style functions
library(htmltools)

data <- MASS::Cars93[1:6, c("Manufacturer", "Model", "Type", "Price", "MPG.city")]

mpg_normalized <- (data$MPG.city - min(data$MPG.city)) / (max(data$MPG.city) - min(data$MPG.city))
mpg_colors <-  rgb(colorRamp(c("#ffe4cc", "#ff9f1a"))(mpg_normalized), maxColorValue = 255)

tbl <- reactable(
  data,
  columns = list(
    MPG.city = colDef(
      style = JS("function(rowInfo, column, state) {
        const { showColors, mpgColors } = state.meta
        if (showColors) {
          return { backgroundColor: mpgColors[rowInfo.index] }
        }
      }")
    )
  ),
  meta = list(
    mpgColors = mpg_colors,
    showColors = TRUE
  ),
  elementId = "cars-colors-table"
)

browsable(
  tagList(
    tags$label(
      tags$input(
        type = "checkbox",
        checked = NA,
        onclick = "Reactable.setMeta('cars-colors-table', function(prevMeta) {
          return { showColors: !prevMeta.showColors }
        })"
      ),
      "Show color scale"
    ),

    tags$hr("aria-hidden" = "true"),

    tbl
  )
)
Manufacturer
Model
Type
Price
MPG.city
Acura
Integra
Small
15.9
25
Acura
Legend
Midsize
33.9
18
Audi
90
Compact
29.1
20
Audi
100
Midsize
37.7
19
BMW
535i
Midsize
30
22
Buick
Century
Midsize
15.7
22

Table Styling

You can customize table styling using several options, which can all be combined:

Highlight rows on hover

reactable(iris[1:5, ], highlight = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Bordered

reactable(iris[1:5, ], bordered = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Borderless

reactable(iris[1:5, ], borderless = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Outlined

reactable(iris[1:5, ], outlined = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Striped

reactable(iris[1:5, ], striped = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Bordered + striped + highlighting

reactable(iris[1:5, ], bordered = TRUE, striped = TRUE, highlight = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Outlined + borderless

reactable(iris[1:5, ], outlined = TRUE, borderless = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Compact

reactable(iris[1:5, ], compact = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

No text wrapping

Long text is wrapped by default, but you can force text to fit on a single line by setting wrap to FALSE:

data <- aggregate(. ~ Species, iris, toString)

reactable(
  data,
  wrap = FALSE,
  resizable = TRUE,
  bordered = TRUE,
  columns = list(Petal.Length = colDef(name = "Petal Length (cm)", minWidth = 50))
)
Species
Sepal.Length
Sepal.Width
Petal Length (cm)
Petal.Width
setosa
5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1, 4.8, 5.1, 4.6, 5.3, 5
3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3, 3, 4, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3, 3.8, 3.2, 3.7, 3.3
1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4
0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2
versicolor
7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8, 6, 5.4, 6, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7
3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2, 3, 2.2, 2.9, 2.9, 3.1, 3, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3, 2.8, 3, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3, 3.4, 3.1, 2.3, 3, 2.5, 2.6, 3, 2.6, 2.3, 2.7, 3, 2.9, 2.9, 2.5, 2.8
4.7, 4.5, 4.9, 4, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4, 4.9, 4.7, 4.3, 4.4, 4.8, 5, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4, 4.4, 4.6, 4, 3.3, 4.2, 4.2, 4.2, 4.3, 3, 4.1
1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1, 1.3, 1.4, 1, 1.5, 1, 1.4, 1.3, 1.4, 1.5, 1, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1, 1.1, 1, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3
virginica
6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9
3.3, 2.7, 3, 2.9, 3, 3, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3, 2.5, 2.8, 3.2, 3, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3, 2.8, 3, 2.8, 3.8, 2.8, 2.8, 2.6, 3, 3.4, 3.1, 3, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3, 2.5, 3, 3.4, 3
6, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5, 5.1, 5.3, 5.5, 6.7, 6.9, 5, 5.7, 4.9, 6.7, 4.9, 5.7, 6, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5, 5.2, 5.4, 5.1
2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2, 1.9, 2.1, 2, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2, 2, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2, 2.3, 1.8

Fixed height + sticky header/footer

You can make tables scrollable by setting a fixed height or width. Headers and footers are sticky by default, so they stay in place when scrolling.

Scrollable tables are automatically made focusable when navigating using a keyboard to ensure that they’re always accessible for keyboard users.

reactable(
  iris[1:20, ],
  height = 270,
  striped = TRUE,
  defaultColDef = colDef(
    footer = function(values, name) {
      htmltools::div(name, style = list(fontWeight = 600))
    }
  )
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
4.6
3.4
1.4
0.3
setosa
5
3.4
1.5
0.2
setosa
4.4
2.9
1.4
0.2
setosa
4.9
3.1
1.5
0.1
setosa
1–10 of 20 rows

Column widths

By default, columns have a minimum width of 100px and stretch to fill the table. You can control the width of a column using the following arguments in colDef():

  • minWidth - minimum width of the column in pixels (defaults to 100)
  • maxWidth - maximum width of the column in pixels
  • width - fixed width of the column in pixels (overrides minWidth and maxWidth)

When columns stretch, minWidth also controls the ratio at which columns grow. For example, if a table consists of 3 columns having minWidth = 100 each, the columns will stretch at a ratio of 100:100:100. Each column will take up 1/3 of the table’s width and not shrink below 100px.

Another example: if a table consists of three columns having minimum widths of 200px, 100px, and 100px, the columns will take up 50%, 25%, and 25% of the table’s width respectively:

reactable(
  MASS::Cars93[1:6, c("Make", "Type", "Weight")],
  columns = list(
    Make = colDef(minWidth = 200),   # 50% width, 200px minimum
    Type = colDef(minWidth = 100),   # 25% width, 100px minimum
    Weight = colDef(minWidth = 100)  # 25% width, 100px minimum
  ),
  bordered = TRUE
)
Make
Type
Weight
Acura Integra
Small
2705
Acura Legend
Midsize
3560
Audi 90
Compact
3375
Audi 100
Midsize
3405
BMW 535i
Midsize
3640
Buick Century
Midsize
2880

No full width

Tables are full width by default, but you can shrink the table to fit its contents by setting fullWidth to FALSE:

reactable(
  MASS::Cars93[1:5, 1:5],
  fullWidth = FALSE,
  bordered = TRUE,
  defaultColDef = colDef(minWidth = 120)
)
Manufacturer
Model
Type
Min.Price
Price
Acura
Integra
Small
12.9
15.9
Acura
Legend
Midsize
29.2
33.9
Audi
90
Compact
25.9
29.1
Audi
100
Midsize
30.8
37.7
BMW
535i
Midsize
23.7
30

You can also set a maximum or fixed width on the table:

reactable(
  MASS::Cars93[1:5, 1:5],
  bordered = TRUE,
  defaultColDef = colDef(minWidth = 120),
  # Set a maximum width on the table:
  style = list(maxWidth = 650),
  # Or a fixed width:
  width = 650
)
Manufacturer
Model
Type
Min.Price
Price
Acura
Integra
Small
12.9
15.9
Acura
Legend
Midsize
29.2
33.9
Audi
90
Compact
25.9
29.1
Audi
100
Midsize
30.8
37.7
BMW
535i
Midsize
23.7
30

Vertical alignment

You can change the vertical alignment of cell content using the vAlign or headerVAlign arguments in colDef() and colGroup(). vAlign controls the alignment of data cells, while headerVAlign controls the alignment of header cells. Possible options are "top" (the default), "center", and "bottom".

library(dplyr)
library(htmltools)

data <- starwars[1:6, ] %>%
  select(character = name, height, mass, gender, homeworld, species)

reactable(
  data,
  columns = list(
    character = colDef(
      name = "Character / Species",
      # Show species under character names
      cell = function(value, index) {
        species <- data$species[index]
        species <- if (!is.na(species)) species else "Unknown"
        div(
          div(style = list(fontWeight = 600), value),
          div(style = list(fontSize = "0.75rem"), species)
        )
      }
    ),
    species = colDef(show = FALSE)
  ),
  # Vertically center cells and bottom-align headers
  defaultColDef = colDef(vAlign = "center", headerVAlign = "bottom"),
  bordered = TRUE
)
Character / Species
height
mass
gender
homeworld
Luke Skywalker
Human
172
77
masculine
Tatooine
C-3PO
Droid
167
75
masculine
Tatooine
R2-D2
Droid
96
32
masculine
Naboo
Darth Vader
Human
202
136
masculine
Tatooine
Leia Organa
Human
150
49
feminine
Alderaan
Owen Lars
Human
178
120
masculine
Tatooine

Custom CSS

For more control over styling, you can add custom class names to the table and apply your own CSS:

reactable(
  iris[1:18, ],
  defaultPageSize = 6,
  borderless = TRUE,
  class = "my-tbl",
  defaultColDef = colDef(headerClass = "my-header"),
  columns = list(
    Sepal.Width = colDef(class = "my-col"),
    Petal.Width = colDef(class = "my-col")
  ),
  rowClass = "my-row"
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
1–6 of 18 rows

In R Markdown documents, you can embed CSS using a css language chunk:

```{css, echo=FALSE}
.my-tbl {
  border: 1px solid rgba(0, 0, 0, 0.1);
}

.my-header {
  border-width: 1px;
}

.my-col {
  border-right: 1px solid rgba(0, 0, 0, 0.05);
}

.my-row:hover {
  background-color: #f5f8ff;
}
```

The examples here embed CSS for demonstration, but it’s sometimes better to add CSS through an external style sheet. To learn more about adding custom CSS through an external style sheet:

Note: If you inspect a table’s HTML, you might find CSS classes like .rt-table on different elements of the table. These CSS classes are undocumented and subject to change, so we recommend adding your own custom class names, or using themes to customize parts of the table that aren’t covered by the custom class names.

Theming

Themes provide a powerful way to customize table styling that can be reused across tables. You can either set theme variables to change the default styles (e.g., row stripe color), or add your own custom CSS to specific elements of the table.

To apply a theme, provide a reactableTheme() to theme:

reactable(
  iris[1:30, ],
  searchable = TRUE,
  striped = TRUE,
  highlight = TRUE,
  bordered = TRUE,
  theme = reactableTheme(
    borderColor = "#dfe2e5",
    stripedColor = "#f6f8fa",
    highlightColor = "#f0f5f9",
    cellPadding = "8px 12px",
    style = list(fontFamily = "-apple-system, BlinkMacSystemFont, Segoe UI, Helvetica, Arial, sans-serif"),
    searchInputStyle = list(width = "100%")
  )
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
4.6
3.4
1.4
0.3
setosa
5
3.4
1.5
0.2
setosa
4.4
2.9
1.4
0.2
setosa
4.9
3.1
1.5
0.1
setosa
1–10 of 30 rows

Global theme

To set the default theme for all tables, use the global reactable.theme option:

options(reactable.theme = reactableTheme(
  color = "hsl(233, 9%, 87%)",
  backgroundColor = "hsl(233, 9%, 19%)",
  borderColor = "hsl(233, 9%, 22%)",
  stripedColor = "hsl(233, 12%, 22%)",
  highlightColor = "hsl(233, 12%, 24%)",
  inputStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
  selectStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
  pageButtonHoverStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
  pageButtonActiveStyle = list(backgroundColor = "hsl(233, 9%, 28%)")
))

reactable(
  iris[1:30, ],
  filterable = TRUE,
  showPageSizeOptions = TRUE,
  striped = TRUE,
  highlight = TRUE,
  details = function(index) paste("Details for row", index)
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
4.6
3.4
1.4
0.3
setosa
5
3.4
1.5
0.2
setosa
4.4
2.9
1.4
0.2
setosa
4.9
3.1
1.5
0.1
setosa
1–10 of 30 rows
Show

Nested selectors

You can use nested CSS selectors in theme styles to target the current element, using & as the selector, or other child elements (just like in Sass). This is useful for adding pseudo-classes like &:hover, or adding styles in a certain context like .outer-container &.

For example, to highlight headers when sorting:

reactable(
  iris[1:5, ],
  columns = list(Sepal.Length = colDef(sortable = FALSE)),
  showSortable = TRUE,
  theme = reactableTheme(
    headerStyle = list(
      "&:hover[aria-sort]" = list(background = "hsl(0, 0%, 96%)"),
      "&[aria-sort='ascending'], &[aria-sort='descending']" = list(background = "hsl(0, 0%, 96%)"),
      borderColor = "#555"
    )
  )
)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Or to apply a dark theme when a parent element has a certain class, like .dark:

theme <- reactableTheme(
  style = list(".dark &" = list(color = "#fff", background = "#282a36")),
  cellStyle = list(".dark &" = list(borderColor = "rgba(255, 255, 255, 0.15)")),
  headerStyle = list(".dark &" = list(borderColor = "rgba(255, 255, 255, 0.15)")),
  paginationStyle = list(".dark &" = list(borderColor = "rgba(255, 255, 255, 0.15)")),
  rowHighlightStyle = list(".dark &" = list(background = "rgba(255, 255, 255, 0.04)")),
  pageButtonHoverStyle = list(".dark &" = list(background = "rgba(255, 255, 255, 0.08)")),
  pageButtonActiveStyle = list(".dark &" = list(background = "rgba(255, 255, 255, 0.1)"))
)

tbl <- reactable(iris[1:12, ], highlight = TRUE, defaultPageSize = 6, theme = theme)

# Simple theme toggle button
tags$button(onclick = "document.querySelector('.themeable-tbl').classList.toggle('dark')",
            "Toggle light/dark")

# Start with the dark theme enabled
div(class = "themeable-tbl dark", tbl)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa
5.4
3.9
1.7
0.4
setosa
1–6 of 12 rows

Dynamic theming

Themes can also be functions that return a reactableTheme() for context-specific styling.

For example, to style tables in RStudio R Notebooks only when a dark editor theme is active:

options(reactable.theme = function() {
  theme <- reactableTheme(
    color = "hsl(233, 9%, 85%)",
    backgroundColor = "hsl(233, 9%, 19%)",
    borderColor = "hsl(233, 9%, 22%)",
    stripedColor = "hsl(233, 12%, 22%)",
    highlightColor = "hsl(233, 12%, 24%)",
    inputStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
    selectStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
    pageButtonHoverStyle = list(backgroundColor = "hsl(233, 9%, 25%)"),
    pageButtonActiveStyle = list(backgroundColor = "hsl(233, 9%, 28%)")
  )

  if (isTRUE(getOption("rstudio.notebook.executing"))) {
    if (requireNamespace("rstudioapi", quietly = TRUE) && rstudioapi::getThemeInfo()$dark) {
      return(theme)
    }
  }
})

Column Groups

You can create column groups by passing a list of colGroup() definitions to columnGroups:

reactable(
  iris[1:5, ],
  columns = list(
    Sepal.Length = colDef(name = "Length"),
    Sepal.Width = colDef(name = "Width"),
    Petal.Length = colDef(name = "Length"),
    Petal.Width = colDef(name = "Width")
  ),
  columnGroups = list(
    colGroup(name = "Sepal", columns = c("Sepal.Length", "Sepal.Width")),
    colGroup(name = "Petal", columns = c("Petal.Length", "Petal.Width"))
  )
)
Sepal
Petal
Length
Width
Length
Width
Species
5.1
3.5
1.4
0.2
setosa
4.9
3
1.4
0.2
setosa
4.7
3.2
1.3
0.2
setosa
4.6
3.1
1.5
0.2
setosa
5
3.6
1.4
0.2
setosa

Column Resizing

You can make columns resizable by setting resizable to TRUE:

reactable(MASS::Cars93[1:5, ], resizable = TRUE, wrap = FALSE, bordered = TRUE)
Manufacturer
Model
Type
Min.Price
Price
Max.Price
MPG.city
MPG.highway
AirBags
DriveTrain
Cylinders
EngineSize
Horsepower
RPM
Rev.per.mile
Man.trans.avail
Fuel.tank.capacity
Passengers
Length
Wheelbase
Width
Turn.circle
Rear.seat.room
Luggage.room
Weight
Origin
Make
Acura
Integra
Small
12.9
15.9
18.8
25
31
None
Front
4
1.8
140
6300
2890
Yes
13.2
5
177
102
68
37
26.5
11
2705
non-USA
Acura Integra
Acura
Legend
Midsize
29.2
33.9
38.7
18
25
Driver & Passenger
Front
6
3.2
200
5500
2335
Yes
18
5
195
115
71
38
30
15
3560
non-USA
Acura Legend
Audi
90
Compact
25.9
29.1
32.3
20
26
Driver only
Front
6
2.8
172
5500
2280
Yes
16.9
5
180
102
67
37
28
14
3375
non-USA
Audi 90
Audi
100
Midsize
30.8
37.7
44.6
19
26
Driver & Passenger
Front
6
2.8
172
5500
2535
Yes
21.1
6
193
106
70
37
31
17
3405
non-USA
Audi 100
BMW
535i
Midsize
23.7
30
36.2
22
30
Driver only
Rear
4
3.5
208
5700
2545
Yes
21.1
4
186
109
69
39
27
13
3640
non-USA
BMW 535i

Sticky Columns

You can make columns sticky when scrolling horizontally using the sticky argument in colDef() or colGroup(). Set sticky to either "left" or "right" to make the column stick to the left or right side.

reactable(
  MASS::Cars93[1:5, ],
  columns = list(
    Manufacturer = colDef(
      sticky = "left",
      # Add a right border style to visually distinguish the sticky column
      style = list(borderRight = "1px solid #eee"),
      headerStyle = list(borderRight = "1px solid #eee")
    ),
    Make = colDef(
      sticky = "right",
      # Add a left border style to visually distinguish the sticky column
      style = list(borderLeft = "1px solid #eee"),
      headerStyle = list(borderLeft = "1px solid #eee")
    )
  ),
  defaultColDef = colDef(minWidth = 150)
)
Manufacturer
Model
Type
Min.Price
Price
Max.Price
MPG.city
MPG.highway
AirBags
DriveTrain
Cylinders
EngineSize
Horsepower
RPM
Rev.per.mile
Man.trans.avail
Fuel.tank.capacity
Passengers
Length
Wheelbase
Width
Turn.circle
Rear.seat.room
Luggage.room
Weight
Origin
Make
Acura
Integra
Small
12.9
15.9
18.8
25
31
None
Front
4
1.8
140
6300
2890
Yes
13.2
5
177
102
68
37
26.5
11
2705
non-USA
Acura Integra
Acura
Legend
Midsize
29.2
33.9
38.7
18
25
Driver & Passenger
Front
6
3.2
200
5500
2335
Yes
18
5
195
115
71
38
30
15
3560
non-USA
Acura Legend
Audi
90
Compact
25.9
29.1
32.3
20
26
Driver only
Front
6
2.8
172
5500
2280
Yes
16.9
5
180
102
67
37
28
14
3375
non-USA
Audi 90
Audi
100
Midsize
30.8
37.7
44.6
19
26
Driver & Passenger
Front
6
2.8
172
5500
2535
Yes
21.1
6
193
106
70
37
31
17
3405
non-USA
Audi 100
BMW
535i
Midsize
23.7
30
36.2
22
30
Driver only
Rear
4
3.5
208
5700
2545
Yes
21.1
4
186
109
69
39
27
13
3640
non-USA
BMW 535i

Multiple sticky columns

# Background style to visually distinguish sticky columns
sticky_style <- list(backgroundColor = "#f7f7f7")

reactable(
  MASS::Cars93[1:5, ],
  columns = list(
    Manufacturer = colDef(
      sticky = "left",
      style = sticky_style,
      headerStyle = sticky_style
    ),
    Model = colDef(
      sticky = "left",
      style = sticky_style,
      headerStyle = sticky_style
    ),
    Type = colDef(
      sticky = "left",
      style = sticky_style,
      headerStyle = sticky_style
    )
  ),
  resizable = TRUE,
  wrap = FALSE,
  bordered = TRUE
)
Manufacturer
Model
Type
Min.Price
Price
Max.Price
MPG.city
MPG.highway
AirBags
DriveTrain
Cylinders
EngineSize
Horsepower
RPM
Rev.per.mile
Man.trans.avail
Fuel.tank.capacity
Passengers
Length
Wheelbase
Width
Turn.circle
Rear.seat.room
Luggage.room
Weight
Origin
Make
Acura
Integra
Small
12.9
15.9
18.8
25
31
None
Front
4
1.8
140
6300
2890
Yes
13.2
5
177
102
68
37
26.5
11
2705
non-USA
Acura Integra
Acura
Legend
Midsize
29.2
33.9
38.7
18
25
Driver & Passenger
Front
6
3.2
200
5500
2335
Yes
18
5
195
115
71
38
30
15
3560
non-USA
Acura Legend
Audi
90
Compact
25.9
29.1
32.3
20
26
Driver only
Front
6
2.8
172
5500
2280
Yes
16.9
5
180
102
67
37
28
14
3375
non-USA
Audi 90
Audi
100
Midsize
30.8
37.7
44.6
19
26
Driver & Passenger
Front
6
2.8
172
5500
2535
Yes
21.1
6
193
106
70
37
31
17
3405
non-USA
Audi 100
BMW
535i
Midsize
23.7
30
36.2
22
30
Driver only
Rear
4
3.5
208
5700
2545
Yes
21.1
4
186
109
69
39
27
13
3640
non-USA
BMW 535i

Sticky column groups

If a column group is sticky, all columns in the group will automatically be made sticky.

reactable(
  MASS::Cars93[1:5, ],
  columnGroups = list(
    colGroup("Make", columns = c("Manufacturer", "Model"), sticky = "left"),
    colGroup("Price", columns = c("Min.Price", "Price", "Max.Price"), sticky = "left")
  ),
  defaultColDef = colDef(footer = "Footer"),
  resizable = TRUE,
  wrap = FALSE,
  bordered = TRUE
)
Make
Price
Manufacturer
Model
Type
Min.Price
Price
Max.Price
MPG.city
MPG.highway
AirBags
DriveTrain
Cylinders
EngineSize
Horsepower
RPM
Rev.per.mile
Man.trans.avail
Fuel.tank.capacity
Passengers
Length
Wheelbase
Width
Turn.circle
Rear.seat.room
Luggage.room
Weight
Origin
Make
Acura
Integra
Small
12.9
15.9
18.8
25
31
None
Front
4
1.8
140
6300
2890
Yes
13.2
5
177
102
68
37
26.5
11
2705
non-USA
Acura Integra
Acura
Legend
Midsize
29.2
33.9
38.7
18
25
Driver & Passenger
Front
6
3.2
200
5500
2335
Yes
18
5
195
115
71
38
30
15
3560
non-USA
Acura Legend
Audi
90
Compact
25.9
29.1
32.3
20
26
Driver only
Front
6
2.8
172
5500
2280
Yes
16.9
5
180
102
67
37
28
14
3375
non-USA
Audi 90
Audi
100
Midsize
30.8
37.7
44.6
19
26
Driver & Passenger
Front
6
2.8
172
5500
2535
Yes
21.1
6
193
106
70
37
31
17
3405
non-USA
Audi 100
BMW
535i
Midsize
23.7
30
36.2
22
30
Driver only
Rear
4
3.5
208
5700
2545
Yes
21.1
4
186
109
69
39
27
13
3640
non-USA
BMW 535i

Row Names and Row Headers

Row names

Row names are shown by default if present. You can customize the row names column using ".rownames" as the column name:

reactable(
  USPersonalExpenditure,
  columns = list(
    .rownames = colDef(name = "Category", sortable = TRUE)
  )
)
Category
1940
1945
1950
1955
1960
Food and Tobacco
22.2
44.5
59.6
73.2
86.8
Household Operation
10.5
15.5
29
36.5
46.2
Medical and Health
3.53
5.76
9.71
14
21.1
Personal Care
1.04
1.98
2.45
3.4
5.4
Private Education
0.341
0.974
1.8
2.6
3.64

If row names haven’t been set explicitly, you can force them to show by setting rownames to TRUE:

reactable(iris[1:5, ], rownames = TRUE)
Sepal.Length
Sepal.Width
Petal.Length
Petal.Width
Species
1
5.1
3.5
1.4
0.2
setosa
2
4.9
3
1.4
0.2
setosa
3
4.7
3.2
1.3
0.2
setosa
4
4.6
3.1
1.5
0.2
setosa
5
5
3.6
1.4
0.2
setosa

Row headers

You can mark up cells in a column as row headers by setting rowHeader to TRUE in colDef().

Use this to help users navigate the table using assistive technologies. When cells are marked up as row headers, assistive technologies will read them aloud while navigating through cells in the table.

Cells in the row names column are automatically marked up as row headers.

data <- MASS::Cars93[1:5, c("Make", "Type", "Price", "MPG.city", "AirBags")]

reactable(
  data,
  columns = list(
    Make = colDef(rowHeader = TRUE, style = list(fontWeight = 600))
  ),
  bordered = TRUE
)
Make
Type
Price
MPG.city
AirBags
Acura Integra
Small
15.9
25
None
Acura Legend
Midsize
33.9
18
Driver & Passenger
Audi 90
Compact
29.1
20
Driver only
Audi 100
Midsize
37.7
19
Driver & Passenger
BMW 535i
Midsize
30
22
Driver only

Cell Click Actions

You can add cell click actions using the onClick argument, which accepts the following values:

  • "expand" to expand the row
  • "select" to select the row
  • A JavaScript function for a custom action, e.g., sending the click event to Shiny

Expand on click