tribble

tribble(...)

Description

tribble() builds a tibble by laying out data row by row, reading left to right — the opposite of tibble() which takes column vectors. It is designed for small tables of data where readability matters, such as lookup tables, configuration data, or examples in documentation.

The column names are declared first using the formula syntax (~name), and the actual values follow. This makes the structure immediately visible when you read the code.

tribble() is part of the tibble package, which provides the tbl_df class — a stricter, more predictable reimagining of data.frame.

Arguments

…

Name-value pairs specifying column names and data. Column names must use the formula syntax (~column_name) and must appear before the corresponding values.

tribble(
  ~name, ~age,
  "Alice", 29,
  "Bob", 34
)
# # A tibble: 2 × 2
#   name   age
#   <chr> <dbl>
# 1 Alice   29
# 2 Bob     34

The ... arguments are processed with rlang::list2(), which means they support tidyeval unquoting via !! and unquote-splice via !!!.

tribble vs tibble vs data.frame

The three functions create rectangular data in R but with different layouts and constraints:

Feature	tribble()	tibble()	data.frame()
Layout	Row-by-row	Column-by-column	Column-by-column
Column references	Not supported	Sequential evaluation	No
List columns	Auto-detected	Auto-detected	No
Row names	No	No	Yes
Partial match	Errors	Errors	Silent NULL
Vector recycling	Errors	Errors	Silent warning

# tibble: columns evaluated sequentially
tibble(x = 1:3, y = x * 2)
# # A tibble: 3 × 2
#       x     y
#   <int> <dbl>
# 1     1     2
# 2     2     4
# 3     3     6

# tribble: no sequential references — use tribble for this data layout
tribble(
  ~x, ~y,
  1, 2,
  2, 4,
  3, 6
)
# # A tibble: 3 × 2
#       x     y
#   <int> <dbl>
# 1     1     2
# 2     2     4
# 3     3     6

List Columns

If any cell in tribble contains a vector longer than one element, that column becomes a list column (type <list>):

tribble(
  ~label, ~values,
  "first", 1:3,
  "second", 4:6
)
# # A tibble: 2 × 2
#   label values
#   <chr> <list>
# 1 first   <int [3]>
# 2 second  <int [3]>

List columns are useful for storing ragged or hierarchical data. Access individual elements with purrr::map() or dplyr::pull() followed by indexing.

Type Coercion

tribble() infers column types from the data you provide, the same way tibble() does. Characters stay character, numbers stay numeric. If you need a specific type — for example, storing a date string as a Date object — use dplyr::mutate() with across() after creation:

tribble(
  ~name, ~joined, ~score,
  "Alice", "2020-01-15", "88",
  "Bob", "2019-07-22", "72"
) |>
  dplyr::mutate(
    dplyr::across(joined, as.Date),
    dplyr::across(score, as.integer)
  )
# # A tibble: 2 × 3
#   name  joined    score
#   <chr> <date>    <int>
# 1 Alice 2020-01-15    88
# 2 Bob   2019-07-22    72

See Also

• filter() — filter rows of a tibble by condition
• pivot_longer() — reshape data from wide to long format
• rownames() — get or set row names of a data frame or tibble