If you have a list-column, this makes each element of the list its own row. unnest() can handle list-columns that contain atomic vectors, lists, or data frames (but not a mixture of the different types).

unnest(data, ..., .drop = NA, .id = NULL, .sep = NULL,
  .preserve = NULL)

Arguments

data

A data frame.

...

Specification of columns to unnest. Use bare variable names or functions of variables. If omitted, defaults to all list-cols.

.drop

Should additional list columns be dropped? By default, unnest will drop them if unnesting the specified columns requires the rows to be duplicated.

.id

Data frame identifier - if supplied, will create a new column with name .id, giving a unique identifier. This is most useful if the list column is named.

.sep

If non-NULL, the names of unnested data frame columns will combine the name of the original list-col with the names from nested data frame, separated by .sep.

.preserve

Optionally, list-columns to preserve in the output. These will be duplicated in the same way as atomic vectors. This has dplyr::select semantics so you can preserve multiple variables with .preserve = c(x, y) or .preserve = starts_with("list").

Details

If you unnest multiple columns, parallel entries must have the same length or number of rows (if a data frame).

See also

nest() for the inverse operation.

Examples

library(dplyr) df <- tibble( x = 1:3, y = c("a", "d,e,f", "g,h") ) df %>% transform(y = strsplit(y, ",")) %>% unnest(y)
#> x y #> 1 1 a #> 2 2 d #> 3 2 e #> 4 2 f #> 5 3 g #> 6 3 h
# Or just df %>% unnest(y = strsplit(y, ","))
#> # A tibble: 6 x 2 #> x y #> <int> <chr> #> 1 1 a #> 2 2 d #> 3 2 e #> 4 2 f #> 5 3 g #> 6 3 h
# It also works if you have a column that contains other data frames! df <- tibble( x = 1:2, y = list( tibble(z = 1), tibble(z = 3:4) ) ) df %>% unnest(y)
#> # A tibble: 3 x 2 #> x z #> <int> <dbl> #> 1 1 1 #> 2 2 3 #> 3 2 4
# You can also unnest multiple columns simultaneously df <- tibble( a = list(c("a", "b"), "c"), b = list(1:2, 3), c = c(11, 22) ) df %>% unnest(a, b)
#> # A tibble: 3 x 3 #> c a b #> <dbl> <chr> <dbl> #> 1 11 a 1 #> 2 11 b 2 #> 3 22 c 3
# If you omit the column names, it'll unnest all list-cols df %>% unnest()
#> # A tibble: 3 x 3 #> c a b #> <dbl> <chr> <dbl> #> 1 11 a 1 #> 2 11 b 2 #> 3 22 c 3
# You can also choose to preserve one or more list-cols df %>% unnest(a, .preserve = b)
#> # A tibble: 3 x 3 #> c b a #> <dbl> <list> <chr> #> 1 11 <int [2]> a #> 2 11 <int [2]> b #> 3 22 <dbl [1]> c
# Nest and unnest are inverses df <- data.frame(x = c(1, 1, 2), y = 3:1) df %>% nest(y)
#> x data #> 1 1 3, 2 #> 2 2 1
df %>% nest(y) %>% unnest()
#> x y #> 1 1 3 #> 2 1 2 #> 3 2 1
# If you have a named list-column, you may want to supply .id df <- tibble( x = 1:2, y = list(a = 1, b = 3:4) ) unnest(df, .id = "name")
#> # A tibble: 3 x 3 #> x y name #> <int> <dbl> <chr> #> 1 1 1 a #> 2 2 3 b #> 3 2 4 b