unnest {tidyr} | R Documentation |
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)
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,
|
.id |
Data frame identifier - if supplied, will create a new column
with name |
.sep |
If non- |
.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
|
If you unnest multiple columns, parallel entries must have the same length or number of rows (if a data frame).
nest()
for the inverse operation.
library(dplyr) df <- tibble( x = 1:3, y = c("a", "d,e,f", "g,h") ) df %>% transform(y = strsplit(y, ",")) %>% unnest(y) # Or just df %>% unnest(y = strsplit(y, ",")) # 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) # 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) # If you omit the column names, it'll unnest all list-cols df %>% unnest() # You can also choose to preserve one or more list-cols df %>% unnest(a, .preserve = b) # Nest and unnest are inverses df <- data.frame(x = c(1, 1, 2), y = 3:1) df %>% nest(y) df %>% nest(y) %>% unnest() # 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")