Split a string into rows

Each of these functions takes a string and splits it into multiple rows:

• separate_longer_delim() splits by a delimiter.

• separate_longer_position() splits by a fixed width.

Usage

separate_longer_delim(data, cols, delim, ...)

separate_longer_position(data, cols, width, ..., keep_empty = FALSE)

Arguments

data

A data frame.

cols

<tidy-select> Columns to separate.

delim

For separate_longer_delim(), a string giving the delimiter between values. By default, it is interpreted as a fixed string; use stringr::regex() and friends to split in other ways.

...

These dots are for future extensions and must be empty.

width

For separate_longer_position(), an integer giving the number of characters to split by.

keep_empty

By default, you'll get ceiling(nchar(x) / width) rows for each observation. If nchar(x) is zero, this means the entire input row will be dropped from the output. If you want to preserve all rows, use keep_empty = TRUE to replace size-0 elements with a missing value.

Value

A data frame based on data. It has the same columns, but different rows.

Examples

df <- tibble(id = 1:4, x = c("x", "x y", "x y z", NA))
df %>% separate_longer_delim(x, delim = " ")
#> # A tibble: 7 × 2
#>      id x    
#>   <int> <chr>
#> 1     1 x    
#> 2     2 x    
#> 3     2 y    
#> 4     3 x    
#> 5     3 y    
#> 6     3 z    
#> 7     4 NA   

# You can separate multiple columns at once if they have the same structure
df <- tibble(id = 1:3, x = c("x", "x y", "x y z"), y = c("a", "a b", "a b c"))
df %>% separate_longer_delim(c(x, y), delim = " ")
#> # A tibble: 6 × 3
#>      id x     y    
#>   <int> <chr> <chr>
#> 1     1 x     a    
#> 2     2 x     a    
#> 3     2 y     b    
#> 4     3 x     a    
#> 5     3 y     b    
#> 6     3 z     c    

# Or instead split by a fixed length
df <- tibble(id = 1:3, x = c("ab", "def", ""))
df %>% separate_longer_position(x, 1)
#> # A tibble: 5 × 2
#>      id x    
#>   <int> <chr>
#> 1     1 a    
#> 2     1 b    
#> 3     2 d    
#> 4     2 e    
#> 5     2 f    
df %>% separate_longer_position(x, 2)
#> # A tibble: 3 × 2
#>      id x    
#>   <int> <chr>
#> 1     1 ab   
#> 2     2 de   
#> 3     2 f    
df %>% separate_longer_position(x, 2, keep_empty = TRUE)
#> # A tibble: 4 × 2
#>      id x    
#>   <int> <chr>
#> 1     1 ab   
#> 2     2 de   
#> 3     2 f    
#> 4     3 NA