Unite multiple columns into one by pasting strings together

Convenience function to paste together multiple columns into one. Analogous to tidyr::unite.

unite(.data, united_colname, ..., sep = "_", remove = FALSE, na2char = FALSE)

Arguments

.data	A data frame.
united_colname	The name of the new column, string only.
...	A selection of columns. If want to select all columns, pass "" to the parameter. See example.
sep	Separator to use between values.
remove	If TRUE, remove input columns from output data frame.
na2char	If FALSE, missing values would be merged into NA, otherwise NA is treated as character "NA". This is different from tidyr.

Value

A data.table

See also

unite,separate

Examples

df <- CJ(x = c("a", NA), y = c("b", NA))
df
#> Key: <x, y>
#>         x      y
#>    <char> <char>
#> 1:   <NA>   <NA>
#> 2:   <NA>      b
#> 3:      a   <NA>
#> 4:      a      b

# Treat missing value as NA, default
df %>% unite("z", x:y, remove = FALSE)
#> Key: <x, y>
#>         x      y      z
#>    <char> <char> <char>
#> 1:   <NA>   <NA>   <NA>
#> 2:   <NA>      b   <NA>
#> 3:      a   <NA>   <NA>
#> 4:      a      b    a_b
# Treat missing value as character "NA"
df %>% unite("z", x:y, na2char = TRUE, remove = FALSE)
#> Key: <x, y>
#>         x      y      z
#>    <char> <char> <char>
#> 1:   <NA>   <NA>  NA_NA
#> 2:   <NA>      b   NA_b
#> 3:      a   <NA>   a_NA
#> 4:      a      b    a_b
# the unite has memory, "z" would not be removed in new operations
# here we remove the original columns ("x" and "y")
df %>% unite("xy", x:y,remove = TRUE)
#>         z     xy
#>    <char> <char>
#> 1:  NA_NA   <NA>
#> 2:   NA_b   <NA>
#> 3:   a_NA   <NA>
#> 4:    a_b    a_b

# Select all columns
iris %>% as.data.table %>% unite("merged_name","")
#>      Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
#>             <num>       <num>        <num>       <num>    <fctr>
#>   1:          5.1         3.5          1.4         0.2    setosa
#>   2:          4.9         3.0          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:          5.0         3.6          1.4         0.2    setosa
#>  ---                                                            
#> 146:          6.7         3.0          5.2         2.3 virginica
#> 147:          6.3         2.5          5.0         1.9 virginica
#> 148:          6.5         3.0          5.2         2.0 virginica
#> 149:          6.2         3.4          5.4         2.3 virginica
#> 150:          5.9         3.0          5.1         1.8 virginica
#>                    merged_name
#>                         <char>
#>   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
#>  ---                          
#> 146:   6.7_3_5.2_2.3_virginica
#> 147:   6.3_2.5_5_1.9_virginica
#> 148:     6.5_3_5.2_2_virginica
#> 149: 6.2_3.4_5.4_2.3_virginica
#> 150:   5.9_3_5.1_1.8_virginica