Mutate columns in data.frame

Analogous function for mutate in dplyr.This is a little different from dt_mutate,because it prohibit the in place replacement.

mutate_dt(data, ..., by)

Arguments

data	data.frame
...	List of variables or name-value pairs of summary/modifications functions.
by	unquoted name of grouping variable of list of unquoted names of grouping variables. For details see data.table

Value

data.table

See also

mutate,dt_mutate

Examples

iris %>% mutate_dt(one = 1)
#>      Sepal.Length Sepal.Width Petal.Length Petal.Width   Species one
#>   1:          5.1         3.5          1.4         0.2    setosa   1
#>   2:          4.9         3.0          1.4         0.2    setosa   1
#>   3:          4.7         3.2          1.3         0.2    setosa   1
#>   4:          4.6         3.1          1.5         0.2    setosa   1
#>   5:          5.0         3.6          1.4         0.2    setosa   1
#>  ---                                                                
#> 146:          6.7         3.0          5.2         2.3 virginica   1
#> 147:          6.3         2.5          5.0         1.9 virginica   1
#> 148:          6.5         3.0          5.2         2.0 virginica   1
#> 149:          6.2         3.4          5.4         2.3 virginica   1
#> 150:          5.9         3.0          5.1         1.8 virginica   1
mtcars  %>%
  head(3) %>%
  mutate_dt(
    cyl2 = cyl * 2,
    cyl4 = cyl2 * 2
  )
#>     mpg cyl disp  hp drat    wt  qsec vs am gear carb cyl2 cyl4
#> 1: 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4   12   24
#> 2: 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4   12   24
#> 3: 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1    8   16

# window functions are useful for grouped mutates
iris %>%
  mutate_dt(
    rank = rank(-Sepal.Length, ties.method = "min"),
    keyby = Species)
#>      Sepal.Length Sepal.Width Petal.Length Petal.Width   Species rank
#>   1:          5.1         3.5          1.4         0.2    setosa   15
#>   2:          4.9         3.0          1.4         0.2    setosa   31
#>   3:          4.7         3.2          1.3         0.2    setosa   40
#>   4:          4.6         3.1          1.5         0.2    setosa   42
#>   5:          5.0         3.6          1.4         0.2    setosa   23
#>  ---                                                                 
#> 146:          6.7         3.0          5.2         2.3 virginica   18
#> 147:          6.3         2.5          5.0         1.9 virginica   32
#> 148:          6.5         3.0          5.2         2.0 virginica   23
#> 149:          6.2         3.4          5.4         2.3 virginica   38
#> 150:          5.9         3.0          5.1         1.8 virginica   44