Conditional mutate function

Perform mutate if condition is met. This function is a simple wrapper for mutate.

conditional_mutate(df1, cond, LHS, RHS)

Arguments

df1	A dataframe
cond	A logical value indicating if mutate should be performed
varName	Name of variable to create

See also

Other conditional dplyr: conditional_filter, conditional_range_filter, conditional_select

Examples

mtcars %>%
  dplyr::as_tibble() %>%
  conditional_mutate(
    exists("cyl", where = .),
    LHS = cyl2,
    RHS = cyl * 2
  )
#> # A tibble: 32 x 12
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  cyl2
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4    12
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4    12
#>  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1     8
#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1    12
#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2    16
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1    12
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4    16
#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2     8
#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2     8
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4    12
#> # … with 22 more rows

mtcars %>%
  dplyr::as_tibble() %>%
  conditional_mutate(
    exists("cyl2", where = .),
    LHS = cyl4,
    RHS = cyl2 * 2
  )
#> # A tibble: 32 x 11
#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1  21       6  160    110  3.9   2.62  16.5     0     1     4     4
#>  2  21       6  160    110  3.9   2.88  17.0     0     1     4     4
#>  3  22.8     4  108     93  3.85  2.32  18.6     1     1     4     1
#>  4  21.4     6  258    110  3.08  3.22  19.4     1     0     3     1
#>  5  18.7     8  360    175  3.15  3.44  17.0     0     0     3     2
#>  6  18.1     6  225    105  2.76  3.46  20.2     1     0     3     1
#>  7  14.3     8  360    245  3.21  3.57  15.8     0     0     3     4
#>  8  24.4     4  147.    62  3.69  3.19  20       1     0     4     2
#>  9  22.8     4  141.    95  3.92  3.15  22.9     1     0     4     2
#> 10  19.2     6  168.   123  3.92  3.44  18.3     1     0     4     4
#> # … with 22 more rows