1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
|
## Tips for saving recipes and filtering columns
When creating variable selections:
* If you are using column filtering steps, such as `step_corr()`, try to avoid hardcoding specific variable names in downstream steps in case those columns are removed by the filter. Instead, use [dplyr::any_of()] and [dplyr::all_of()].
* [dplyr::any_of()] will be tolerant if a column has been removed.
* [dplyr::all_of()] will fail unless all of the columns are present in the data.
* For both of these functions, if you are going to save the recipe as a binary object to use in another R session, try to avoid referring to a vector in your workspace.
* Preferred: `any_of(!!var_names)`
* Avoid: `any_of(var_names)`
Some examples:
```{r, error=TRUE}
some_vars <- names(mtcars)[4:6]
# No filter steps, OK for not saving the recipe
rec_1 <-
recipe(mpg ~ ., data = mtcars) %>%
step_log(all_of(some_vars)) %>%
prep()
# No filter steps, saving the recipe
rec_2 <-
recipe(mpg ~ ., data = mtcars) %>%
step_log(!!!some_vars) %>%
prep()
# This fails since `wt` is not in the data
recipe(mpg ~ ., data = mtcars) %>%
step_rm(wt) %>%
step_log(!!!some_vars) %>%
prep()
# Best for filters (using any_of()) and when
# saving the recipe
rec_4 <-
recipe(mpg ~ ., data = mtcars) %>%
step_rm(wt) %>%
step_log(any_of(!!some_vars)) %>%
# equal to step_log(any_of(c("hp", "drat", "wt")))
prep()
```
|
