Tidyverse ’_at’ variants

tldr: tidyverse function variants take slightly different input. Testing out a variant or two can save you a lot of debugging time.

In tidyverse watch out for inconsistencies in function versions. There are variants of common functions (e.g. mutate(), mutate_all(), mutate_at()) don’t necessarily behave the same way (or how you would expect).

Here, I was applying an operation to a grouped df where each Experiment contains several FileNames with multiple observations in each. To keep everything reusable I’m using exp instead of Experiment to select the right col.

> exp = "Experiment"
> rec = "FileName"

> df %>%
+     dplyr::select(
+       exp, rec, r11, r12
+     )
# A tibble: 564 x 4
   Experiment FileName           r11   r12
   <chr>      <chr>            <dbl> <dbl>
 1 190808a    190808a_0020.abf  5.06 0.150
 2 190808a    190808a_0020.abf  5.13 0.160
 3 190808a    190808a_0020.abf  5.11 0.122
 4 190808a    190808a_0020.abf  2.49 0.152
 5 190808a    190808a_0020.abf  2.49 0.195
# ... with 559 more rows

As soon as we do the same thing with group_by() we don’t get the right column even though select() didn’t have an issue with exp.

> df %>%
+     dplyr::select(
+       exp, rec, r11, r12
+     ) %>%
+     group_by(exp, rec)
Error: Column `exp` is unknown

So we can try explicitly selecting the columns we want as groupings.

>     df %>%
+     dplyr::select(
+       exp, rec, r11, r12
+     ) %>%
+     group_by(vars(exp, rec))
Error: Column `vars(exp, rec)` must be length 564 (the number of rows) or one, not 2

No dice there. vars() is designed to work with the _at variants so we can try that. et voilà!

> df %>%
+     dplyr::select(
+       exp, rec, r11, r12
+     ) %>%
+     group_by_at(vars(exp, rec))

# A tibble: 564 x 4
# Groups:   Experiment, FileName [69]
   Experiment FileName           r11   r12
   <chr>      <chr>            <dbl> <dbl>
 1 190808a    190808a_0020.abf  5.06 0.150
 2 190808a    190808a_0020.abf  5.13 0.160
 3 190808a    190808a_0020.abf  5.11 0.122
 4 190808a    190808a_0020.abf  2.49 0.152
 5 190808a    190808a_0020.abf  2.49 0.195
# ... with 559 more rows