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dplyr's pick() function lets you select columns *within select(), count(), or mutate() activities *. For ex.
df %>% mutate(rank = dense_rank(pick(x, y)))
OR
df %>% count(pick(starts_with("z")))
dplyr.tidyverse.orgSelect a subset of columns — pickpick() provides a way to easily select a subset of columns from your data
using select() semantics while inside a
"data-masking" function like mutate() or
summarise(). pick() returns a data frame containing the selected columns
for the current group.
pick() is complementary to across():
With pick(), you typically apply a function to the full data frame.
With across(), you typically apply a function to each column.
![library(tidyAML)
library(dplyr)
create_model_spec(
.parsnip_eng = list("lm","glm"),
.parsnip_fns = list("linear_reg")
) |>
pull(.model_spec)
[[1]]
Linear Regression Model Specification (regression)
Computational engine: lm
[[2]]
Linear Regression Model Specification (regression)
Computational engine: glm](https://media.mstdn.social/media_attachments/files/114/313/636/555/433/614/original/46d6b02551206089.png "library(tidyAML)
library(dplyr)
create_model_spec(
.parsnip_eng = list(\"lm\",\"glm\"),
.parsnip_fns = list(\"linear_reg\")
) |>
pull(.model_spec)
[[1]]
Linear Regression Model Specification (regression)
Computational engine: lm
[[2]]
Linear Regression Model Specification (regression)
Computational engine: glm")
