I need to be able to change iteration number in each seperated line of one dplyr code. I have prepared and example of 'by hand' approach and what I need to do in 'pseudo steps'.
library(tidyverse)
cr <-
mtcars %>%
group_by(gear) %>%
nest()
# This is 'by-hand' approach of what I would like to do - How to automate it? E.g. we do not know all values of 'carb'
cr$data[[1]] %>%
mutate(VARIABLE1 =
case_when(carb == 1 ~ hp/mpg,
TRUE ~ 0)) %>%
mutate(VARIABLE2 =
case_when(carb == 2 ~ hp/mpg,
TRUE ~ 0)) %>%
mutate(VARIABLE4 =
case_when(carb == 4 ~ hp/mpg,
TRUE ~ 0))
# This is a pseodu-idea of what I need to do. Is the any way how to change iteration number in ONE dplyr code?
vals <- cr$data[[1]] %>% pull(carb) %>% sort %>% unique()
for (i in vals) {
message(i)
cr$data[[1]] %>%
mutate(paste('VARIABLE', i, sep = '') = case_when(carb == i ~ hp/mpg, # At this line, all i shall be first element of vals
TRUE ~ 0)) %>%
mutate(paste('VARIABLE', i, sep = '') = case_when(carb == i ~ hp/mpg, # At this line, all i shall be second element of vals
TRUE ~ 0)) %>%
mutate(paste('VARIABLE', i, sep = '') = case_when(carb == i ~ hp/mpg, # At this line, all i shall be third element of vals
TRUE ~ 0))
}
is there any trick maybe using purrr
package or other solution as well?
I need to iterate over some unique values of some variable. And for each unique value create a new column in dataframe. I need to automatize this, however I am not able to do so on my own.