create new variables from formulas stored in a list using dplyr

Question

I have a list of formulas which I want to use to create new variables with mutate. For each formula stored in my list, I want to create a new variable. I want to automatically generate one variable for each element in my list. This is my code

library("dplyr")
library("purrr")
library("formula.tools")

t<-10 #just some constant which needs to be included (and found within my pipe)

ut <- list( # my list with the formulas as elements
  v1 = V.1 ~ A * B*t,
  v2 = V.2 ~ A+B)

data <- tibble(A=rnorm(10),B=runif(10)) %>%  ## the dataset
  mutate(!!lhs(ut[["v1"]]) := !!rhs(ut[["v1"]]),
         !!lhs(ut[["v2"]]) := !!rhs(ut[["v2"]]))

This works fine. However, I do not want to write this for each element in my function. I want to mutate to take each element of the list, and apply the formula, i.e. I need some kind of loop. I tried with across, but across requires existing variables.

I tried to wrap it into a function and use map, but this didn't work

by_formula <- function(equation){
 !!lhs(equation) := !!rhs(equation) 
}

data <- tibble(A=rnorm(10),B=runif(10)) %>%
  mutate(map(ut,by_formula))

I appreciate any hints how to do this so that I do not need to worry about the length of the list. This should be part of a function where the length of the list depends on the user input.

akrun · Accepted Answer · 2023-01-07 01:54:55Z

1

Here is one way

library(dplyr)
library(purrr)
library(formula.tools)
by_formula <- function(equation){
# //! cur_data_all may get deprecated in favor of pick
# pick(everything()) %>%
 cur_data_all() %>%
 transmute(!!lhs(equation) := !!rhs(equation) )
}

 tibble(A=rnorm(10),B=runif(10)) %>% 
    mutate(map_dfc(ut, by_formula))

-output

# A tibble: 10 × 4
        A       B      V.1     V.2
    <dbl>   <dbl>    <dbl>   <dbl>
 1  1.73  0.0770    1.33    1.80  
 2 -1.46  0.894   -13.0    -0.562 
 3 -0.620 0.804    -4.99    0.184 
 4  0.834 0.524     4.37    1.36  
 5 -0.980 0.00581  -0.0569 -0.974 
 6 -0.361 0.316    -1.14   -0.0444
 7  1.73  0.833    14.4     2.57  
 8  1.71  0.512     8.74    2.22  
 9  0.233 0.944     2.20    1.18  
10 -0.832 0.474    -3.94   -0.358

edited Jan 7, 2023 at 1:54

answered Jan 7, 2023 at 0:45

akrun

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