multiple ifelse statements and dplyr pipes, not recognizing 2nd object

Question

What I'm trying to do: take columns from one data frame, recode them using ifelse statements, and move them to a new data frame, all the while using dplyr and pipes to do it in one shot.

Issue: The code works fine for the with just one column but I am running into problems once R encounters more than one column in same line of code. The second column is not recognized and R throws an error. I get the following error:

Error in mutate_impl(.data, dots) : Evaluation error: object 'var2_orig' not found.

Any thoughts on why this is? There may also be an easier way to this without using ifelse statements. I am open to suggestions on this front as well, but I am still curious about how to do this with ifelse and why the error with more than one column. Many thanks.

Sample code:

library(tidyverse)

# creating fake data set
df_orig <- data_frame(var1_orig = sample(1:3, 50, replace = T),
                  var2_orig = sample(-2:2, 50, replace = T))

# works for one var (recoding 3's as NA, 2's as 1, and 1's as 0):

df_new <- df_orig %>%
  as_tibble() %>%
  transmute(var1_new = ifelse(var1_orig == 3, NA, ifelse(var1_orig == 
  2, 1, ifelse(var1_orig == 1, 0, var1_orig))))

# and works the other var (recoding negatives as NA, 1's and 2's as 1, and 
leaving 0's as 0's):

df_new <- df_orig %>%
  as_tibble() %>%
  transmute(var2_new = ifelse(var2_orig < 0, NA, ifelse(var2_orig == 
  1 | var2_orig == 2, 1, 0)))

# but not together in same line of code (error: var2_orig not recognized):

df_new <- df_orig %>%
  as_tibble() %>%
  transmute(var1_new = ifelse(var1_orig == 3, NA, ifelse(var1_orig == 
  2, 1, ifelse(var1_orig == 1, 0, var1_orig)))) %>%
  transmute(var2_new = ifelse(var2_orig < 0, NA, ifelse(var2_orig == 
  1 | var2_orig == 2, 1, 0)))

Answer 1

Transmute will drop the variables, hence the error. You can use mutate to update the existing variables and then rename_all (If needed) to change their names,

df_orig %>%
    as_tibble() %>%
    mutate(var1_orig = ifelse(var1_orig == 3, NA, ifelse(var1_orig == 2, 1,
                                                         ifelse(var1_orig == 1, 0, var1_orig))),
           var2_orig = ifelse(var2_orig < 0, NA, ifelse(var2_orig == 1 | var2_orig == 2, 1, 0))) %>%
    rename_all(funs(sub('_.*', '_new', .)))