r - Issue with using Pipe for multiple ifelse functions

Question

i am using the tidyverse package and working with the pipe term "%>%" how ever after using it on multiple functions i seem to get an error(can not find function ) -.-^and i did not find any info on this on term ("%>%<-") in the net.

 #AB1 
  df_1$AB1<- ifelse(df_1$AB1==1 , 1 ,  
                        ifelse(df_1$AB1== 2, as.integer(-1),
                               ifelse(df_1$AB1== 3, 0,
                                      ifelse(df_1$AB1== 4,0,NA)))) %>%  
#AB2
  df_1$AB2<- ifelse(df_1$AB2==1 , 1 ,  
                     ifelse(df_1$AB2== 2, as.integer(-1),
                            ifelse(df_1$AB2== 3, 0,
                                   ifelse(df_1$AB2== 4,0,NA)))) 

i have tried canging the dataframe to df_2 f.e. or to remove the seconddf_1$AB2<-

#AB1 
  df_1$AB1<- ifelse(df_1$AB1==1 , 1 ,  
                        ifelse(df_1$AB1== 2, as.integer(-1),
                               ifelse(df_1$AB1== 3, 0,
                                      ifelse(df_1$AB1== 4,0,NA)))) %>%  
#AB2
  ifelse(df_1$AB2==1 , 1 ,  
                     ifelse(df_1$AB2== 2, as.integer(-1),
                            ifelse(df_1$AB2== 3, 0,
                                   ifelse(df_1$AB2== 4,0,NA))))

seems like i do not realy get the pipe thing. i wanted to make R run both functions after eaach other but it does not seem wo work? Is there a way to save some time since i would like to avoid going "ctrl" +"r" on many diffrent functions each time i want to change my data in this way.

Bests regards and ty for taking looking at this !

question from:https://stackoverflow.com/questions/66050679/issue-with-using-pipe-for-multiple-ifelse-functions

Answer 1

You should first determine your whole dataframe as data for the pipe. After that, you should not provide the data input for every function, the pipe does that, that is the magic of pipes.

Than you could use transmute to transform your desired columns. case_when() is a nice, cleaner alternative to multiple neste ifelse()s.

Without an example from your data (please post (dput(head(df_1)), and the results of your attempts, it is hard to tell exactly what should work, but you may be ok with this: Try this.

 #AB1 
  df_1 %>% transmute(AB1=case_when(
                        AB1==1 ~ 1 ,  
                        AB1== 2 ~ as.integer(-1),
                        AB1== 3 ~ 0,
                        AB1== 4 ~ 0,
                        TRUE ~ NA) %>%

         transmute(AB2=case_when(
                        AB2==2 ~ 1 ,  
                        AB2== 2 ~ as.integer(-1),
                        AB2== 3 ~ 0,
                        AB2== 4 ~ 0,
                        TRUE ~ NA) %>%