R reshape2 - transform 6 cols into 2 columns





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I am very new to R programming and stackoverflow, this is for a school's lab, please forgive me if I'm not asking the questions correctly..



I am given a data set with these columns:



ID  |  X_B_Rate  |  X_D_Rate  |  Y_B_Rate  |  Y_D_Rate  | Z_B_Rate  | Z_D_Rate


As you can see, the columns kind of repeat itself, the challenge is to write R code and transform the columns into:



ID  | x_or_y  |  B_or_D  |  Rate


I have tried reshape2's melt() function, but I can't wrap my head around how RegExp works with it



test <- melt(df, id.vars=c('ID'), measure.vars=grep('X$',colnames(df)), 

variable.name='x_or_y', value.name='Rate')


I know the code is definitely wrong... I'm only getting a list of IDs, I can't seem to understand how the RegExp works with the melt() function and I have tried googling "Reshape2 melt()" but everywhere there's only a very short doc on it.



I would totally appreciate if someone could tell me what am I doing wrong or at least point me in a the correct direction to the proper doc :(



Thanks in advance!






r reshape2







share|improve this question


















  • 1





    Could you provide sample data using dput(yourdf) for better results?

    – NelsonGon
    Nov 24 '18 at 17:12


















0















I am very new to R programming and stackoverflow, this is for a school's lab, please forgive me if I'm not asking the questions correctly..



I am given a data set with these columns:



ID  |  X_B_Rate  |  X_D_Rate  |  Y_B_Rate  |  Y_D_Rate  | Z_B_Rate  | Z_D_Rate


As you can see, the columns kind of repeat itself, the challenge is to write R code and transform the columns into:



ID  | x_or_y  |  B_or_D  |  Rate


I have tried reshape2's melt() function, but I can't wrap my head around how RegExp works with it



test <- melt(df, id.vars=c('ID'), measure.vars=grep('X$',colnames(df)), 

variable.name='x_or_y', value.name='Rate')


I know the code is definitely wrong... I'm only getting a list of IDs, I can't seem to understand how the RegExp works with the melt() function and I have tried googling "Reshape2 melt()" but everywhere there's only a very short doc on it.



I would totally appreciate if someone could tell me what am I doing wrong or at least point me in a the correct direction to the proper doc :(



Thanks in advance!






r reshape2







share|improve this question


















  • 1





    Could you provide sample data using dput(yourdf) for better results?

    – NelsonGon
    Nov 24 '18 at 17:12














0












0








0








I am very new to R programming and stackoverflow, this is for a school's lab, please forgive me if I'm not asking the questions correctly..



I am given a data set with these columns:



ID  |  X_B_Rate  |  X_D_Rate  |  Y_B_Rate  |  Y_D_Rate  | Z_B_Rate  | Z_D_Rate


As you can see, the columns kind of repeat itself, the challenge is to write R code and transform the columns into:



ID  | x_or_y  |  B_or_D  |  Rate


I have tried reshape2's melt() function, but I can't wrap my head around how RegExp works with it



test <- melt(df, id.vars=c('ID'), measure.vars=grep('X$',colnames(df)), 

variable.name='x_or_y', value.name='Rate')


I know the code is definitely wrong... I'm only getting a list of IDs, I can't seem to understand how the RegExp works with the melt() function and I have tried googling "Reshape2 melt()" but everywhere there's only a very short doc on it.



I would totally appreciate if someone could tell me what am I doing wrong or at least point me in a the correct direction to the proper doc :(



Thanks in advance!






r reshape2







share|improve this question














I am very new to R programming and stackoverflow, this is for a school's lab, please forgive me if I'm not asking the questions correctly..



I am given a data set with these columns:



ID  |  X_B_Rate  |  X_D_Rate  |  Y_B_Rate  |  Y_D_Rate  | Z_B_Rate  | Z_D_Rate


As you can see, the columns kind of repeat itself, the challenge is to write R code and transform the columns into:



ID  | x_or_y  |  B_or_D  |  Rate


I have tried reshape2's melt() function, but I can't wrap my head around how RegExp works with it



test <- melt(df, id.vars=c('ID'), measure.vars=grep('X$',colnames(df)), 

variable.name='x_or_y', value.name='Rate')


I know the code is definitely wrong... I'm only getting a list of IDs, I can't seem to understand how the RegExp works with the melt() function and I have tried googling "Reshape2 melt()" but everywhere there's only a very short doc on it.



I would totally appreciate if someone could tell me what am I doing wrong or at least point me in a the correct direction to the proper doc :(



Thanks in advance!






r reshape2




r reshape2






share|improve this question













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asked Nov 24 '18 at 16:55









RivRiv

2116




2116








  • 1





    Could you provide sample data using dput(yourdf) for better results?

    – NelsonGon
    Nov 24 '18 at 17:12














  • 1





    Could you provide sample data using dput(yourdf) for better results?

    – NelsonGon
    Nov 24 '18 at 17:12








1




1





Could you provide sample data using dput(yourdf) for better results?

– NelsonGon
Nov 24 '18 at 17:12





Could you provide sample data using dput(yourdf) for better results?

– NelsonGon
Nov 24 '18 at 17:12












1 Answer
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1














This should do it:



yourdf %>% 

  gather("id","value",1:ncol(.))


You can then rename your columns in whichever way you wish.
EDIT: Using reshape2 you could do something like this:



yourdf%>% 

  mutate(ID=row_number()) %>% 

  reshape2::melt(id.vars=c("ID"))


I've used my own data to exemplify as your question provides no sample data.






share|improve this answer


























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    This should do it:



    yourdf %>% 
    
  gather("id","value",1:ncol(.))


    You can then rename your columns in whichever way you wish.
    EDIT: Using reshape2 you could do something like this:



    yourdf%>% 
    
  mutate(ID=row_number()) %>% 
    
  reshape2::melt(id.vars=c("ID"))


    I've used my own data to exemplify as your question provides no sample data.






    share|improve this answer






























      1














      This should do it:



      yourdf %>% 
      
  gather("id","value",1:ncol(.))


      You can then rename your columns in whichever way you wish.
      EDIT: Using reshape2 you could do something like this:



      yourdf%>% 
      
  mutate(ID=row_number()) %>% 
      
  reshape2::melt(id.vars=c("ID"))


      I've used my own data to exemplify as your question provides no sample data.






      share|improve this answer




























        1












        1








        1







        This should do it:



        yourdf %>% 
        
  gather("id","value",1:ncol(.))


        You can then rename your columns in whichever way you wish.
        EDIT: Using reshape2 you could do something like this:



        yourdf%>% 
        
  mutate(ID=row_number()) %>% 
        
  reshape2::melt(id.vars=c("ID"))


        I've used my own data to exemplify as your question provides no sample data.






        share|improve this answer















        This should do it:



        yourdf %>% 
        
  gather("id","value",1:ncol(.))


        You can then rename your columns in whichever way you wish.
        EDIT: Using reshape2 you could do something like this:



        yourdf%>% 
        
  mutate(ID=row_number()) %>% 
        
  reshape2::melt(id.vars=c("ID"))


        I've used my own data to exemplify as your question provides no sample data.







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 24 '18 at 17:17

























        answered Nov 24 '18 at 17:11









        NelsonGonNelsonGon

        4,2264834




        4,2264834
































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