How to write a function whose input is a vector and output is a character vector based on quantile...












0















I am writing a funcion whose input is a vector and output is a character vector of three levels: Below Avg, Avg, and Above Avg. I would like the character vector to be calucalted based on the 1st and 3rd quantiles of the vector given. When I call my function, only Below Avg returns which I understand why it returns, but do not know how to fix. Ideally I would like a new vector such that Below Avg corresponds to the values below the 1st quantile, Above Avg corresponds to values above the 3rd quantile, and Avg is everything in between.



x<-c(1:10)

label_scale<-function(vecrr){

  lq<-quantile(vecrr,0.25)

  uq<-quantile(vecrr,0.75)

  if(vecrr<=lq){

    k<-'Below Avg.'

  } else if(vecrr>=uq){

    k<-'Above Avg.'

  } else{

    k<-'Avg.'}

  return(k)

}

y<-mapply(label_scale,x)

z<-sapply(x,label_scale)





r function quantile







share|improve this question

























  • Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

    – AntoniosK
    Nov 21 '18 at 10:50











  • My apologies. That has been fixed.

    – Jack Armstrong
    Nov 21 '18 at 11:01
















0















I am writing a funcion whose input is a vector and output is a character vector of three levels: Below Avg, Avg, and Above Avg. I would like the character vector to be calucalted based on the 1st and 3rd quantiles of the vector given. When I call my function, only Below Avg returns which I understand why it returns, but do not know how to fix. Ideally I would like a new vector such that Below Avg corresponds to the values below the 1st quantile, Above Avg corresponds to values above the 3rd quantile, and Avg is everything in between.



x<-c(1:10)

label_scale<-function(vecrr){

  lq<-quantile(vecrr,0.25)

  uq<-quantile(vecrr,0.75)

  if(vecrr<=lq){

    k<-'Below Avg.'

  } else if(vecrr>=uq){

    k<-'Above Avg.'

  } else{

    k<-'Avg.'}

  return(k)

}

y<-mapply(label_scale,x)

z<-sapply(x,label_scale)





r function quantile







share|improve this question

























  • Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

    – AntoniosK
    Nov 21 '18 at 10:50











  • My apologies. That has been fixed.

    – Jack Armstrong
    Nov 21 '18 at 11:01














0












0








0


0






I am writing a funcion whose input is a vector and output is a character vector of three levels: Below Avg, Avg, and Above Avg. I would like the character vector to be calucalted based on the 1st and 3rd quantiles of the vector given. When I call my function, only Below Avg returns which I understand why it returns, but do not know how to fix. Ideally I would like a new vector such that Below Avg corresponds to the values below the 1st quantile, Above Avg corresponds to values above the 3rd quantile, and Avg is everything in between.



x<-c(1:10)

label_scale<-function(vecrr){

  lq<-quantile(vecrr,0.25)

  uq<-quantile(vecrr,0.75)

  if(vecrr<=lq){

    k<-'Below Avg.'

  } else if(vecrr>=uq){

    k<-'Above Avg.'

  } else{

    k<-'Avg.'}

  return(k)

}

y<-mapply(label_scale,x)

z<-sapply(x,label_scale)





r function quantile







share|improve this question
















I am writing a funcion whose input is a vector and output is a character vector of three levels: Below Avg, Avg, and Above Avg. I would like the character vector to be calucalted based on the 1st and 3rd quantiles of the vector given. When I call my function, only Below Avg returns which I understand why it returns, but do not know how to fix. Ideally I would like a new vector such that Below Avg corresponds to the values below the 1st quantile, Above Avg corresponds to values above the 3rd quantile, and Avg is everything in between.



x<-c(1:10)

label_scale<-function(vecrr){

  lq<-quantile(vecrr,0.25)

  uq<-quantile(vecrr,0.75)

  if(vecrr<=lq){

    k<-'Below Avg.'

  } else if(vecrr>=uq){

    k<-'Above Avg.'

  } else{

    k<-'Avg.'}

  return(k)

}

y<-mapply(label_scale,x)

z<-sapply(x,label_scale)





r function quantile




r function quantile






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 21 '18 at 11:01







Jack Armstrong

















asked Nov 21 '18 at 10:43









Jack ArmstrongJack Armstrong

318519




318519













  • Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

    – AntoniosK
    Nov 21 '18 at 10:50











  • My apologies. That has been fixed.

    – Jack Armstrong
    Nov 21 '18 at 11:01



















  • Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

    – AntoniosK
    Nov 21 '18 at 10:50











  • My apologies. That has been fixed.

    – Jack Armstrong
    Nov 21 '18 at 11:01

















Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

– AntoniosK
Nov 21 '18 at 10:50





Do you mean mapply(label_scale,x) and sapply(x,label_scale)? You posted those the other way around and it doesn't work at all.

– AntoniosK
Nov 21 '18 at 10:50













My apologies. That has been fixed.

– Jack Armstrong
Nov 21 '18 at 11:01





My apologies. That has been fixed.

– Jack Armstrong
Nov 21 '18 at 11:01












2 Answers
2






active

oldest

votes


















1














Your problem is that you apply your function to each one of the elements of your vector and by default a given value is always equal to the quantile of that value and your process will return Below Avg for each one of the vector elements. (Eg. x == quantile(x, 0.25) will always return TRUE).



You should use ifelse inside your function, which is vectorised:



# example vector

x<-c(1:10)



# function

label_scale<-function(vecrr){

  lq<-quantile(vecrr,0.25)

  uq<-quantile(vecrr,0.75)



ifelse(vecrr<=lq, 'Below Avg.', ifelse(vecrr>=uq, 'Above Avg.', 'Avg.'))  



}



# use function on a vector

label_scale(x)



# [1] "Below Avg." "Below Avg." "Below Avg." "Avg."       "Avg."       "Avg."       "Avg."       "Above Avg."

# [9] "Above Avg." "Above Avg."





share|improve this answer


























  • This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

    – rookie
    Nov 21 '18 at 11:14



















0














I would use cut and quantile in this situation:



x <- c(1:10)



x.char <- cut(x, quantile(x, c(0,.25,.75,1)), include.lowest = T, labels = c('Below Avg.', 'Avg.','Above Avg.'))



x.char

[1] Below Avg. Below Avg. Below Avg. Avg. Avg. Avg. Avg.      

[8] Above Avg. Above Avg. Above Avg.

Levels: Below Avg. Avg. Above Avg.





share|improve this answer

























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    2 Answers
    2






    active

    oldest

    votes








    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    1














    Your problem is that you apply your function to each one of the elements of your vector and by default a given value is always equal to the quantile of that value and your process will return Below Avg for each one of the vector elements. (Eg. x == quantile(x, 0.25) will always return TRUE).



    You should use ifelse inside your function, which is vectorised:



    # example vector
    
x<-c(1:10)
    

    
# function
    
label_scale<-function(vecrr){
    
  lq<-quantile(vecrr,0.25)
    
  uq<-quantile(vecrr,0.75)
    

    
ifelse(vecrr<=lq, 'Below Avg.', ifelse(vecrr>=uq, 'Above Avg.', 'Avg.'))  
    

    
}
    

    
# use function on a vector
    
label_scale(x)
    

    
# [1] "Below Avg." "Below Avg." "Below Avg." "Avg."       "Avg."       "Avg."       "Avg."       "Above Avg."
    
# [9] "Above Avg." "Above Avg."





    share|improve this answer


























    • This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

      – rookie
      Nov 21 '18 at 11:14
















    1














    Your problem is that you apply your function to each one of the elements of your vector and by default a given value is always equal to the quantile of that value and your process will return Below Avg for each one of the vector elements. (Eg. x == quantile(x, 0.25) will always return TRUE).



    You should use ifelse inside your function, which is vectorised:



    # example vector
    
x<-c(1:10)
    

    
# function
    
label_scale<-function(vecrr){
    
  lq<-quantile(vecrr,0.25)
    
  uq<-quantile(vecrr,0.75)
    

    
ifelse(vecrr<=lq, 'Below Avg.', ifelse(vecrr>=uq, 'Above Avg.', 'Avg.'))  
    

    
}
    

    
# use function on a vector
    
label_scale(x)
    

    
# [1] "Below Avg." "Below Avg." "Below Avg." "Avg."       "Avg."       "Avg."       "Avg."       "Above Avg."
    
# [9] "Above Avg." "Above Avg."





    share|improve this answer


























    • This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

      – rookie
      Nov 21 '18 at 11:14














    1












    1








    1







    Your problem is that you apply your function to each one of the elements of your vector and by default a given value is always equal to the quantile of that value and your process will return Below Avg for each one of the vector elements. (Eg. x == quantile(x, 0.25) will always return TRUE).



    You should use ifelse inside your function, which is vectorised:



    # example vector
    
x<-c(1:10)
    

    
# function
    
label_scale<-function(vecrr){
    
  lq<-quantile(vecrr,0.25)
    
  uq<-quantile(vecrr,0.75)
    

    
ifelse(vecrr<=lq, 'Below Avg.', ifelse(vecrr>=uq, 'Above Avg.', 'Avg.'))  
    

    
}
    

    
# use function on a vector
    
label_scale(x)
    

    
# [1] "Below Avg." "Below Avg." "Below Avg." "Avg."       "Avg."       "Avg."       "Avg."       "Above Avg."
    
# [9] "Above Avg." "Above Avg."





    share|improve this answer















    Your problem is that you apply your function to each one of the elements of your vector and by default a given value is always equal to the quantile of that value and your process will return Below Avg for each one of the vector elements. (Eg. x == quantile(x, 0.25) will always return TRUE).



    You should use ifelse inside your function, which is vectorised:



    # example vector
    
x<-c(1:10)
    

    
# function
    
label_scale<-function(vecrr){
    
  lq<-quantile(vecrr,0.25)
    
  uq<-quantile(vecrr,0.75)
    

    
ifelse(vecrr<=lq, 'Below Avg.', ifelse(vecrr>=uq, 'Above Avg.', 'Avg.'))  
    

    
}
    

    
# use function on a vector
    
label_scale(x)
    

    
# [1] "Below Avg." "Below Avg." "Below Avg." "Avg."       "Avg."       "Avg."       "Avg."       "Above Avg."
    
# [9] "Above Avg." "Above Avg."






    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 21 '18 at 11:00

























    answered Nov 21 '18 at 10:53









    AntoniosKAntoniosK

    12.5k1822




    12.5k1822













    • This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

      – rookie
      Nov 21 '18 at 11:14



















    • This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

      – rookie
      Nov 21 '18 at 11:14

















    This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

    – rookie
    Nov 21 '18 at 11:14





    This gets more complicated with more levels. The cut function is specifically designed for converting numeric vectors into character/factor vectors - see my answer.

    – rookie
    Nov 21 '18 at 11:14













    0














    I would use cut and quantile in this situation:



    x <- c(1:10)
    

    
x.char <- cut(x, quantile(x, c(0,.25,.75,1)), include.lowest = T, labels = c('Below Avg.', 'Avg.','Above Avg.'))
    

    
x.char
    
[1] Below Avg. Below Avg. Below Avg. Avg. Avg. Avg. Avg.      
    
[8] Above Avg. Above Avg. Above Avg.
    
Levels: Below Avg. Avg. Above Avg.





    share|improve this answer






























      0














      I would use cut and quantile in this situation:



      x <- c(1:10)
      

      
x.char <- cut(x, quantile(x, c(0,.25,.75,1)), include.lowest = T, labels = c('Below Avg.', 'Avg.','Above Avg.'))
      

      
x.char
      
[1] Below Avg. Below Avg. Below Avg. Avg. Avg. Avg. Avg.      
      
[8] Above Avg. Above Avg. Above Avg.
      
Levels: Below Avg. Avg. Above Avg.





      share|improve this answer




























        0












        0








        0







        I would use cut and quantile in this situation:



        x <- c(1:10)
        

        
x.char <- cut(x, quantile(x, c(0,.25,.75,1)), include.lowest = T, labels = c('Below Avg.', 'Avg.','Above Avg.'))
        

        
x.char
        
[1] Below Avg. Below Avg. Below Avg. Avg. Avg. Avg. Avg.      
        
[8] Above Avg. Above Avg. Above Avg.
        
Levels: Below Avg. Avg. Above Avg.





        share|improve this answer















        I would use cut and quantile in this situation:



        x <- c(1:10)
        

        
x.char <- cut(x, quantile(x, c(0,.25,.75,1)), include.lowest = T, labels = c('Below Avg.', 'Avg.','Above Avg.'))
        

        
x.char
        
[1] Below Avg. Below Avg. Below Avg. Avg. Avg. Avg. Avg.      
        
[8] Above Avg. Above Avg. Above Avg.
        
Levels: Below Avg. Avg. Above Avg.






        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 21 '18 at 11:14

























        answered Nov 21 '18 at 11:00









        rookierookie

        763




        763






























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