Is there a good reason to use `sort` with `index.return = TRUE` instead of `order`?





.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty{ height:90px;width:728px;box-sizing:border-box;
}







5















sort has the argument index.return which is by default FALSE. If you set it to TRUE you get the ordering index... basically the same as when you use order.



My question

Are there cases where it makes sense to use sort with index.return = TRUE instead of order?






r sorting







share|improve this question


















  • 3





    FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

    – hrbrmstr
    Nov 16 '18 at 12:58


















5















sort has the argument index.return which is by default FALSE. If you set it to TRUE you get the ordering index... basically the same as when you use order.



My question

Are there cases where it makes sense to use sort with index.return = TRUE instead of order?






r sorting







share|improve this question


















  • 3





    FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

    – hrbrmstr
    Nov 16 '18 at 12:58














5












5








5


1






sort has the argument index.return which is by default FALSE. If you set it to TRUE you get the ordering index... basically the same as when you use order.



My question

Are there cases where it makes sense to use sort with index.return = TRUE instead of order?






r sorting







share|improve this question














sort has the argument index.return which is by default FALSE. If you set it to TRUE you get the ordering index... basically the same as when you use order.



My question

Are there cases where it makes sense to use sort with index.return = TRUE instead of order?






r sorting




r sorting






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 16 '18 at 12:46









vonjdvonjd

2,13732844




2,13732844








  • 3





    FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

    – hrbrmstr
    Nov 16 '18 at 12:58














  • 3





    FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

    – hrbrmstr
    Nov 16 '18 at 12:58








3




3





FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

– hrbrmstr
Nov 16 '18 at 12:58





FWIW sort calls this x[order(x, na.last = na.last, decreasing = decreasing)] for non-integer inputs.

– hrbrmstr
Nov 16 '18 at 12:58












2 Answers
2






active

oldest

votes


















6














order simply gives the indexes, instead sort gives also the values (and with index.return=T a list):



x <- runif(10, 0, 100)

order(x)

# [1]  2  7  1  9  6  5  8 10  4  3

sort(x, index.return=T)

# $`x`

# [1] 0.08140348 0.18272011 0.23575252 0.51493537 0.64281259 0.92121388 0.93759670 0.96221375 0.97646916 0.97863369

# 

# $ix

# [1]  2  7  1  9  6  5  8 10  4  3


It seems that order is a little faster with big numbers (longer vector size):



x <- runif(10000000, 0, 100)



microbenchmark::microbenchmark(

  sort = {sort(x, index.return=T)},

  order = {x[order(x)]},

  times = 100

)

# Unit: milliseconds

# expr      min       lq     mean   median       uq      max neval

# sort 63.48221 67.79530 78.33724 70.74215 74.10109 173.1129   100

# order 56.46055 57.18649 60.88239 58.29462 62.13086 155.5481   100


So probably you should pick sort with index.return = TRUE only if you need a list object to be returned. I can't find an example where sort is better than the other.






share|improve this answer





















  • 1





    To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

    – camille
    Nov 16 '18 at 14:04











  • Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

    – RLave
    Nov 16 '18 at 14:05













  • Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

    – Csd
    Nov 16 '18 at 17:15



















1














My suggestions are based on RLave's answer.



You could use the argument method, sort(x,method="quick",index.return=TRUE), and the function might be a little faster than the default. Also if you want a faster (for large vectors) alternative method of this, you can use this function:



sort_order <- function(x){

    indices <- order(x) #you can choose a method also but leave default.

    list("x"=x[indices],"ix"=indices)

}


Here are some benchmarks.



microbenchmark::microbenchmark(

     sort=s<-sort(x,index.return=T),

     "quick sort"=sq<-sort(x,method="quick",index.return=T),

     "order sort"=so<-sort_order(x),times = 10

     times=10

)



Unit: seconds

         expr      min       lq     mean   median       uq      max neval

         sort 1.493714 1.662791 1.737854 1.708502 1.887993 1.960912    10

   quick sort 1.366938 1.374874 1.451778 1.444342 1.480122 1.668693    10

   order sort 1.181974 1.344398 1.359209 1.369108 1.424569 1.461862    10



all.equal(so,sq)

[1] TRUE

all.equal(s,so)

[1] TRUE





share|improve this answer
























    Your Answer






    StackExchange.ifUsing("editor", function () {
    StackExchange.using("externalEditor", function () {
    StackExchange.using("snippets", function () {
    StackExchange.snippets.init();
    });
    });
    }, "code-snippets");

    StackExchange.ready(function() {
    var channelOptions = {
    tags: "".split(" "),
    id: "1"
    };
    initTagRenderer("".split(" "), "".split(" "), channelOptions);

    StackExchange.using("externalEditor", function() {
    // Have to fire editor after snippets, if snippets enabled
    if (StackExchange.settings.snippets.snippetsEnabled) {
    StackExchange.using("snippets", function() {
    createEditor();
    });
    }
    else {
    createEditor();
    }
    });

    function createEditor() {
    StackExchange.prepareEditor({
    heartbeatType: 'answer',
    autoActivateHeartbeat: false,
    convertImagesToLinks: true,
    noModals: true,
    showLowRepImageUploadWarning: true,
    reputationToPostImages: 10,
    bindNavPrevention: true,
    postfix: "",
    imageUploader: {
    brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
    contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
    allowUrls: true
    },
    onDemand: true,
    discardSelector: ".discard-answer"
    ,immediatelyShowMarkdownHelp:true
    });


    }
    });














    draft saved

    draft discarded


















    StackExchange.ready(
    function () {
    StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53338224%2fis-there-a-good-reason-to-use-sort-with-index-return-true-instead-of-orde%23new-answer', 'question_page');
    }
    );

    Post as a guest















    Required, but never shown

























    2 Answers
    2






    active

    oldest

    votes








    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    6














    order simply gives the indexes, instead sort gives also the values (and with index.return=T a list):



    x <- runif(10, 0, 100)
    
order(x)
    
# [1]  2  7  1  9  6  5  8 10  4  3
    
sort(x, index.return=T)
    
# $`x`
    
# [1] 0.08140348 0.18272011 0.23575252 0.51493537 0.64281259 0.92121388 0.93759670 0.96221375 0.97646916 0.97863369
    
# 
    
# $ix
    
# [1]  2  7  1  9  6  5  8 10  4  3


    It seems that order is a little faster with big numbers (longer vector size):



    x <- runif(10000000, 0, 100)
    

    
microbenchmark::microbenchmark(
    
  sort = {sort(x, index.return=T)},
    
  order = {x[order(x)]},
    
  times = 100
    
)
    
# Unit: milliseconds
    
# expr      min       lq     mean   median       uq      max neval
    
# sort 63.48221 67.79530 78.33724 70.74215 74.10109 173.1129   100
    
# order 56.46055 57.18649 60.88239 58.29462 62.13086 155.5481   100


    So probably you should pick sort with index.return = TRUE only if you need a list object to be returned. I can't find an example where sort is better than the other.






    share|improve this answer





















    • 1





      To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

      – camille
      Nov 16 '18 at 14:04











    • Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

      – RLave
      Nov 16 '18 at 14:05













    • Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

      – Csd
      Nov 16 '18 at 17:15
















    6














    order simply gives the indexes, instead sort gives also the values (and with index.return=T a list):



    x <- runif(10, 0, 100)
    
order(x)
    
# [1]  2  7  1  9  6  5  8 10  4  3
    
sort(x, index.return=T)
    
# $`x`
    
# [1] 0.08140348 0.18272011 0.23575252 0.51493537 0.64281259 0.92121388 0.93759670 0.96221375 0.97646916 0.97863369
    
# 
    
# $ix
    
# [1]  2  7  1  9  6  5  8 10  4  3


    It seems that order is a little faster with big numbers (longer vector size):



    x <- runif(10000000, 0, 100)
    

    
microbenchmark::microbenchmark(
    
  sort = {sort(x, index.return=T)},
    
  order = {x[order(x)]},
    
  times = 100
    
)
    
# Unit: milliseconds
    
# expr      min       lq     mean   median       uq      max neval
    
# sort 63.48221 67.79530 78.33724 70.74215 74.10109 173.1129   100
    
# order 56.46055 57.18649 60.88239 58.29462 62.13086 155.5481   100


    So probably you should pick sort with index.return = TRUE only if you need a list object to be returned. I can't find an example where sort is better than the other.






    share|improve this answer





















    • 1





      To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

      – camille
      Nov 16 '18 at 14:04











    • Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

      – RLave
      Nov 16 '18 at 14:05













    • Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

      – Csd
      Nov 16 '18 at 17:15














    6












    6








    6







    order simply gives the indexes, instead sort gives also the values (and with index.return=T a list):



    x <- runif(10, 0, 100)
    
order(x)
    
# [1]  2  7  1  9  6  5  8 10  4  3
    
sort(x, index.return=T)
    
# $`x`
    
# [1] 0.08140348 0.18272011 0.23575252 0.51493537 0.64281259 0.92121388 0.93759670 0.96221375 0.97646916 0.97863369
    
# 
    
# $ix
    
# [1]  2  7  1  9  6  5  8 10  4  3


    It seems that order is a little faster with big numbers (longer vector size):



    x <- runif(10000000, 0, 100)
    

    
microbenchmark::microbenchmark(
    
  sort = {sort(x, index.return=T)},
    
  order = {x[order(x)]},
    
  times = 100
    
)
    
# Unit: milliseconds
    
# expr      min       lq     mean   median       uq      max neval
    
# sort 63.48221 67.79530 78.33724 70.74215 74.10109 173.1129   100
    
# order 56.46055 57.18649 60.88239 58.29462 62.13086 155.5481   100


    So probably you should pick sort with index.return = TRUE only if you need a list object to be returned. I can't find an example where sort is better than the other.






    share|improve this answer















    order simply gives the indexes, instead sort gives also the values (and with index.return=T a list):



    x <- runif(10, 0, 100)
    
order(x)
    
# [1]  2  7  1  9  6  5  8 10  4  3
    
sort(x, index.return=T)
    
# $`x`
    
# [1] 0.08140348 0.18272011 0.23575252 0.51493537 0.64281259 0.92121388 0.93759670 0.96221375 0.97646916 0.97863369
    
# 
    
# $ix
    
# [1]  2  7  1  9  6  5  8 10  4  3


    It seems that order is a little faster with big numbers (longer vector size):



    x <- runif(10000000, 0, 100)
    

    
microbenchmark::microbenchmark(
    
  sort = {sort(x, index.return=T)},
    
  order = {x[order(x)]},
    
  times = 100
    
)
    
# Unit: milliseconds
    
# expr      min       lq     mean   median       uq      max neval
    
# sort 63.48221 67.79530 78.33724 70.74215 74.10109 173.1129   100
    
# order 56.46055 57.18649 60.88239 58.29462 62.13086 155.5481   100


    So probably you should pick sort with index.return = TRUE only if you need a list object to be returned. I can't find an example where sort is better than the other.







    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 16 '18 at 14:10

























    answered Nov 16 '18 at 12:55









    RLaveRLave

    5,28911226




    5,28911226








    • 1





      To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

      – camille
      Nov 16 '18 at 14:04











    • Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

      – RLave
      Nov 16 '18 at 14:05













    • Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

      – Csd
      Nov 16 '18 at 17:15














    • 1





      To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

      – camille
      Nov 16 '18 at 14:04











    • Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

      – RLave
      Nov 16 '18 at 14:05













    • Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

      – Csd
      Nov 16 '18 at 17:15








    1




    1





    To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

    – camille
    Nov 16 '18 at 14:04





    To clarify, by "big numbers" you mean order is faster with sorting vectors with lots of numbers, not numbers that are large in magnitude, right?

    – camille
    Nov 16 '18 at 14:04













    Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

    – RLave
    Nov 16 '18 at 14:05







    Yes I meant longer vector size. I checked at it seems that even with numbers of bigger magniture is still a little faster. It doesn't change much if you use runif(10000000, 0, 100) or runif(10000000, 0, 10000).

    – RLave
    Nov 16 '18 at 14:05















    Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

    – Csd
    Nov 16 '18 at 17:15





    Sometimes sort(x,method-"quick",...) is faster so you could test also with this arguments. Nice answer.

    – Csd
    Nov 16 '18 at 17:15













    1














    My suggestions are based on RLave's answer.



    You could use the argument method, sort(x,method="quick",index.return=TRUE), and the function might be a little faster than the default. Also if you want a faster (for large vectors) alternative method of this, you can use this function:



    sort_order <- function(x){
    
    indices <- order(x) #you can choose a method also but leave default.
    
    list("x"=x[indices],"ix"=indices)
    
}


    Here are some benchmarks.



    microbenchmark::microbenchmark(
    
     sort=s<-sort(x,index.return=T),
    
     "quick sort"=sq<-sort(x,method="quick",index.return=T),
    
     "order sort"=so<-sort_order(x),times = 10
    
     times=10
    
)
    

    
Unit: seconds
    
         expr      min       lq     mean   median       uq      max neval
    
         sort 1.493714 1.662791 1.737854 1.708502 1.887993 1.960912    10
    
   quick sort 1.366938 1.374874 1.451778 1.444342 1.480122 1.668693    10
    
   order sort 1.181974 1.344398 1.359209 1.369108 1.424569 1.461862    10
    

    
all.equal(so,sq)
    
[1] TRUE
    
all.equal(s,so)
    
[1] TRUE





    share|improve this answer




























      1














      My suggestions are based on RLave's answer.



      You could use the argument method, sort(x,method="quick",index.return=TRUE), and the function might be a little faster than the default. Also if you want a faster (for large vectors) alternative method of this, you can use this function:



      sort_order <- function(x){
      
    indices <- order(x) #you can choose a method also but leave default.
      
    list("x"=x[indices],"ix"=indices)
      
}


      Here are some benchmarks.



      microbenchmark::microbenchmark(
      
     sort=s<-sort(x,index.return=T),
      
     "quick sort"=sq<-sort(x,method="quick",index.return=T),
      
     "order sort"=so<-sort_order(x),times = 10
      
     times=10
      
)
      

      
Unit: seconds
      
         expr      min       lq     mean   median       uq      max neval
      
         sort 1.493714 1.662791 1.737854 1.708502 1.887993 1.960912    10
      
   quick sort 1.366938 1.374874 1.451778 1.444342 1.480122 1.668693    10
      
   order sort 1.181974 1.344398 1.359209 1.369108 1.424569 1.461862    10
      

      
all.equal(so,sq)
      
[1] TRUE
      
all.equal(s,so)
      
[1] TRUE





      share|improve this answer


























        1












        1








        1







        My suggestions are based on RLave's answer.



        You could use the argument method, sort(x,method="quick",index.return=TRUE), and the function might be a little faster than the default. Also if you want a faster (for large vectors) alternative method of this, you can use this function:



        sort_order <- function(x){
        
    indices <- order(x) #you can choose a method also but leave default.
        
    list("x"=x[indices],"ix"=indices)
        
}


        Here are some benchmarks.



        microbenchmark::microbenchmark(
        
     sort=s<-sort(x,index.return=T),
        
     "quick sort"=sq<-sort(x,method="quick",index.return=T),
        
     "order sort"=so<-sort_order(x),times = 10
        
     times=10
        
)
        

        
Unit: seconds
        
         expr      min       lq     mean   median       uq      max neval
        
         sort 1.493714 1.662791 1.737854 1.708502 1.887993 1.960912    10
        
   quick sort 1.366938 1.374874 1.451778 1.444342 1.480122 1.668693    10
        
   order sort 1.181974 1.344398 1.359209 1.369108 1.424569 1.461862    10
        

        
all.equal(so,sq)
        
[1] TRUE
        
all.equal(s,so)
        
[1] TRUE





        share|improve this answer













        My suggestions are based on RLave's answer.



        You could use the argument method, sort(x,method="quick",index.return=TRUE), and the function might be a little faster than the default. Also if you want a faster (for large vectors) alternative method of this, you can use this function:



        sort_order <- function(x){
        
    indices <- order(x) #you can choose a method also but leave default.
        
    list("x"=x[indices],"ix"=indices)
        
}


        Here are some benchmarks.



        microbenchmark::microbenchmark(
        
     sort=s<-sort(x,index.return=T),
        
     "quick sort"=sq<-sort(x,method="quick",index.return=T),
        
     "order sort"=so<-sort_order(x),times = 10
        
     times=10
        
)
        

        
Unit: seconds
        
         expr      min       lq     mean   median       uq      max neval
        
         sort 1.493714 1.662791 1.737854 1.708502 1.887993 1.960912    10
        
   quick sort 1.366938 1.374874 1.451778 1.444342 1.480122 1.668693    10
        
   order sort 1.181974 1.344398 1.359209 1.369108 1.424569 1.461862    10
        

        
all.equal(so,sq)
        
[1] TRUE
        
all.equal(s,so)
        
[1] TRUE






        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 16 '18 at 17:33









        CsdCsd

        31819




        31819






























            draft saved

            draft discarded




















































            Thanks for contributing an answer to Stack Overflow!


            • Please be sure to answer the question. Provide details and share your research!

            But avoid …



            • Asking for help, clarification, or responding to other answers.

            • Making statements based on opinion; back them up with references or personal experience.


            To learn more, see our tips on writing great answers.




            draft saved


            draft discarded














            StackExchange.ready(
            function () {
            StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53338224%2fis-there-a-good-reason-to-use-sort-with-index-return-true-instead-of-orde%23new-answer', 'question_page');
            }
            );

            Post as a guest















            Required, but never shown





















































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown

































            Required, but never shown














            Required, but never shown












            Required, but never shown







            Required, but never shown







            -

            Popular posts from this blog

            Bressuire

            Image
            Subprefecture and commune in Nouvelle-Aquitaine, France Bressuire Subprefecture and commune Chateau de Bressuire and the Eglise Notre-Dame Coat of arms Location of Bressuire Bressuire Show map of France Bressuire Show map of Nouvelle-Aquitaine Coordinates: 46°50′27″N 0°29′14″W  /  46.8408°N 0.4872°W  / 46.8408; -0.4872 Coordinates: 46°50′27″N 0°29′14″W  /  46.8408°N 0.4872°W  / 46.8408; -0.4872 Country France Region Nouvelle-Aquitaine Department Deux-Sèvres Arrondissement Bressuire Canton Bressuire Government  • Mayor .mw-parser-output .nobold{font-weight:normal} (2014–20) Jean Michel Bernier Area 1 180.59 km 2 (69.73 sq mi) Population (2014) 2 19,300  • Density 110/km 2 (280/sq mi) Time zone UTC+01:00 (CET)  • Summer (DST) UTC+02:00 (CEST) INSEE/Postal code 79049 /79300 Elevation 98–236 m (322–774 ft) (avg. 173 m or 568 ft) 1 French Land Register data, which exclude...
            Read more

            Vorschmack

            Image
            Vorschmack Ukrainian Jewish-style vorschmack served on rye bread Course Hors d'oeuvre Region or state Eastern Europe Associated national cuisine Ashkenazi Jewish, Finnish, German, Ukrainian, Polish, Russian Main ingredients Ground meat and/or fish Cookbook: Vorschmack   Media: Vorschmack Vorschmack or forshmak (Yiddish: פֿאָרשמאַק ‎, from archaic German Vorschmack , "foretaste" [1] or "appetizer" [2] ) is an originally East European dish made of salty minced fish or meat. Different variants of this dish are especially common in Ashkenazi Jewish and Finnish cuisine. Some varieties are also known in Russian and Polish cuisine. Contents 1 In Jewish cuisine 2 In Russian cuisine 3 In Polish cuisine 4 In Finnish cuisine 5 See also 6 References In Jewish cuisine According to Gil Marks, the German name points to the possible Germanic origin of this dish. [1] William Pokhlyobkin descr...
            Read more

            Quarantine

            Image
            For other uses, see Quarantine (disambiguation). Signal flag "Lima" called the "Yellow Jack" which when flown in harbor means ship is under quarantine. A simple yellow flag (also called the "Yellow Jack") had historically been used to signal quarantine (it stands for Q among signal flags), but now indicates the opposite, as a signal of a ship free of disease that requests boarding and inspection. A quarantine is used to separate and restrict the movement of people; it is 'a restraint upon the activities or communication of persons or the transport of goods designed to prevent the spread of disease or pests', for a certain period of time. [1] This is often used in connection to disease and illness, such as those who may possibly have been exposed to a communicable disease. [2] The term is often erroneously used to mean medical isolation, which is "to separate ill persons who have a communicable disease from those who are healthy...
            Read more