R new calculated field by dividing sum of 1 column with count of category list [duplicate]











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  • Calculate group mean (or other summary stats) and assign to original data

    4 answers




I have a dataframe with 2 columns:



Price . Category

10 . Cat-A

5 . Cat-B

20 . Cat-A

30 . Cat-A

15 . Cat-B


So, I have count = 3 for Cat-A and thus I need a new column which sums the price for Cat-A and divides by the count of category i.e., (10+20+30)/3 = 20



Final table should look like this:



Price . Category . Ratio

10 . Cat-A . 20

5 . Cat-B . 10

20 . Cat-A . 20

30 . Cat-A . 20

15 . Cat-B . 10





r







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 Nov 11 at 0:52


This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.



















    up vote
    0
    down vote

    favorite













    This question already has an answer here:




    • Calculate group mean (or other summary stats) and assign to original data

      4 answers




    I have a dataframe with 2 columns:



    Price . Category
    
10 . Cat-A
    
5 . Cat-B
    
20 . Cat-A
    
30 . Cat-A
    
15 . Cat-B


    So, I have count = 3 for Cat-A and thus I need a new column which sums the price for Cat-A and divides by the count of category i.e., (10+20+30)/3 = 20



    Final table should look like this:



    Price . Category . Ratio
    
10 . Cat-A . 20
    
5 . Cat-B . 10
    
20 . Cat-A . 20
    
30 . Cat-A . 20
    
15 . Cat-B . 10





    r







    share|improve this question















    marked as duplicate by Jilber Urbina r
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     Nov 11 at 0:52


    This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

















      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite












      This question already has an answer here:




      • Calculate group mean (or other summary stats) and assign to original data

        4 answers




      I have a dataframe with 2 columns:



      Price . Category
      
10 . Cat-A
      
5 . Cat-B
      
20 . Cat-A
      
30 . Cat-A
      
15 . Cat-B


      So, I have count = 3 for Cat-A and thus I need a new column which sums the price for Cat-A and divides by the count of category i.e., (10+20+30)/3 = 20



      Final table should look like this:



      Price . Category . Ratio
      
10 . Cat-A . 20
      
5 . Cat-B . 10
      
20 . Cat-A . 20
      
30 . Cat-A . 20
      
15 . Cat-B . 10





      r







      share|improve this question
















      This question already has an answer here:




      • Calculate group mean (or other summary stats) and assign to original data

        4 answers




      I have a dataframe with 2 columns:



      Price . Category
      
10 . Cat-A
      
5 . Cat-B
      
20 . Cat-A
      
30 . Cat-A
      
15 . Cat-B


      So, I have count = 3 for Cat-A and thus I need a new column which sums the price for Cat-A and divides by the count of category i.e., (10+20+30)/3 = 20



      Final table should look like this:



      Price . Category . Ratio
      
10 . Cat-A . 20
      
5 . Cat-B . 10
      
20 . Cat-A . 20
      
30 . Cat-A . 20
      
15 . Cat-B . 10




      This question already has an answer here:




      • Calculate group mean (or other summary stats) and assign to original data

        4 answers







      r




      r






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 11 at 0:47

























      asked Nov 11 at 0:43









      A_K

      12




      12




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       Nov 11 at 0:52


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          1 Answer
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          Here's a way using base R assuming your dataframe is called df-



          df$Ratio <- ave(df$Price, df$Category, FUN = mean)





          share|improve this answer




























            1 Answer
            1






            active

            oldest

            votes








            1 Answer
            1






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes








            up vote
            0
            down vote













            Here's a way using base R assuming your dataframe is called df-



            df$Ratio <- ave(df$Price, df$Category, FUN = mean)





            share|improve this answer

























              up vote
              0
              down vote













              Here's a way using base R assuming your dataframe is called df-



              df$Ratio <- ave(df$Price, df$Category, FUN = mean)





              share|improve this answer























                up vote
                0
                down vote










                up vote
                0
                down vote









                Here's a way using base R assuming your dataframe is called df-



                df$Ratio <- ave(df$Price, df$Category, FUN = mean)





                share|improve this answer












                Here's a way using base R assuming your dataframe is called df-



                df$Ratio <- ave(df$Price, df$Category, FUN = mean)






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 11 at 0:47









                Shree

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                2,818321















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