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How to find the groupwise order of values in an R data frame?
To find the groupwise order of values in an R data frame, we can use mutate function of dplyr package along with rank function and grouping will be done with the help of group_by function.
For Example, if we have a data frame called df that contains two columns say Group and DV then we can find the groupwise order of DV values by using the command given below −
df%%group_by(Group)%%mutate(Order=rank(DV))
Example 1
Following snippet creates a sample data frame −
Group<-rep(LETTERS[1:5],each=4) Score<-sample(1:50,20) df1<-data.frame(Group,Score) df1
The following dataframe is created
Group Score 1 A 13 2 A 27 3 A 50 4 A 42 5 B 43 6 B 20 7 B 45 8 B 49 9 C 31 10 C 15 11 C 26 12 C 33 13 D 40 14 D 38 15 D 12 16 D 17 17 E 16 18 E 28 19 E 5 20 E 9
To load dplyr package and find groupwise order of Score in df1 on the above created data frame, add the following code to the above snippet −
Group<-rep(LETTERS[1:5],each=4) Score<-sample(1:50,20) df1<-data.frame(Group,Score) library(dplyr) df1%%group_by(Group)%%mutate(Order=rank(Score)) # A tibble: 20 x 3 # Groups: Group [5]
Output
If you execute all the above given snippets as a single program, it generates the following Output −
Group Score Order <chr <int <dbl 1 A 13 1 2 A 27 2 3 A 50 4 4 A 42 3 5 B 43 2 6 B 20 1 7 B 45 3 8 B 49 4 9 C 31 3 10 C 15 1 11 C 26 2 12 C 33 4 13 D 40 4 14 D 38 3 15 D 12 1 16 D 17 2 17 E 16 3 18 E 28 4 19 E 5 1 20 E 9 2
Example 2
Following snippet creates a sample data frame −
Category<-rep(c("I","II","III","IV"),each=5) Sales<-sample(51:100,20) df2<-data.frame(Category,Sales) df2
The following dataframe is created
Category Sales 1 I 97 2 I 66 3 I 75 4 I 80 5 I 63 6 II 69 7 II 84 8 II 72 9 II 59 10 II 65 11 III 68 12 III 73 13 III 88 14 III 93 15 III 100 16 IV 58 17 IV 83 18 IV 95 19 IV 61 20 IV 67
To find groupwise order of Sales in df2 on the above created data frame, add the following code to the above snippet −
Category<-rep(c("I","II","III","IV"),each=5) Sales<-sample(51:100,20) df2<-data.frame(Category,Sales) df2%%group_by(Category)%%mutate(Order=rank(Sales)) # A tibble: 20 x 3 # Groups: Category [4]
Output
If you execute all the above given snippets as a single program, it generates the following Output −
Category Sales Order <chr <int <dbl 1 I 97 5 2 I 66 2 3 I 75 3 4 I 80 4 5 I 63 1 6 II 69 3 7 II 84 5 8 II 72 4 9 II 59 1 10 II 65 2 11 III 68 1 12 III 73 2 13 III 88 3 14 III 93 4 15 III 100 5 16 IV 58 1 17 IV 83 4 18 IV 95 5 19 IV 61 2 20 IV 67 3
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