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How to find the row means in data.table object for columns having same name in R?
To find the row mean of columns having same name in R data.table, we can follow the below steps −
First of all, create a data.table with some columns having same name.
Then, use tapply along with colnames and mean function to find the row mean of columns having same name.
Example
Create the data.table
Let’s create a data.table as shown below −
library(data.table) DT<- data.table(x=rpois(25,2),y=rpois(25,1),x=rpois(25,10),y=rpois(25,5),check.names=FALSE) DT
Output
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
x y x y 1: 4 1 11 3 2: 2 2 5 3 3: 3 0 7 4 4: 1 1 8 3 5: 4 0 6 4 6: 1 1 11 4 7: 1 1 10 6 8: 1 1 8 2 9: 2 0 6 5 10: 4 0 10 4 11: 1 1 9 6 12: 2 0 9 4 13: 1 1 8 3 14: 3 1 11 3 15: 2 1 5 7 16: 3 1 9 5 17: 2 0 2 7 18: 3 0 7 4 19: 2 0 9 8 20: 0 1 10 4 21: 3 3 9 4 22: 0 1 9 8 23: 5 1 9 6 24: 2 0 13 1 25: 1 2 21 7 x y x y
Find the row mean of columns having same name
Using tapply along with colnames and mean function to find the row mean of columns having same name in data.table DT −
library(data.table) DT<- data.table(x=rpois(25,2),y=rpois(25,1),x=rpois(25,10),y=rpois(25,5),check.names=FALSE) t(apply(DT,1, function(x) tapply(x,colnames(DT),mean)))
Output
x y [1,] 7.5 2.0 [2,] 3.5 2.5 [3,] 5.0 2.0 [4,] 4.5 2.0 [5,] 5.0 2.0 [6,] 6.0 2.5 [7,] 5.5 3.5 [8,] 4.5 1.5 [9,] 4.0 2.5 [10,] 7.0 2.0 [11,] 5.0 3.5 [12,] 5.5 2.0 [13,] 4.5 2.0 [14,] 7.0 2.0 [15,] 3.5 4.0 [16,] 6.0 3.0 [17,] 2.0 3.5 [18,] 5.0 2.0 [19,] 5.5 4.0 [20,] 5.0 2.5 [21,] 6.0 3.5 [22,] 4.5 4.5 [23,] 7.0 3.5 [24,] 7.5 0.5 [25,] 11.0 4.5
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