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How to create a column of raise to the power of another column in data frames stored in R list?
To create a column of raise to the power of another column in data frames stored in R list, we can follow the below steps −
First of all, create a list of data frames.
Then, use lapply function to create a column of raise to the power of another column in data frames stored in the list.
Example
Create the list of data frames
Using data.frame function to create data frames and list function to create the list of those data frames −
df1<-data.frame(x=sample(1:10,25,replace=TRUE),y=sample(1:5,25,replace=TRUE)) df2<-data.frame(x=sample(1:2,25,replace=TRUE),y=sample(1:5,25,replace=TRUE)) List<-list(df1,df2) List
Output
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
[[1]] x y 1 9 4 2 4 4 3 4 1 4 6 3 5 8 4 6 6 3 7 4 1 8 5 2 9 8 5 10 10 2 11 2 4 12 9 3 13 9 4 14 6 2 15 10 3 16 10 1 17 4 2 18 5 5 19 2 1 20 3 4 21 7 5 22 7 4 23 4 2 24 7 4 25 6 2 [[2]] x y 1 2 5 2 1 5 3 1 2 4 1 1 5 1 4 6 2 1 7 1 2 8 1 2 9 1 3 10 1 5 11 1 2 12 2 4 13 2 4 14 1 3 15 2 4 16 2 3 17 1 1 18 2 1 19 1 2 20 1 5 21 2 5 22 1 3 23 1 4 24 2 3 25 2 1
Create a column of raise to the power of another column
Using lapply function to create a column of raise to the power of another column in data frames df1 and df2 stored in the list called List as shown below −
df1-data.frame(x=sample(1:10,25,replace=TRUE),y=sample(1:5,25,replace=TRUE)) df2<-data.frame(x=sample(1:2,25,replace=TRUE),y=sample(1:5,25,replace=TRUE)) List<-list(df1,df2) lapply(List,function(x) { + x$PowerCol2<-(x$x)^(x$y) + return(x) + })
Output
[[1]] x y PowerCol2 1 9 4 6561 2 4 4 256 3 4 1 4 4 6 3 216 5 8 4 4096 6 6 3 216 7 4 1 4 8 5 2 25 9 8 5 32768 10 10 2 100 11 2 4 16 12 9 3 729 13 9 4 6561 14 6 2 36 15 10 3 1000 16 10 1 10 17 4 2 16 18 5 5 3125 19 2 1 2 20 3 4 81 21 7 5 16807 22 7 4 2401 23 4 2 16 24 7 4 2401 25 6 2 36 [[2]] x y PowerCol2 1 2 5 32 2 1 5 1 3 1 2 1 4 1 1 1 5 1 4 1 6 2 1 2 7 1 2 1 8 1 2 1 9 1 3 1 10 1 5 1 11 1 2 1 12 2 4 16 13 2 4 16 14 1 3 1 15 2 4 16 16 2 3 8 17 1 1 1 18 2 1 2 19 1 2 1 20 1 5 1 21 2 5 32 22 1 3 1 23 1 4 1 24 2 3 8 25 2 1 2
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