I have a dataframe (df1) like this.
f1 f2 f3 f4 f5
d1 1 0 1 1 1
d2 1 0 0 1 0
d3 0 0 0 1 1
d4 0 1 0 0 1
The d1...d4 column is the rowname, the f1...f5 row is the columnname.
To do sample(df1), I get a new dataframe with count of 1 same as df1. So, the count of 1 is conserved for the whole dataframe but not for each row or each column.
Is it possible to do the randomization row-wise or column-wise?
I want to randomize the df1 column-wise for each column, i.e. the number of 1 in each column remains the same. and each column need to be changed by at least once. For example, I may have a randomized df2 like this: (Noted that the count of 1 in each column remains the same but the count of 1 in each row is different.
f1 f2 f3 f4 f5
d1 1 0 0 0 1
d2 0 1 0 1 1
d3 1 0 0 1 1
d4 0 0 1 1 0
Likewise, I also want to randomize the df1 row-wise for each row, i.e. the no. of 1 in each row remains the same, and each row need to be changed (but the no of changed entries could be different). For example, a randomized df3 could be something like this:
f1 f2 f3 f4 f5
d1 0 1 1 1 1 <- two entries are different
d2 0 0 1 0 1 <- four entries are different
d3 1 0 0 0 1 <- two entries are different
d4 0 0 1 0 1 <- two entries are different
PS. Many thanks for the help from Gavin Simpson, Joris Meys and Chase for the previous answers to my previous question on randomizing two columns.