How to randomize (or permute) a dataframe rowwise and columnwise?

Question

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.

Answer 1

Given the R data.frame:

> df1   a b c 1 1 1 0 2 1 0 0 3 0 1 0 4 0 0 0 

Shuffle row-wise:

> df2 <- df1[sample(nrow(df1)),] > df2   a b c 3 0 1 0 4 0 0 0 2 1 0 0 1 1 1 0 

By default sample() randomly reorders the elements passed as the first argument. This means that the default size is the size of the passed array. Passing parameter replace=FALSE (the default) to sample(...) ensures that sampling is done without replacement which accomplishes a row wise shuffle.

Shuffle column-wise:

> df3 <- df1[,sample(ncol(df1))] > df3   c a b 1 0 1 1 2 0 1 0 3 0 0 1 4 0 0 0 

Answer 2

This is another way to shuffle the data.frame using package dplyr:

row-wise:

df2 <- slice(df1, sample(1:n())) 

or

df2 <- sample_frac(df1, 1L) 

column-wise:

df2 <- select(df1, one_of(sample(names(df1))))