Shuffling a pandas dataframe

Question

I have the following dataframe:

df = pd.DataFrame({'A':range(10), 'B':range(10), 'C':range(10), 'D':range(10)})

I would like to shuffle the data using the below function:

import pandas as pd

import numpy as np

def shuffle(df, n=1, axis=0):
    df = df.copy()
    for _ in range(n):
        df.apply(np.random.shuffle, axis=axis)
        return df

However I do not want to shuffle columns A and D, only columns B and C. Is there a way to do this by amending the function? I want to say if column == 'A' or 'D' then don't shuffle.

Thanks

You could easily index the dataframe, use `sample` to shuffle and assign back. Why using this function? — yatu, Jul 20 '20 at 13:48
I want to say if column == 'B' or 'C' then don't shuffle. Or you meant columns A or D . Best — smile, Jul 20 '20 at 13:49
take out the column need to be shuffled, then assign it back — BENY, Jul 20 '20 at 13:49
@YOBEN_S I did think of that but would like to write that into the function if possible — Mrmoleje, Jul 20 '20 at 13:50
I think the solution you want is similar to this https://stackoverflow.com/questions/15772009/shuffling-permutating-a-dataframe-in-pandas. Only that you wany columns A and D unchanged . Is this true ? — smile, Jul 20 '20 at 16:28

score 0 · Answer 1 · answered Jul 20 '20 at 17:24

You could shuffle the required columns as below:

import numpy as np
import pandas as pd

# the data 
df = pd.DataFrame({'A':range(10), 'B':range(10), 
     'C':range(10), 'D':range(10)}) 

# shuffle 
df.B = np.random.permutation(df.B)
df.C =  np.random.permutation(df.C) 

# or shuffle this way (in place)
np.random.shuffle(df.B)
np.random.shuffle(df.C)

If you need to shuffle using your shuffle function:

def shuffle(df, n=1):

   for _ in range(n):
        # shuffle B
        np.random.shuffle(df.B)
        # shuffle C
        np.random.shuffle(df.C)
        print(df.B,df.C)   # comment this out as needed

    return df

You do not need to disturb columns A and D.

Shuffling a pandas dataframe

1 Answers1