Shuffle a pandas dataframe by groups

Assuming you want to shuffle by sampleID. First df.groupby, shuffle (import random first), and then call pd.concat:

import random

groups = [df for _, df in df.groupby('sampleID')]
random.shuffle(groups)

pd.concat(groups).reset_index(drop=True)

   sampleID  col1  col2
0         2     1    20
1         2     2    94
2         2     3    99
3         1     1    63
4         1     2    23
5         1     3    73
6         3     1    73
7         3     2    56
8         3     3    34

You reset the index with df.reset_index(drop=True), but it is an optional step.

I found this to be significantly faster than the accepted answer:

ids = df["sampleID"].unique()
random.shuffle(ids)
df = df.set_index("sampleID").loc[ids].reset_index()

for some reason the pd.concat was the bottleneck in my usecase. Regardless this way you avoid the concatenation.