[FIXED] Find most common values for each row consist of lists

Issue

I have pd.DataFrame in which one column contains lists as the values. I want to create another column which consist only the most common value from that column. Example dataframe:

    col_1
0   [1, 2, 3, 3]
1   [2, 2, 8, 8, 7]
2   [3, 4]

And the expected dataframe is

    col_1           col_2
0   [1, 2, 3, 3]    [3]
1   [2, 2, 8, 8, 7] [2, 8]
2   [3, 4]          [3, 4]

I tried to do

from statistics import mode
df['col_1'].apply(lambda x: mode(x)) 

But it is showing the most common list in that column.

I also tried to use pandas mode function directly on that column, it also did not help. Is there any way to find the most common value(s)?

Solution

Using mode per group:

df['col_2'] = (df['col_1']
               .explode()
               .groupby(level=0)
               .apply(lambda x: x.mode().tolist())
              )

output:

             col_1   col_2
0     [1, 2, 3, 3]     [3]
1  [2, 2, 8, 8, 7]  [2, 8]
2           [3, 4]  [3, 4]

Answered By - mozway