How to combine 2 lists of pandas columns?

Question

Say I have a df like this:

      col1          col2
0.   [1, 2, 3]      [4, 5, 6]
1    [4, 6]         [43]
2.   [7, 11]        NaN
3.   None           [9, 9]
4.   []             [13, 17]

I want to combine the two columns into one combined list. For NaN and None values I would like to ignore them.
Expected results:

      col1          col2           col3
0.   [1, 2, 3]      [4, 5, 6]     [1, 2, 3, 4, 5, 6]
1    [4, 6]         43            [4, 6, 43]
2.   [7, 11]        NaN           [7, 11]
3.   None           [9, 9]        [9, 9]
4.   []             [13, 17]      [13, 17]
5.   NaN            NaN           NaN

I’ve looked at numpy and pandas functions and am unable to do this. Help.

Asked By: mha

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Source

Answer 1

Solution with remove missing values if not exist in both columns with DataFrame.stack and aggregation:

df['col3'] = df[['col1','col2']].stack().groupby(level=0).sum()

Or:

df = pd.DataFrame({'col1':[[1, 2, 3], [4, 6], [7, 11],  None, [], np.nan],
                   'col2':[[4, 5, 6], [43], np.nan, [9, 9],[13, 17], np.nan]})

df['col3'] = (df.stack()
                .groupby(level=0)
                .agg(lambda x: [z for y in x for z in y]))
print (df)
        col1       col2                col3
0  [1, 2, 3]  [4, 5, 6]  [1, 2, 3, 4, 5, 6]
1     [4, 6]       [43]          [4, 6, 43]
2    [7, 11]        NaN             [7, 11]
3       None     [9, 9]              [9, 9]
4         []   [13, 17]            [13, 17]
5        NaN        NaN                 NaN

Answered By: jezrael

Answer 2

Using numpy and keeping the NaN:

import numpy as np
df['col3'] = [np.r_[x].tolist() for x in zip(df['col1'], df['col2'])]

Output:

        col1       col2                col3
0  [1, 2, 3]  [4, 5, 6]  [1, 2, 3, 4, 5, 6]
1     [4, 6]         43          [4, 6, 43]
2    [7, 11]        NaN    [7.0, 11.0, nan]
3       None     [9, 9]        [None, 9, 9]
4         []   [13, 17]        [13.0, 17.0]

Answered By: mozway

How to combine 2 lists of pandas columns?

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