here is my use-case
df = pd.DataFrame({'A':[[(1,2),(3,4)],[(5,6),(7,8)]],'B':[[15,35],[55,75]]})
I would like to merge the "A" and "B" columns to get the result:
df['C'] = [[(1,2,15),(3,4,35)],[(5,6,55),(7,8,75)]]
Please feel free to propose a method with the lowest timing. Thanks
Just do:
df['C'] = [[ai + (bi,) for ai, bi in zip(a, b)] for a, b in df[['A', 'B']].to_numpy()]
print(df)
Output
A B C
0 [(1, 2), (3, 4)] [15, 35] [(1, 2, 15), (3, 4, 35)]
1 [(5, 6), (7, 8)] [55, 75] [(5, 6, 55), (7, 8, 75)]
You can use double zip solution with * for unpack tuples:
df['C'] = [[(*a, b) for a, b in zip(x, y)] for x, y in zip(df['A'],df['B'])]
print (df)
A B C
0 [(1, 2), (3, 4)] [15, 35] [(1, 2, 15), (3, 4, 35)]
1 [(5, 6), (7, 8)] [55, 75] [(5, 6, 55), (7, 8, 75)]
