How to concatenate data frames with unequal number of rows and different column names

Question

I am trying to concatenate four data frames with an unequal number of rows and different column names. Here I am placing my code and output what I am getting.

import pandas as pd data1 = pd.DataFrame({'Col':[33,44,55,67], 'Col1':[44,55,55,555]}) data2 = pd.DataFrame({'Col2':[33,44], 'Col3':[22,22]}) data3 = pd.DataFrame({'Col4':[33,44,44], 'Col5':[22,22,44]}) data4 = pd.DataFrame({'Col6':[33], 'Col7':[22], 'Col8':[44]}) data5 = pd.concat([data1, data2, data3, data4]) data5

here is my actual output

what I am expecting is:

Thanks in advance

What is the output size you d expect if different number of rows given? Max of them all? — armamut
– armamut, Commented Jan 28, 2021 at 9:50
Could you also please describe what have you tried to solve? — armamut
– armamut, Commented Jan 28, 2021 at 9:51

jezrael · Accepted Answer · 2021-01-28 09:57:08Z

3

You can use concat with axis=1, but first repeat values for match maximal lengths of rows:

dfs = [data1, data2, data3, data4] maxlen = len(max(dfs, key=len)) print (maxlen) 4 dfs = [pd.concat([x] * int(np.ceil(maxlen / len(x))), ignore_index=True).iloc[:maxlen] for x in dfs] data5 = pd.concat(dfs, axis=1) print (data5) Col Col1 Col2 Col3 Col4 Col5 Col6 Col7 Col8 0 33 44 33 22 33 22 33 22 44 1 44 55 44 22 44 22 33 22 44 2 55 55 33 22 44 44 33 22 44 3 67 555 44 22 33 22 33 22 44