Concatenating two Pandas columns based on a condition

I have two columns and I’m trying to make a new one depending if one has a null value or not. I have the following example and I´m trying to use the np.where() function but it doesn´t seems to work.

import pandas as pd 
import numpy as np 

# DF 1
a = pd.DataFrame([1,'nan',2],columns=['a1'])
# DF 2
b = pd.DataFrame(['hola','hola','hola'],columns=['b1']) 
# New Column
b['b2'] = np.where(a['a1'].astype(str) != 'nan', b['b1'] + a['a1'].astype(str)) 

The result for the new column ‘b2’ should be:


The np.where function also doesn´t has like an else option so I don´t know how to include that. I appreciate the help!

>Solution :

You need to "synchronize" a and b dataframes to make pairwise comparisons (possibly with pd.concat):

b['b2'] = pd.concat([a.replace({'nan': ''}), b], axis=1).apply(lambda x:x['b1'] + str(x['a1']), axis=1)

     b1     b2
0  hola  hola1
1  hola   hola
2  hola  hola2

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