Pandas, concatenating values of columns.

Question

I have found answers to this question on here before, but none of them seem to work for me. Right now I have a data frame with a list of clients and their address. However, each address is separated into many columns and i'm trying to put them all under one.

The code I have so far read as so:

data1_df['Address'] = data1_df['Address 1'].map(str) + ", " + data1_df['Address 2'].map(str) + ", " +  data1_df['Address 3'].map(str) + ", " + data1_df['city'].map(str) + ", " +  data1_df['city'].map(str) + ", " +  data1_df['Province/State'].map(str) + ", " +  data1_df['Country'].map(str) + ", " +  data1_df['Postal Code'].map(str)  

However, the error I get is: TypeError: Unary plus expects numeric dtype, not object

I'm not sure why it's not accepting the strings as they are and using the + operator. Shouldn't the plus accommodate objects?

Answer 1

Hopefully you'll find this example helpful:

import pandas as pd
import numpy as np

df = pd.DataFrame({'A': [1,2,3],
                   'B': list('ABC'),
                   'C': [4,5,np.nan],
                   'D': ['One', np.nan, 'Three']})

addColumns = ['B', 'C', 'D']

df['Address'] = df[addColumns].astype(str).apply(lambda x: ', '.join([i for i in x if i != 'nan']), axis=1)

df

#   A  B    C      D      Address
#0  1  A  4.0    One  A, 4.0, One
#1  2  B  5.0    NaN       B, 5.0
#2  3  C  NaN  Three     C, Three

The above will work as str representation of NaN is nan.

Or you can make it with filling NaN with empty strings:

df['Address'] = df[addColumns].fillna('').astype(str).apply(lambda x: ', '.join([i for i in x if i]), axis=1)