How to write in excel/pandas Dataframe of two different variables value in same column

Question

I'm new to pandas and trying to figure out how to add two different variables values in the same column.

import pandas as pd
import requests
from bs4 import BeautifulSoup
itemproducts = pd.DataFrame()

url = 'https://www.trwaftermarket.com/en/catalogue/product/BCH720/'
r = requests.get(url)
soup = BeautifulSoup(r.content,'lxml')

code_name = soup.find_all('div',{'class':'col-sm-6 intro-section reset-margin'})
for head in code_name:
    item_code  = head.find('span',{'class':'heading'}).text
    item_name  = head.find('span',{'class':'subheading'}).text

for tab_ in tab_4:
    ab = tab_.find_all('td')
    make_name1    = ab[0].text.replace('Make','')
    code1         = ab[1].text.replace('OE Number','')
    make_name2    = ab[2].text.replace('Make','')
    code2         = ab[3].text.replace('OE Number','')

itemproducts=itemproducts.append({'CODE':item_code,
                                'NAME':item_name,
                                'MAKE':[make_name1,make_name2],
                                'OE NUMBER':[code1,code2]},ignore_index=True)

OUTPUT (Excel image)

What actually I want

Answer 1

In pandas you must specify all the data in the same length. So, in this case, I suggest that you specify each column or row as a fixed length list. For those that have one member less, append a NaN to match.

Answer 2

I couldn't reproduce the results from your script. However, based on your end dataframe, perhpas you can make use of explode together with apply the dataframe in the end:

#creating your dataframe
itemproducts = pd.DataFrame({'CODE':'BCH720','MAKE':[['HONDA','HONDA']],'NAME':['Brake Caliper'],'OE NUMBER':[['43019-SAA-J51','43019-SAA-J50']]})

>>> itemproducts
      CODE                MAKE           NAME                           OE NUMBER
0  BCH720  ['HONDA', 'HONDA']  Brake Caliper  ['43019-SAA-J51', '43019-SAA-J50']

#using apply method with explode on 'MAKE' and 'OE NUMBER'
>>> itemproducts.apply(lambda x: x.explode() if x.name in ['MAKE', 'OE NUMBER'] else x)
     CODE   MAKE           NAME      OE NUMBER
0  BCH720  HONDA  Brake Caliper  43019-SAA-J51
0  BCH720  HONDA  Brake Caliper  43019-SAA-J50

Answer 3

I found a similar question here on stackoverflow that can help you. Another approach is to use explode function from Pandas Dataframe.

Below I put an example from pandas documentation.

>>> df = pd.DataFrame({'A': [[1, 2, 3], 'foo', [], [3, 4]], 'B': 1})
>>> df
           A  B
0  [1, 2, 3]  1
1        foo  1
2         []  1
3     [3, 4]  1

>>> df.explode('A')
     A  B
0    1  1
0    2  1
0    3  1
1  foo  1
2  NaN  1
3    3  1
3    4  1