Check if a string value of a column in a Pandas DataFrame starts with the value of another column

Question

I am trying to concatenate two string columns col1 and col2 in a Pandas DataFrame. But I do not want to concatenate them if col2’s value already begins with the value of col1. In this case I want to use col2 without concatenation. This would be the expected behavior:

col1	col2	result
ABC	ABC	ABC
ABC	XYC	ABCXYZ
ABC	abc123	abc123

I tried this code:

import pandas as pd

df = pd.DataFrame({
    'col1': ['ABC', 'ABC', 'AbC'],
    'col2': ['ABC', 'XYZ', 'abc123'],
})


df['result'] = df['col2'].where(df['col2'].str.lower().str.startswith(df['col1'].str.lower()), df['col1'] + df['col2'])

df

But that results in:

col1	col2	result
ABC	ABC	ABCABC
ABC	XYC	ABCXYZ
ABC	abc123	AbCabc123

For testing purposes I used a string literal as parameter for startswith and received the expected results:

df['result'] = df['col2'].where(df['col2'].str.lower().str.startswith('abc'), df['col1'] + df['col2'])

I found out that the result of the startswith function always returns NaN:

df['result'] = df['col2'].str.lower().str.startswith(df['col1'].str.lower())

col1	col2	result
ABC	ABC	NaN
ABC	XYC	NaN
ABC	abc123	NaN

If I replace the startswith parameter with a string literal I receive booleans as expected:

df['result'] = df['col2'].str.lower().str.startswith('abc')

col1	col2	result
ABC	ABC	True
ABC	XYC	False
ABC	abc123	True

I understand that it seems to be a problem to use a series as a parameter in the startswith function. But I do not get it to work.

I am very new to Python and Pandas, I intensively used search engines and stackoverflow's search function before I created my first post. What do I have to change in my code to accomplish the desired behavior? Any help is highly appreciated. Thanks!