How to remove possible suffix repetitions from a str column?

Consider the following dataframe, where the suffix in a str column might be repeating itself:

    Book
0   Book1.pdf
1   Book2.pdf.pdf
2   Book3.epub
3   Book4.mobi.mobi
4   Book5.epub.epub

Desired output (removed suffixes where needed)

    Book
0   Book1.pdf
1   Book2.pdf
2   Book3.epub
3   Book4.mobi
4   Book5.epub

I have tried splitting on the . character and then counting occurences of the last item to check if there is duplication.

I have used file paths only to illustrate my point! The contents of the column could be something different than paths!

>Solution :

Use a regex with a capturing group + reference and str.replace:

df['Book'] = df['Book'].str.replace(r'(\.[^.]+)\1$', r'\1', regex=True)

# or
df['Book'] = df['Book'].str.replace(r'(\.[^.]+)(?=\1)$', '', regex=True)

Output:

         Book
0   Book1.pdf
1   Book2.pdf
2  Book3.epub
3  Book4.mobi
4  Book5.epub

regex demo 1

regex demo 2

generalization

if you want something generic that doesn’t depend on the .:

df['Book'] = df['Book'].str.replace(r'(.+)\1$', r'\1', regex=True)

regex demo