replace part of an int or string in a pandas dataframe column upon condition

I have a pandas dataframe with a column representing dates but saved in int format. For several dates I have a 13th and a 14th month. I would like to replace these 13th and 14th months by the 12th month. And then, eventually transform it into date_time format.

Original_date
20190101
20191301
20191401

New_date
20190101
20191201
20191201

I tried by replacing the format into string then replace only based on the index of the months in the string [4:6], but it didn’t work out:

df.original_date.astype(str)
for string in df['original_date']:
    if string[4:6]=="13" or string[4:6]=="14":
        string.replace(string, string[:4]+ "12" + string[6:])
print(df['original_date'])

>Solution :

You can use .str.replace with regex

df['New_date'] = df['Original_date'].astype(str).str.replace('(\d{4})(13|14)(\d{2})', r'\g<1>12\3', regex=True)

print(df)

   Original_date  New_date
0       20190101  20190101
1       20191301  20191201
2       20191401  20191201