Pattern matching on a website URL with Pandas DataFrame

Question

I am trying to solve a slightly complex project with Pattern matching for a website URL.

I have a particular column that contains URL with several informat

Answer 1

Remove data=, split by everything you see:

df_split = df['input'].str.replace('data=', '').str.split(r' |/|\?|\.', expand=True).replace('', np.nan).dropna(how='all', axis=1)
then you can rename your columns as you wish.

Edit: I added the dropping of empty columns.

Edit2: to take into account the absent hostname, split separately:

df_split1 = df['input'].str.split(r'\?data=', expand=True)
df_left = df_split1.loc[:, 0].str.rsplit(r'/', n=5, expand=True)
df_right = df_split1.loc[:, 1].str.split(r'\.| ', expand=True)

df_left['option_a'] = df_left.iloc[:, 0].str.split(r'/', expand=True).iloc[:, -1].fillna(df_left.iloc[:, 0])
df_left['sitename'] = df_left.iloc[:, 0].apply(lambda x: np.NaN if '/' not in x else re.split(r'/', x)[0])

then concat

df = pd.concat([df_left, df_right], axis=1).iloc[:, 1:].replace('', np.nan).dropna(how='all', axis=1)

then do the remaining renaming of the columns.