Update column value if another column has a certain substring-CodePudding

I'm facing a lot of trouble on what seems to be a simple matter:

I have a column with some beverages names, but they are poluted with "12oz" and "Boxes". I want to get only the name of the beverages. Unfortunally, they are not typed in the same particular form, so i cant just [0:5] them. I know all the beverages names on the column, if that helps

Ex: Column name: WHISKY BALLANTINES12YO 12X1000 ML RESTAGE

Column Created based on the previous one: BALLANTINES

Thanks in advance,

EDIT Some other examples:

CHIVAS REGAL 12 ANOS 12X1L should be CHIVAS

VODKA ABSOLUT 12X1000ML should be ABSOLUT

CodePudding user response：

Just use replace statements and set regex to true, and replace with an empty string, like this:

df.replace('12oz', '', regex=True)

This is assuming you know what text you will have to replace.

CodePudding user response：

If you have the list of all the beverages, you can use pandas.Series.extract :

import re

list_of_bvr= ["ballantines", "chivas", "absolut"]

df["Col1"]= df["Col1"].str.extract(f"({'|'.join(list_of_bvr)})", flags=re.I, expand=False)

# Output :

print(df)

          Col1
0  BALLANTINES
1       CHIVAS
2      ABSOLUT