How to match a word from column and compare with other column in pandas dataframe I have the below dataframe

Text                                Keywords       Type
It’s a roll-on tube                 roll-on        ball
It is barrel                        barrel         barr
An unknown shape                                   others
it’s a assembly                     assembly       assembly
it’s a sealing assembly             assembly       factory
its a roll-on double                roll-on        factory


I have first found out the keywords, and based on the keyword and its corresponding type, it should true or false

For example,
when the keyword is roll-on , the type should be "ball" or "others"
when the keyword is barrel, the type should be "barr" or "others"

Output

Text                                Keywords       Type         Result
It’s a roll-on tube                 roll-on        ball         True
It is barrel                        barrel         barr         True
An unknown shape                                   others       False
it’s a assembly                     assembly       assembly     True
it’s a sealing assembly             assembly       factory      True
its a roll-on double                roll-on        factory      False
If you know the rules, then you can code them up as you would usually do.
For e.g.
df['Keywords'] == &quot;roll-on&quot; &amp; (df['Type'] == &quot;ball&quot; | df['Type'] == &quot;others&quot;) =&gt; df['Result'] = True
If you have too many rules and associations to manually code, you could consider using a look-up table + merge procedure. Here you would store all the rules and associations as a table (i.e. this would include Keywords, Type, and Result), and merge Result back on to your original dataframe (by Keywords and Type).