df.drop()

df.drop(columns=column_name or [col_1_name, ..., col_k_name])

Drops a single column, or every column in a list of column names, from df.

Input:

columns : string or list

Column name(s) to drop.

Returns:

A new DataFrame without the column(s) specified in columns.

Return Type:

DataFrame

---

pets = pets.assign(New_column_1=['this', 'is', 'a', 'new', 'column', 'I', 'assigned'], 
                  New_column_2=['this', 'is', 'another', 'new', 'column', 'I', 'assigned'])
pets

Index	ID	Species	Color	Weight	Age	Is_Cat	Owner_Comment	New_column_1	New_column_2
0	dog_001	dog	black	40	5	False	There are no bad dogs, only bad owners.	this	this
1	cat_001	cat	golden	1.5	0.2	True	My best birthday present ever!!!	is	is
2	cat_002	cat	black	15	9	True	****All you need is love and a cat.****	a	another
3	dog_002	dog	white	80	2	False	Love is a wet nose and a wagging tail.	new	new
4	dog_003	dog	black	25	0.5	False	Be the person your dog thinks you are.	column	column
5	ham_001	hamster	black	1	3	False	No, thank you!	I	I
6	ham_002	hamster	golden	0.25	0.2	False	No, thank you!	assigned	assigned
7	cat_003	cat	black	10	0	True	No, thank you!	.	.

pets = pets.drop(columns=['New_column_1', 'New_column_2'])
pets

Index	ID	Species	Color	Weight	Age	Is_Cat	Owner_Comment
0	dog_001	dog	black	40	5	False	There are no bad dogs, only bad owners.
1	cat_001	cat	golden	1.5	0.2	True	My best birthday present ever!!!
2	cat_002	cat	black	15	9	True	****All you need is love and a cat.****
3	dog_002	dog	white	80	2	False	Love is a wet nose and a wagging tail.
4	dog_003	dog	black	25	0.5	False	Be the person your dog thinks you are.
5	ham_001	hamster	black	1	3	False	No, thank you!
6	ham_002	hamster	golden	0.25	0.2	False	No, thank you!
7	cat_003	cat	black	10	0	True	No, thank you!