How to select multiple rows in a pandas column to create a new dataframe

Asked Apr 03 '18 at 12:21

Active Mar 30 '22 at 15:58

Viewed 1.8k times

I have a Pandas Dataframe and there are some columns that I want to keep in terms of location and others I do not.

I know that when selecting a specific value in a column to get a row I can use:

x = df[df['location']=='Aberdeen']

However, how can I do it for many locations without having to do them individually and then concatenate?

This is what Ive tried:

x = df[[df['location']=='Aberdeen' & 'Glasgow' & 'London']]

But I am receiving a:

TypeError: 'Series' objects are mutable, thus they cannot be hashed

I know there must be a super simple solution to this but I haven't figured it out, please help.

edited Mar 30 '22 at 15:58

vvvvv

asked Apr 03 '18 at 12:21

snow_fall

10

`df[df["location"].isin(["Aberdeen", "Glasgow", "London"])]` might do the trick – Angus Williams Apr 03 '18 at 12:23
@AngusWilliams - Yes, you are right. – jezrael Apr 03 '18 at 12:25
Initially typed up as an answer but it's been marked as a dupe. – Angus Williams Apr 03 '18 at 12:26
1

@AngusWilliams Thank you! I will use that. Did not realise it was a duplicate because I didn't even know how to structure the title Question. I'll be checking that out and shutting this one down. Thanks again all. – snow_fall Apr 03 '18 at 12:30

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