Pandas: Why is 'in' broken Series?

Asked May 18 '18 at 22:14

Active May 18 '18 at 22:34

Viewed 44 times

When I run

the_id in attrs['ID']
2941264 in pd.Series([2941264,2941273,2941273,2941282]) # or this

I get False. But when I run

any(attrs['ID'].isin([the_id]))

I get True.

How does a Pandas Series implement in?

That is, why does Series have this unintuitive behaviour?

And how could different results be produced from it?

edited May 18 '18 at 22:34

asked May 18 '18 at 22:14

ifly6

https://stackoverflow.com/questions/19960077/how-to-implement-in-and-not-in-for-pandas-dataframe – BENY May 18 '18 at 22:18
`in` operator is generally implemented someplace. Where is that place? – ifly6 May 18 '18 at 22:19
@Wen: Bad dupe. The questioner has already found `isin`; they want to know what's up with `in`. – user2357112 May 18 '18 at 22:19
@user2357112 check the answer https://stackoverflow.com/a/19960136/7964527 – BENY May 18 '18 at 22:20
@Wen: That still doesn't explain what `thing in some_series` means. – user2357112 May 18 '18 at 22:21
@user2357112 if you think not a dup, you can reopen it – BENY May 18 '18 at 22:23
Possible duplicate of [How to implement 'in' and 'not in' for Pandas dataframe](https://stackoverflow.com/questions/19960077/how-to-implement-in-and-not-in-for-pandas-dataframe) – DYZ May 18 '18 at 22:27
https://stackoverflow.com/questions/24841768/python-pandas-why-does-the-in-operator-work-with-indices-and-not-with-the-d @user2357112 how about this one . :-) – BENY May 18 '18 at 22:28
@Wen: That's a much better dupe target. – user2357112 May 18 '18 at 22:30

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