An equivalent to R's %in% operator in Python

Question

I'm starting to learn a bit more about Python. One function I often want but don't know how to program/do in Python is the x %in% y operator in R. It works like so:

1:3 %in% 2:4 ##[1] FALSE TRUE TRUE

The first element in x (1) has no match in y so FALSE where as the last two elements of x (2 & 3) do have a match in y so they get TRUE.

Not that I expected this to work as it wouldn't have worked in R either but using == in Python I get:

[1, 2, 3] == [2, 3, 4] # False

How could I get the same type of operator in Python? I'm not tied to base Python if such an operator already exists elsewhere.

How is this a duplicate? The other question asks for a panda-specific solution and the answer has nothing to do with general concept of 'in'. — FMaz
– FMaz, Commented Jul 26, 2016 at 20:54
Could do for i in x: [].append(i in y) or [i in y for i in x] — data_steve
– data_steve, Commented Jul 26, 2016 at 21:10

FMaz · Accepted Answer · 2016-07-26 20:42:13Z

3

It's actually very simple.

if/for element in list-like object.

Specifically, when doing so for a list it will compare every element in that list. When using a dict as the list-like object (iterable), it will use the dict keys as the object to iterate through.

Cheers

Edit: For your case you should make use of "List Comprehensions".

[True for element in list1 if element in list2]

answered Jul 26, 2016 at 20:42

FMaz

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3 Comments

Konrad Rudolph Over a year ago

I’m not sure I understand your answer — if element in list-like object and for element in list-like object are two fundamentally different operations in Python. The second one performs iteration, not a membership test. The first one performs the membership test (see my answer) but the if isn’t part of the syntax.

FMaz Over a year ago

I know. I just wanted to demonstrate other uses of the 'in' keyword.

akrun Over a year ago

Good use of if. Plus one.

Konrad Rudolph · Accepted Answer · 2016-07-26 20:40:48Z

%in% is simply in in Python. But, like most other things in Python outside numpy, it’s not vectorised:

In [1]: 1 in [1, 2, 3] Out[1]: True In [2]: [1, 2] in [1, 2, 3] Out[2]: False

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