Element-wise logical OR in Pandas

Question

I would like the element-wise logical OR operator. I know "or" itself is not what I am looking for.

I am aware that AND corresponds to & and NOT, ~. But what about OR?

score 147 · Accepted Answer · edited Jun 16 '19 at 03:44

147

The corresponding operator is |:

 df[(df < 3) | (df == 5)]

would elementwise check if value is less than 3 or equal to 5.

If you need a function to do this, we have np.logical_or. For two conditions, you can use

df[np.logical_or(df<3, df==5)]

Or, for multiple conditions use the logical_or.reduce,

df[np.logical_or.reduce([df<3, df==5])]

Since the conditions are specified as individual arguments, parentheses grouping is not needed.

More information on logical operations with pandas can be found here.

edited Jun 16 '19 at 03:44

cs95

answered Jul 16 '14 at 08:24

deinonychusaur

37

The round brackets *are* important – Gerard Aug 08 '16 at 15:22
5

`|` and `np.logical_or` behave differently in the presence of NaNs. See https://stackoverflow.com/q/37131462/2596586 – Frank Nov 14 '19 at 00:18
Just a comment: `or` is not working here. Only `|` works. – S. Wu Mar 15 '20 at 00:17

score 11 · Answer 2 · answered May 12 '17 at 21:35

11

To take the element-wise logical OR of two Series a and b just do

a | b

answered May 12 '17 at 21:35

Jonathan Stray

2 Answers2