Element-wise logical OR in Pandas

All we need is an easy explanation of the problem, so here it is.

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?

How to solve :

I know you bored from this bug, So we are here to help you! Take a deep breath and look at the explanation of your problem. We have many solutions to this problem, But we recommend you to use the first method because it is tested & true method that will 100% work for you.

Method 1

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.

Method 2

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

a | b

Note: Use and implement method 1 because this method fully tested our system.
Thank you 🙂

All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0

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