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?

Solution 1

The corresponding operator is |:

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

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

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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.

Solution 2

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

a | b

Comments

[Gerard]

The round brackets are important

[Frank]

| and np.logical_or behave differently in the presence of NaNs. See stackoverflow.com/q/37131462/2596586

[Alan]

Just a comment: or is not working here. Only | works.