# 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.

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