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