np.logical_or() in Numpy – Python

Question

Please anyone can explain me this resulting code

x = np.array([9, 5])
y = np.array([16, 12])

np.logical_or(x < 5, y > 15)

Result -> array([ True, False])

Since:

np.logical_or(x < 5, y > 15)
x < 5 = [False, False], y > 15 = [True, False]

I think it should be:

[False or False, False or True] = [False, True]

In fact Python giving the result like this:

[False or True, False or False] = [True, False]

Why the result is not [False, True], but in fact python giving the result [True, False]?
It is not match with the order of operation np.logical_or(x < 5, y > 15)

Even I tried ChatGPT explanation I still don’t have clear understanding of this concept.

Please I would be appreciate, if anyone can explain the background of python process in detail step by step.

Asked By: Luki_DataScience

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Source

Answer 1

You are interpreting the result wrong. Numpy’s logical_or can have a few arguments as filters. In your case, the input arguments are x < 5 and y > 15. It then combines them together with an or operator.

The first argument x < 5 would lead to: [False, False]
The second argument y > 15 would lead to: [True, False]
The final result = [False or True, False or False] = [True, False]

Answered By: physicalattraction

np.logical_or() in Numpy – Python

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