Extract the count of positive and negative values from an array

Question

I need to work with an array to make some computations. I have the following data:

x = [[81, 68, 71, 71, 67, -72], [79, 77, 88, 88, 59, -71], [67, 71, 68, 68, 85, -66]]

and I would need to play with the data and extract from each column the number of positive and negative values so the output should be like:

positive_value = [3,3,3,3,0]
negative_vaue = [0,0,0,0,3]

I gave it a try using a for loop with no success and with Numpy as well, but I do not really know how to use it.

What is the best way to get that result?

Answer 1

Probably the most elegant way is to convert it to a numpy array first, then perform a condition >= 0 on it, and then calculate the sum(..) over the first axis:

import numpy as np

np.sum(np.array(x) >= 0, axis=0)

This then yields:

>>> np.sum(np.array(x) >= 0, axis=0)
array([3, 3, 3, 3, 3, 0])

So by using np.array(x) >= 0, we obtain a 2d-array of booleans:

>>> np.array(X) >= 0
array([[ True,  True,  True,  True,  True, False],
       [ True,  True,  True,  True,  True, False],
       [ True,  True,  True,  True,  True, False]], dtype=bool)

Since True counts as one, and False as zero, by calculing the sum per column, we thus count the number of positive numbers.

In case you want to count strictly positive numbers (so only larger than zero), you should omit the = in >=:

>>> np.sum(np.array(x) > 0, axis=0)
array([3, 3, 3, 3, 3, 0])