Count elements in numpy array between bounds

Asked Jul 13 '18 at 00:20

Active Jul 13 '18 at 00:20

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Given an array such that:

arr = np.array([0,0,1,1,1,2,2,3,3,3,3,3,4,4,5,5,5,5,5,6])

I want to know the frequency of values >=0 & <1, >=1 & <2, >=2 & <3...etc

so I would get an new array like:

freq =[2,3,2,5,2,5,1].

I can use np.where((arr>=0)&(arr<1)) but this changes the shape of arr. Is there a pythonic way of getting the frequency of values over an interval of 1?

asked Jul 13 '18 at 00:20

Nathan Thomas

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Do you actually have integers and single integer intervals? Because `np.bincount` is likely all you need in that case. If not, `np.histogram`. – miradulo Jul 13 '18 at 00:23
the interval range will be integer as in the question but the values in arr may be either floats or integers – Nathan Thomas Jul 13 '18 at 00:26
Then `np.histogram(arr, bins=7, range=(0, 7))` for instance. – miradulo Jul 13 '18 at 00:29
so for clarity, this is inclusive of the lower limit but not the upper limit, correct? so for example >=0 & < 1 – Nathan Thomas Jul 13 '18 at 00:32
Yep, as noted in the [docs](https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html). – miradulo Jul 13 '18 at 00:34

Count elements in numpy array between bounds

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