[python] numpy.where() detailed, step-by-step explanation / examples

I have trouble properly understanding numpy.where() despite reading the doc, this post and this other post.

Can someone provide step-by-step commented examples with 1D and 2D arrays?

This question is related to python numpy scipy

The answer is


Here is a little more fun. I've found that very often NumPy does exactly what I wish it would do - sometimes it's faster for me to just try things than it is to read the docs. Actually a mixture of both is best.

I think your answer is fine (and it's OK to accept it if you like). This is just "extra".

import numpy as np

a = np.arange(4,10).reshape(2,3)

wh = np.where(a>7)
gt = a>7
x  = np.where(gt)

print "wh: ", wh
print "gt: ", gt
print "x:  ", x

gives:

wh:  (array([1, 1]), array([1, 2]))
gt:  [[False False False]
      [False  True  True]]
x:   (array([1, 1]), array([1, 2]))

... but:

print "a[wh]: ", a[wh]
print "a[gt]  ", a[gt]
print "a[x]:  ", a[x]

gives:

a[wh]:  [8 9]
a[gt]   [8 9]
a[x]:   [8 9]

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