element selection in numpy array

Question

How can I subset the required array from original array(data) converting other element as np.nan?

import numpy as np

data = np.array([1,1,1,2,2,2,3,3,3,4,4,4,5,5,5])

required = np.where((data <= 2) & (data >= 4),data,np.nan)

print (required)

The required array must be as follows:

[1,1,1,2,2,2,nan,nan,nan,4,4,4,5,5,5]

As a side note, your desired output is impossible (except by using dtype=object), because nan is a float, and cannot be stored in an int array. So, you can have [1., 1., …, nan, …, 5., 5.], but not [1, 1, …, nan, …, 5, 5]. — abarnert
– abarnert, Commented Dec 24, 2013 at 23:12

DSM · Accepted Answer · 2013-12-24 22:07:22Z

3

I think you want or, not and (or, here, | not &):

>>> import numpy as np
>>> data = np.array([1,1,1,2,2,2,3,3,3,4,4,4,5,5,5])
>>> required = np.where((data <= 2) | (data >= 4),data,np.nan)
>>> required
array([  1.,   1.,   1.,   2.,   2.,   2.,  nan,  nan,  nan,   4.,   4.,
         4.,   5.,   5.,   5.])

answered Dec 24, 2013 at 22:07

DSM

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1 Comment

abarnert Over a year ago

Yep, data <= 2 and data >= 4 isn't possible for any value of data, so he ends up with all nans…

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