CODEWITHSUNDEEP
pythonarraysnumpyscikit-learnna
Robin Kohrs
Robin Kohrs

Reputation: 697

Convert specific value in numpy array to NAN

I have a two-dimensional numpy-array. It has a shape of (6994, 6994). There are many values of -1000 which I would like to encode as NAN. I tried:

array[array == -1000] = np.NAN, but this gives me the error cannot convert float NaN to integer

When I tried to write a function:

def valtona(array, val):
    for i in array:
        for j in array:
            if array[i,j] == -1000:
                array[i,j] = np.NAN

I get: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

I know there are some questions out there regarding the same issue, but I still didn't manage to fix it.

Upvotes: 2

Views: 3318

Answers (2)

Ethan
Ethan

Reputation: 1373

You can use np.isclose() and set parameters to meet your needs to overcome the precision challenge of working with floats. 

>>> a
array([ 0.,  1.,  2.,  4.,  4.,  5.,  6.,  7.,  8.,  9.])
>>> a[3]
4.0000000000001004
>>> a[4]
4.0
>>> np.isclose(a,[4.0], .00000001, .00000001)
array([False, False, False,  True,  True, False, False, False, False, False], dtype=bool)
>>> np.isclose(a,[4.0])
array([False, False, False,  True,  True, False, False, False, False, False], dtype=bool)
>>> a[np.isclose(a,[4.0], .00000001, .00000001)]=np.nan
>>> a
array([  0.,   1.,   2.,  nan,  nan,   5.,   6.,   7.,   8.,   9.])

Upvotes: 1

0buz
0buz

Reputation: 3503

You can still use 

array[array == -1000] = np.NAN

You just need to convert it to float first.

array=array.astype('float')
array[array == -1000] = np.NAN

Upvotes: 4

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