Python NumPy – Change NaN to Zero in Array

To remove NaN values from a NumPy array x:

x = x[~numpy.isnan(x)]

Explanation

The inner function numpy.isnan returns a boolean/logical array which has the value True everywhere that x is not-a-number. Since we want the opposite, we use the logical-not operator ~ to get an array with Trues everywhere that x is a valid number.

Lastly, we use this logical array to index into the original array x, in order to retrieve just the non-NaN values.

np.nan has type float: arrays containing it must also have this datatype (or the complex or object datatype) so you may need to cast arr before you try to assign this value.

The error arises because the string value 'nan' can't be converted to an integer type to match arr's type.

>>> arr = arr.astype('float')
>>> arr[arr == 0] = 'nan' # or use np.nan
>>> arr
array([[ nan,   1.,   2.],
       [  3.,   4.,   5.]])