Handling nonexistent values

The power of NumPy's indexing capabilities comes in handy when preprocessing data that we have just read in from a text file. Most likely, this will contain invalid values that we will mark as not being real numbers, using numpy.NAN, as shown in the following code:

>>> # let's pretend we have read this from a text file:
>>> c = np.array([1, 2, np.NAN, 3, 4])
array([ 1., 2., nan, 3., 4.])
>>> np.isnan(c)
array([False, False, True, False, False], dtype=bool)
>>> c[~np.isnan(c)]
array([ 1., 2., 3., 4.])
>>> np.mean(c[~np.isnan(c)]) 
2.5