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numpy.ma.count_masked

numpy.ma.count_masked(arr, axis=None) [source]

Count the number of masked elements along the given axis.

Parameters:
arr : array_like

An array with (possibly) masked elements.

axis : int, optional

Axis along which to count. If None (default), a flattened version of the array is used.

Returns:
count : int, ndarray

The total number of masked elements (axis=None) or the number of masked elements along each slice of the given axis.

See also

MaskedArray.count
Count non-masked elements.

Examples

>>> import numpy.ma as ma
>>> a = np.arange(9).reshape((3,3))
>>> a = ma.array(a)
>>> a[1, 0] = ma.masked
>>> a[1, 2] = ma.masked
>>> a[2, 1] = ma.masked
>>> a
masked_array(
  data=[[0, 1, 2],
        [--, 4, --],
        [6, --, 8]],
  mask=[[False, False, False],
        [ True, False,  True],
        [False,  True, False]],
  fill_value=999999)
>>> ma.count_masked(a)
3

When the axis keyword is used an array is returned.

>>> ma.count_masked(a, axis=0)
array([1, 1, 1])
>>> ma.count_masked(a, axis=1)
array([0, 2, 1])

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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.ma.count_masked.html