numpy.ma.count_masked#
- ma.count_masked(arr, axis=None)[source]#
Count the number of masked elements along the given axis.
- Parameters:
- arrarray_like
An array with (possibly) masked elements.
- axisint, optional
Axis along which to count. If None (default), a flattened version of the array is used.
- Returns:
- countint, 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
>>> a = np.arange(9).reshape((3,3)) >>> a = np.ma.array(a) >>> a[1, 0] = np.ma.masked >>> a[1, 2] = np.ma.masked >>> a[2, 1] = np.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) >>> np.ma.count_masked(a) 3
When the axis keyword is used an array is returned.
>>> np.ma.count_masked(a, axis=0) array([1, 1, 1]) >>> np.ma.count_masked(a, axis=1) array([0, 2, 1])