numpy.ma.MaskedArray.count#

method

ma.MaskedArray.count(axis=None, keepdims=<no value>)[source]#

Count the non-masked elements of the array along the given axis.

Parameters:

axisNone or int or tuple of ints, optional: Axis or axes along which the count is performed. The default, None, performs the count over all the dimensions of the input array. axis may be negative, in which case it counts from the last to the first axis. If this is a tuple of ints, the count is performed on multiple axes, instead of a single axis or all the axes as before.
keepdimsbool, optional: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the array.

Returns:

resultndarray or scalar: An array with the same shape as the input array, with the specified axis removed. If the array is a 0-d array, or if axis is None, a scalar is returned.

See also

ma.count_masked: Count masked elements in array or along a given axis.

Examples

>>> import numpy.ma as ma
>>> a = ma.arange(6).reshape((2, 3))
>>> a[1, :] = ma.masked
>>> a
masked_array(
  data=[[0, 1, 2],
        [--, --, --]],
  mask=[[False, False, False],
        [ True,  True,  True]],
  fill_value=999999)
>>> a.count()
3

When the axis keyword is specified an array of appropriate size is returned.

>>> a.count(axis=0)
array([1, 1, 1])
>>> a.count(axis=1)
array([3, 0])