numpy.MaskedArray.mean() is used to return the average value of masked array elements along a given axis. Here, masked entries are ignored and leaf items that are not leaf will be masked.
numpy.ma.mean (axis = None, dtype = None, out = None)
axis: [int, optional] Axis along which the mean is computed. The default (None) is to compute the mean over the flattened array.
dtype: [dtype, optional] Type of the returned array, as well as of the accumulator in which the elements are multiplied.
out: [ndarray, optional] A location into which the result is stored.
– & gt; If provided, it must have a shape that the inputs broadcast to.
– & gt; If not provided or None, a freshly-allocated array is returned.
Return: [mean_along_axis, ndarray] A new array holding the result is returned unless out is specified, in which case a reference to out is returned.
Code # 1:
Input array: [[1 2] [3 -1] [5 -3]] Masked array: [[- 2] [- -1] [5 -3]] mean of masked array along default axis: 0.75
Code # 2:
Input array: [[1 0 3] [4 1 6]] Masked array: [[1 0 3] [4 1 -]] mean of masked array along 0 axis: [2.5 0.5 3.0] mean of masked array along 1 axis: [1.3333333333333333 2.5]