numpy.MaskedArray.median() is used to calculate the sum of masked array elements along a given axis.
numpy.ma.sum (arr, axis = None, dtype = None, out = None, keepdims = False)
Parameters: strong >
arr: [ndarray] Input masked array.
axis: [int, optional] Axis along which the sum is computed. The default (None) is to compute the sum 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.
keepdims: [bool, 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 input array.
Return: [sum_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]] sum of masked array along default axis: 3
Code # 2:
< code class = "plain"> in_arr
Input array: [[1 0 3] [4 1 6]] Masked array: [[1 0 3] [4 1 -]] sum of masked array along 0 axis: [5 1 3] sum of masked array along 1 axis: [4 5] pre>
Data and storage models are the basis for big data ecosystem stacks. While storage model captures the physical aspects and features for data storage, data model captures the logical representation and...
If you can program, you are ready to grapple with Bayesian statistics. In this book, you'll learn how to solve statistical problems using Python code instead of math formulas, using discrete probabili...
Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series), 1st Edition. Pandas for Everyone brings together the practical knowledge and insights you need to solve real-worl...
Managing and analyzing data have always offered the greatest benefits and the greatest challenges for organizations of all sizes and across all industries. Businesses have long struggled with finding ...