NumPy | Python Methods and Functions

** **

** numpy.MaskedArray.median() ** is used to calculate the sum of masked array elements along a given axis.

Syntax:`numpy.ma.sum (arr, axis = None, dtype = None, out = None, keepdims = False)`

Parameters:

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: **

` `

` ` ` # Program Python explaining `

` # numpy.MaskedArray.sum () method `

` # import numy as geek `

` # and numpy.ma module as ma `

` import `

` numpy as geek `

` import `

` numpy.ma as ma `

` # create input array `

` in_arr `

` = `

` geek.array ([[`

` 1 `

`, `

` 2 `

`], [`

` 3 `

`, `

` - `

` 1 `

`], [`

` 5 `

`, `

` - `

` 3 `

`]]) `

` print `

` (`

` "Input array:" `

`, in_arr) `

` # Now we create a masked array. `

` # invalidating the entry. `

` mask_arr `

` = `

` ma.masked_array (in_arr, mask `

` = `

` [[`

` 1 `

`, `

` 0 `

`], [`

` 1 `

`, `

` 0 `

`], [`

` 0 `

`, `

` 0 `

`]]) `

` print `

` (`

` "Masked array:" `

`, mask_arr) `

` # apply MaskedArray.sum `

` # methods of the masked array `

` out_arr `

` = `

` ma. `

` sum `

` (mask_arr) `

` print `

` (`

` "sum of masked array along default axis: "`

`, out_arr) `

` `

** Output :**

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 ` ` |

** Output:**

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]

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