# Numpy MaskedArray.average() function | Python

`numpy.MaskedArray.average() ` function is used to return the weighted average of array over the given axis.

Syntax : `numpy.ma.average(arr, axis=None, weights=None, returned=False)`

Parameters:

arr :[ array_like] Input masked array whose data to be averaged. Masked entries are not taken into account in the computation.
axis :[ int, optional] Axis along which to average arr. If None, averaging is done over the flattened array.
weights : [array_like, optional] The importance that each element has in the computation of the average. If weights=None, then all data in arr are assumed to have a weight equal to one. If weights is complex, the imaginary parts are ignored.
returned :[ bool, optional] It indicates whether a tuple (result, sum of weights) should be returned as output (True), or just the result (False). Default is False.

Return : [ scalar or MaskedArray] The average along the specified axis. When returned is True, return a tuple with the average as the first element and the sum of the weights as the second element.

Code #1 :

 `# Python program explaining ` `# numpy.MaskedArray.average() method  ` `   `  `# importing numpy as geek   ` `# and numpy.ma module as ma  ` `import` `numpy as geek  ` `import` `numpy.ma as ma  ` `   `  `# creating input array   ` `in_arr ``=` `geek.array([[``1``, ``2``], [ ``3``, ``-``1``], [ ``5``, ``-``3``]]) ` `print` `(``"Input array : "``, in_arr)  ` `   `  `# Now we are creating a masked array.  ` `# by making  entry as invalid.   ` `mask_arr ``=` `ma.masked_array(in_arr, mask ``=``[[``1``, ``0``], [ ``1``, ``0``], [ ``0``, ``0``]])  ` `print` `(``"Masked array : "``, mask_arr)  ` `   `  `# applying MaskedArray.average     ` `# methods to masked array ` `out_arr ``=` `ma.average(mask_arr)  ` `print` `(``"normal average of masked array : "``, out_arr)  `

Output:

```Input array :  [[ 1  2]
[ 3 -1]
[ 5 -3]]
[-- -1]
[5 -3]]
normal average of masked array :  0.75
```

Code #2 :

 `# Python program explaining ` `# numpy.MaskedArray.average() method  ` `   `  `# importing numpy as geek   ` `# and numpy.ma module as ma  ` `import` `numpy as geek  ` `import` `numpy.ma as ma  ` `   `  `# creating input array   ` `in_arr ``=` `geek.array([[``1``, ``2``], [ ``3``, ``-``1``], [ ``5``, ``-``3``]]) ` `print` `(``"Input array : "``, in_arr)  ` `   `  `# Now we are creating a masked array.  ` `# by making  entry as invalid.   ` `mask_arr ``=` `ma.masked_array(in_arr, mask ``=``[[``1``, ``0``], [ ``1``, ``0``], [ ``0``, ``0``]])  ` `print` `(``"Masked array : "``, mask_arr)  ` `   `  `# applying MaskedArray.average     ` `# methods to masked array ` `out_arr ``=` `ma.average(mask_arr, weights ``=``[[``0``, ``1``], [ ``0``, ``2``], [ ``3``, ``1``]])  ` `print` `(``"weighted average of masked array : "``, out_arr)  `

Output:

```Input array :  [[ 1  2]
[ 3 -1]
[ 5 -3]]
[-- -1]
[5 -3]]
weighted average of masked array :  1.7142857142857142
```

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