NumPy - average() function

The NumPy average() function is used to compute the weighted average along the specified axis. The syntax for using this function is given below:

Syntax

numpy.average(a, axis=None, weights=None, returned=False)

Parameters

`a`	`Required.` Specify an array containing data to be averaged. If a is not an array, a conversion is attempted.
`axis`	`Optional.` Specify axis or axes along which to average a. The default, axis=None, will average over all of the elements of the input array. If axis is negative it counts from the last to the first axis.
`weight`	`Optional.` Specify an array of weights associated with the values in a. The weights array can either be 1-D (in which case its length must be the size of a along the given axis) or of the same shape as a. If weights=None, then all data in a are assumed to have a weight equal to one.
`returned`	`Optional.` Default is False. If True, the tuple (average, sum_of_weights) is returned, otherwise only the average is returned.

Return Value

Returns the average along the specified axis when returned is False. When returned is set to True, returns a tuple with the average as the first element and the sum of the weights as the second element.

Exception

Raises ZeroDivisionError exception, When all weights along axis are zero.
Raises TypeError exception, When the length of 1D weights is not the same as the shape of a along axis.

Example: Average of all values

In the example below, average() function is used to calculate average of all values present in the array.

import numpy as np
Arr = np.array([[1,2],[3, 4]])

print("Array is:")
print(Arr)

#average of all values
print("\nAverage of values:", np.average(Arr))

The output of the above code will be:

Array is:
[[1 2]
 [3 4]]

Average of values: 2.5

Example: average() with axis parameter

When axis parameter is provided, averaging is performed over the specified axes. Consider the following example.

import numpy as np
Arr = np.array([[10,20,30],[70,80,90]])

print("Array is:")
print(Arr)

#averaging along axis=0
print("\nAverage along axis=0")
print(np.average(Arr, axis=0))

#averaging along axis=1
print("\nAverage along axis=1")
print(np.average(Arr, axis=1))

The output of the above code will be:

Array is:
[[10 20 30]
 [70 80 90]]

Average along axis=0
[40. 50. 60.]

Average along axis=1
[20. 80.]

Example: average() with weight parameter

In the example below, weight array is provided to calculate weighted average along the specified axis.

import numpy as np
Arr = np.array([[10,20],[80,90]])
w = np.array([0.4, 0.6])
print("Array is:")
print(Arr)

#averaging along axis=0
print("\nWeighted Average along axis=0")
print(np.average(Arr, axis=0, weights=w))

#averaging along axis=1
print("\nWeighted Average along axis=1")
print(np.average(Arr, axis=1, weights=w))

The output of the above code will be:

Array is:
[[10 20]
 [80 90]]

Weighted Average along axis=0
[52. 62.]

Weighted Average along axis=1
[16. 86.]

❮ NumPy - Functions