# NumPy power()

The power() function is used to raise the elements of an array to a specified power.

### Example

import numpy as np

# create an array for the base values
base = np.array([2, 3, 4])

# create an array for the exponent values
exponent = np.array([2, 3, 4])

# use power() to raise the base values to the power of the corresponding exponent values result = np.power(base, exponent)
print(result) # Output : [ 4 27 256]

## power() Syntax

The syntax of power() is:

numpy.power(base, exponent, out=None)

## power() Arguments

The power() function takes one argument:

• base - the input array containing base values
• exponent - the exponent value or array, which can be a scalar or an array of the same shape as base.
• out (optional) - the output array where the result will be stored

## power() Return Value

The power() function returns an array that contains the elements of the base array raised to the power of the corresponding elements in the exponent array.

## Example 1: power() With Scalar Exponent

import numpy as np

# create an array for the base values
base = np.array([1, 2, 3, 4, 5])

# specify the exponent value
exponent = 3

# use power() to raise the base values to the specified exponent result = np.power(base, exponent)
print(result)

Output

[  1   8  27  64 125]

In this example, we have used the power() function to raise each element in the base array to the power of the specified exponent.

## Example 2: power() With Array of Exponent Values

import numpy as np

# create an array for the base values
base = np.array([2, 3, 4])

# create an array for the exponent values
exponent = np.array([4, 2, 1])

# use power() to raise the base values to the power of the corresponding exponent values result = np.power(base, exponent)
print(result)

Output

[16  9  4]

## Example 3: Use of out Argument in power()

import numpy as np

base = np.array([7, 8, 9, 10, 12])
exponent = 2

# create an empty array with the same shape as the base array
result = np.zeros_like(base)
# calculate the power and store the result in the out_array np.power(base, exponent, out=result)
print(out_array)

Output

[ 49  64  81 100 144]

Here, after specifying out=result, the result of the power operation is stored in the result array.