# Set the first array elements raised to powers from second array element-wise in Numpy

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To set the first array elements raised to powers from second array, element-wise, use the numpy.power() method in Python. Here, the 1st parameter is the base and the 2nd exponents.

Raise each base in x1 to the positionally-corresponding power in x2. x1 and x2 must be broadcastable to the same shape. An integer type raised to a negative integer power will raise a ValueError. Negative values raised to a non-integral value will return nan. To get complex results, cast the input to complex, or specify the dtype to be complex.

The out is a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

## Steps

At first, import the required library −

import numpy as np

Create an array −

arr = np.array([5, 10, 25, 30, 40, 50])


Display the array −

print("Array...\n", arr)

Get the type of the array −

print("\nOur Array type...\n", arr.dtype)


Get the dimensions of the Array −

print("\nOur Array Dimension...\n",arr.ndim)

Get the shape of the Array −

print("\nOur Array Shape...\n",arr.shape)


Set the exponent −

p = [2, 3, 2, 3, 2, 3]

To set the first array elements raised to powers from second array, element-wise, use the numpy.power() method. Here, the 1st parameter is the base and the 2nd exponents −

print("\nResult...\n",np.power(arr, p))


## Example

import numpy as np

# Create an array
arr = np.array([5, 10, 25, 30, 40, 50])

# Display the array
print("Array...\n", arr)

# Get the type of the array
print("\nOur Array type...\n", arr.dtype)

# Get the dimensions of the Array
print("\nOur Array Dimension...\n",arr.ndim)

# Get the shape of the Array
print("\nOur Array Shape...\n",arr.shape)

# Set the exponent
p = [2, 3, 2, 3, 2, 3]

# To set the first array elements raised to powers from second array, element-wise, use the numpy.power() method in Python
# Here, the 1st parameter is the base and the 2nd exponents
print("\nResult...\n",np.power(arr, p))

## Output

Array...
[ 5 10 25 30 40 50]

Our Array type...
int64

Our Array Dimension...
1

Our Array Shape...
(6,)

Result...
[ 25 1000 625 27000 1600 125000]