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# Get the Outer product of two arrays in Python

To get the Outer product of two arrays, use the numpy.outer() method in Python. The 1st parameter a is the first input vector. Input is flattened if not already 1-dimensional. The 2nd parameter b is the second input vector. Input is flattened if not already 1-dimensional. The 3rd parameter out is a location where the result is stored.

Given two vectors, a = [a0, a1, ..., aM] and b = [b0, b1, ..., bN], the outer product [1] is −

[[a0*b0 a0*b1 ... a0*bN ] [a1*b0 . [ ... . [aM*b0 aM*bN ]]

## Steps

At first, import the required libraries-

import numpy as np

Creating two numpy One-Dimensional array using the array() method −

arr1 = np.array([5, 10, 15]) arr2 = np.array([20, 25, 30])

Display the arrays −

print("Array1...\n",arr1) print("\nArray2...\n",arr2)

Check the Dimensions of both the arrays −

print("\nDimensions of Array1...\n",arr1.ndim) print("\nDimensions of Array2...\n",arr2.ndim)

Check the Shape of both the arrays −

print("\nShape of Array1...\n",arr1.shape) print("\nShape of Array2...\n",arr2.shape)

To get the Outer product of two arrays, use the numpy.outer() method in Python −

print("\nResult (Outer Product)...\n",np.outer(arr1, arr2))

## Example

import numpy as np # Creating two numpy One-Dimensional array using the array() method arr1 = np.array([5, 10, 15]) arr2 = np.array([20, 25, 30]) # Display the arrays print("Array1...\n",arr1) print("\nArray2...\n",arr2) # Check the Dimensions of both the arrays print("\nDimensions of Array1...\n",arr1.ndim) print("\nDimensions of Array2...\n",arr2.ndim) # Check the Shape of both the arrays print("\nShape of Array1...\n",arr1.shape) print("\nShape of Array2...\n",arr2.shape) # To get the Outer product of two arrays, use the numpy.outer() method in Python print("\nResult (Outer Product)...\n",np.outer(arr1, arr2))

## Output

Array1... [ 5 10 15] Array2... [20 25 30] Dimensions of Array1... 1 Dimensions of Array2... 1 Shape of Array1... (3,) Shape of Array2... (3,) Result (Outer Product)... [[100 125 150] [200 250 300] [300 375 450]]

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