# How to build an array of all combinations of two NumPy arrays?

• Difficulty Level : Basic
• Last Updated : 05 Sep, 2020

Sometimes we need to find the combination of elements of two or more arrays. Numpy has a function to compute the combination of 2 or more Numpy arrays named as “numpy.meshgrid()“. This function is used to create a rectangular grid out of two given one-dimensional arrays representing the Cartesian indexing or Matrix indexing.

Syntax:

```numpy.meshgrid(*xi, copy=True, sparse=False, indexing='xy')
```

Example 1: Computing combinations of elements of Two NumPy arrays

## Python3

 `# importing Numpy package ` `import` `numpy as np ` ` `  `# creating 2 numpy arrays ` `array_1 ``=` `np.array([``1``, ``2``]) ` `array_2 ``=` `np.array([``4``, ``6``]) ` ` `  `print``(``"Array-1"``) ` `print``(array_1) ` ` `  `print``(``"\nArray-2"``) ` `print``(array_2) ` ` `  `# combination of elements of array_1 and array_2 ` `# using numpy.meshgrid().T.reshape() ` `comb_array ``=` `np.array(np.meshgrid(array_1, array_2)).T.reshape(``-``1``, ``2``) ` ` `  `print``(``"\nCombine array:"``) ` `print``(comb_array) `

Output:

In the above example, we combine elements of ‘array_1‘ and ‘array_2‘ using numpy.meshgrid().T.reshape()

Example 2: Computing combinations of elements of Three NumPy arrays

## Python3

 `# importing Numpy package ` `import` `numpy as np ` ` `  `# creating 3 numpy arrays ` `array_1 ``=` `np.array([``1``, ``2``, ``3``]) ` `array_2 ``=` `np.array([``4``, ``6``, ``4``]) ` `array_3 ``=` `np.array([``3``, ``6``]) ` ` `  `print``(``"Array-1"``) ` `print``(array_1) ` ` `  `print``(``"Array-2"``) ` `print``(array_2) ` ` `  `print``(``"Array-3"``) ` `print``(array_3) ` ` `  ` `  `# combination of elements of array_1, ` `# array_2 and array_3 using  ` `# numpy.meshgrid().T.reshape() ` `comb_array ``=` `np.array( ` `  ``np.meshgrid(array_1, array_2, array_3)).T.reshape(``-``1``, ``3``) ` ` `  `print``(``"\nCombine array:"``) ` `print``(comb_array) `

Output:

In the above example, we combine elements of ‘array_1‘, ‘array_2‘ and ‘array_3‘ using numpy.meshgrid().T.reshape()

Example 3: Computing combinations of elements of Four NumPy arrays

## Python3

 `# importing Numpy package ` `import` `numpy as np ` ` `  `# creating 4 numpy arrays ` `array_1 ``=` `np.array([``50``, ``21``]) ` `array_2 ``=` `np.array([``4``, ``4``]) ` `array_3 ``=` `np.array([``1``, ``10``]) ` `array_4 ``=` `np.array([``7``, ``14``]) ` ` `  ` `  `print``(``"Array-1"``) ` `print``(array_1) ` ` `  `print``(``"Array-2"``) ` `print``(array_2) ` ` `  `print``(``"Array-3"``) ` `print``(array_3) ` ` `  `print``(``"Array-4"``) ` `print``(array_4) ` ` `  ` `  `# combination of elements of array_1,  ` `# array_2, array_3 and array_4 ` `# using numpy.meshgrid().T.reshape() ` `comb_array ``=` `np.array(np.meshgrid( ` `    ``array_1, array_2, array_3, array_4)).T.reshape(``-``1``, ``4``) ` ` `  `print``(``"\nCombine array:"``) ` `print``(comb_array) `

Output:

In the above example, we combine elements of ‘array_1‘, ‘array_2‘, ‘array_3‘ and ‘array_4‘ using numpy.meshgrid().T.reshape()

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