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You can use one of the following two methods to create an array of arrays in Python using the NumPy package:

**Method 1: Combine Individual Arrays**

import numpy as np array1 = np.array([1, 2, 3]) array2 = np.array([4, 5, 6]) array3 = np.array([7, 8, 9]) all_arrays = np.array([array1, array2, array3])

**Method 2: Create Array of Arrays Directly**

import numpy as np all_arrays = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

The following examples show how to use each method in practice.

**Method 1: Combine Individual Arrays**

The following code shows how to create an array of arrays by simply combining individual arrays:

import numpy as np #define individual arrays array1 = np.array([10, 20, 30, 40, 50]) array2 = np.array([60, 70, 80, 90, 100]) array3 = np.array([110, 120, 130, 140, 150]) #combine individual arrays into one array of arrays all_arrays = np.array([array1, array2, array3]) #view array of arrays print(all_arrays) [[ 10 20 30 40 50] [ 60 70 80 90 100] [110 120 130 140 150]]

**Method 2: Create Array of Arrays Directly**

The following code shows how to create an array of arrays directly:

import numpy as np #create array of arrays all_arrays = np.array([[10, 20, 30, 40, 50], [60, 70, 80, 90, 100], [110, 120, 130, 140, 150]]) #view array of arrays print(all_arrays) [[ 10 20 30 40 50] [ 60 70 80 90 100] [110 120 130 140 150]]

Notice that this array of arrays matches the one created using the previous method.

**How to Access Elements in an Array of Arrays**

You can use the **shape** function to retrieve the dimensions of an array of arrays:

print(all_arrays.shape) (3, 5)

This tells us that there are three rows and five columns in the array of arrays.

You can use the **size** function to see how many total values are in the array of arrays:

print(all_arrays.size) 15

This tells us that there are 15 total values in the array of arrays.

You can use **brackets** to access elements in certain positions of the array of arrays.

For example, you can use the following syntax to retrieve the value in the first array located in index position 3:

print(all_arrays[0, 3]) 40

We can use this syntax to access any value weâ€™d like in the array of arrays.

**Additional Resources**

The following tutorials explain how to perform other common operations with arrays in Python:

How to Concatenate Arrays in Python

How to Create Pandas DataFrame from NumPy Array

How to Convert Pandas DataFrame to NumPy Array