Course Content

NumPy in a Nutshell

## NumPy in a Nutshell

# 3-D Arrays

With **three-dimensional arrays**, everything is quite clear and logical. These arrays consist of elements that are **two-dimensional arrays**.

Let's practice to make it easier to understand.

Here's an example of how we can create a **3-D array** with **four 2-D arrays**, each containing **three 1D arrays** with 2 elements:

`import numpy as np # Creating array arr = np.array([ [ [1, 2], [4, 3], [7, 4] ], [ [2, 10], [9, 15], [7, 5] ], [ [1, 11], [3, 20], [0, 2] ], [ [9, 25], [6, 13], [9, 8] ] ]) # Displaying array print(arr)`

Let's now take a look at the visualization of this array:

Our 3D array is `4x3x2`

, hence why we have a **rectangular parallelepiped** with sides equal to 4, 3 and 2, respectively. The innermost 1D arrays lie along the **axis 2** (e.g., `[1, 2]`

or `[4, 3]`

) where each small cube with side equal to 1 is a particular element (number).

Basically, all the elements of a 3D array are stored inside these innermost 1D arrays. The **rectangular parallelepiped** is just a visual representation for us to make things clear. The total number of elements (small cubes) is equal to **24** (the volume of the rectangular parallelepiped), which `4 * 3 * 2`

.

Note

Since its a 2D visualization of a 3D object, we cannot display and see here all the elements.

Time to test your strength!

Task

- You need to create two arrays:
- the first one is a 2-D array containing two arrays with the values:
`1, 5, 2`

and`34, 2, 7`

; - the second one is a 3-D array (use only a
**single line**to create this array) containing two 2-D arrays, both of which include two arrays with the values`5, 3, 8`

and`6, 1, 9`

.

- the first one is a 2-D array containing two arrays with the values:
- Display these arrays on the screen: first
`arr_1`

, then`arr_2`

.

Thanks for your feedback!

# 3-D Arrays

With **three-dimensional arrays**, everything is quite clear and logical. These arrays consist of elements that are **two-dimensional arrays**.

Let's practice to make it easier to understand.

Here's an example of how we can create a **3-D array** with **four 2-D arrays**, each containing **three 1D arrays** with 2 elements:

`import numpy as np # Creating array arr = np.array([ [ [1, 2], [4, 3], [7, 4] ], [ [2, 10], [9, 15], [7, 5] ], [ [1, 11], [3, 20], [0, 2] ], [ [9, 25], [6, 13], [9, 8] ] ]) # Displaying array print(arr)`

Let's now take a look at the visualization of this array:

Our 3D array is `4x3x2`

, hence why we have a **rectangular parallelepiped** with sides equal to 4, 3 and 2, respectively. The innermost 1D arrays lie along the **axis 2** (e.g., `[1, 2]`

or `[4, 3]`

) where each small cube with side equal to 1 is a particular element (number).

Basically, all the elements of a 3D array are stored inside these innermost 1D arrays. The **rectangular parallelepiped** is just a visual representation for us to make things clear. The total number of elements (small cubes) is equal to **24** (the volume of the rectangular parallelepiped), which `4 * 3 * 2`

.

Note

Since its a 2D visualization of a 3D object, we cannot display and see here all the elements.

Time to test your strength!

Task

- You need to create two arrays:
- the first one is a 2-D array containing two arrays with the values:
`1, 5, 2`

and`34, 2, 7`

; - the second one is a 3-D array (use only a
**single line**to create this array) containing two 2-D arrays, both of which include two arrays with the values`5, 3, 8`

and`6, 1, 9`

.

- the first one is a 2-D array containing two arrays with the values:
- Display these arrays on the screen: first
`arr_1`

, then`arr_2`

.

Thanks for your feedback!

# 3-D Arrays

With **three-dimensional arrays**, everything is quite clear and logical. These arrays consist of elements that are **two-dimensional arrays**.

Let's practice to make it easier to understand.

Here's an example of how we can create a **3-D array** with **four 2-D arrays**, each containing **three 1D arrays** with 2 elements:

`import numpy as np # Creating array arr = np.array([ [ [1, 2], [4, 3], [7, 4] ], [ [2, 10], [9, 15], [7, 5] ], [ [1, 11], [3, 20], [0, 2] ], [ [9, 25], [6, 13], [9, 8] ] ]) # Displaying array print(arr)`

Let's now take a look at the visualization of this array:

Our 3D array is `4x3x2`

, hence why we have a **rectangular parallelepiped** with sides equal to 4, 3 and 2, respectively. The innermost 1D arrays lie along the **axis 2** (e.g., `[1, 2]`

or `[4, 3]`

) where each small cube with side equal to 1 is a particular element (number).

Basically, all the elements of a 3D array are stored inside these innermost 1D arrays. The **rectangular parallelepiped** is just a visual representation for us to make things clear. The total number of elements (small cubes) is equal to **24** (the volume of the rectangular parallelepiped), which `4 * 3 * 2`

.

Note

Since its a 2D visualization of a 3D object, we cannot display and see here all the elements.

Time to test your strength!

Task

- You need to create two arrays:
- the first one is a 2-D array containing two arrays with the values:
`1, 5, 2`

and`34, 2, 7`

; - the second one is a 3-D array (use only a
**single line**to create this array) containing two 2-D arrays, both of which include two arrays with the values`5, 3, 8`

and`6, 1, 9`

.

- the first one is a 2-D array containing two arrays with the values:
- Display these arrays on the screen: first
`arr_1`

, then`arr_2`

.

Thanks for your feedback!

**three-dimensional arrays**, everything is quite clear and logical. These arrays consist of elements that are **two-dimensional arrays**.

Let's practice to make it easier to understand.

**3-D array** with **four 2-D arrays**, each containing **three 1D arrays** with 2 elements:

Let's now take a look at the visualization of this array:

`4x3x2`

, hence why we have a **rectangular parallelepiped** with sides equal to 4, 3 and 2, respectively. The innermost 1D arrays lie along the **axis 2** (e.g., `[1, 2]`

or `[4, 3]`

) where each small cube with side equal to 1 is a particular element (number).

**rectangular parallelepiped** is just a visual representation for us to make things clear. The total number of elements (small cubes) is equal to **24** (the volume of the rectangular parallelepiped), which `4 * 3 * 2`

.

Note

Since its a 2D visualization of a 3D object, we cannot display and see here all the elements.

Time to test your strength!

Task

- You need to create two arrays:
- the first one is a 2-D array containing two arrays with the values:
`1, 5, 2`

and`34, 2, 7`

; - the second one is a 3-D array (use only a
**single line**to create this array) containing two 2-D arrays, both of which include two arrays with the values`5, 3, 8`

and`6, 1, 9`

.

- the first one is a 2-D array containing two arrays with the values:
- Display these arrays on the screen: first
`arr_1`

, then`arr_2`

.