Course Content

NumPy in a Nutshell

## NumPy in a Nutshell

# Flattening

Do you know what it means to **flatten** an array? Flattening is the process of transforming a multidimensional array into a one-dimensional one.

This transformation can be achieved using two different methods:

- the first one we're already familiar with is the
`.reshape(-1)`

method with an argument of`-1`

; - the other option is to use the
`.flatten()`

method.

Now, let's have a look at both of these methods in practice.

Let's see how to use the `.reshape(-1)`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.reshape(-1) print(new_array)`

Let's see how to use the `.flatten()`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.flatten() print(new_array)`

Let's practice!

Task

Consider the following array:

`[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]]`

You should transform it into the following array:

`[1 2 3 4 5 6 7 8 9 10 11 12]`

.

Thanks for your feedback!

# Flattening

Do you know what it means to **flatten** an array? Flattening is the process of transforming a multidimensional array into a one-dimensional one.

This transformation can be achieved using two different methods:

- the first one we're already familiar with is the
`.reshape(-1)`

method with an argument of`-1`

; - the other option is to use the
`.flatten()`

method.

Now, let's have a look at both of these methods in practice.

Let's see how to use the `.reshape(-1)`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.reshape(-1) print(new_array)`

Let's see how to use the `.flatten()`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.flatten() print(new_array)`

Let's practice!

Task

Consider the following array:

`[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]]`

You should transform it into the following array:

`[1 2 3 4 5 6 7 8 9 10 11 12]`

.

Thanks for your feedback!

# Flattening

Do you know what it means to **flatten** an array? Flattening is the process of transforming a multidimensional array into a one-dimensional one.

This transformation can be achieved using two different methods:

- the first one we're already familiar with is the
`.reshape(-1)`

method with an argument of`-1`

; - the other option is to use the
`.flatten()`

method.

Now, let's have a look at both of these methods in practice.

Let's see how to use the `.reshape(-1)`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.reshape(-1) print(new_array)`

Let's see how to use the `.flatten()`

method:

`import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.flatten() print(new_array)`

Let's practice!

Task

Consider the following array:

`[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]]`

You should transform it into the following array:

`[1 2 3 4 5 6 7 8 9 10 11 12]`

.

Thanks for your feedback!

**flatten** an array? Flattening is the process of transforming a multidimensional array into a one-dimensional one.

This transformation can be achieved using two different methods:

- the first one we're already familiar with is the
`.reshape(-1)`

method with an argument of`-1`

; - the other option is to use the
`.flatten()`

method.

Now, let's have a look at both of these methods in practice.

Let's see how to use the `.reshape(-1)`

method:

Let's see how to use the `.flatten()`

method:

Let's practice!

Task

Consider the following array:

`[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]]`

You should transform it into the following array:

`[1 2 3 4 5 6 7 8 9 10 11 12]`

.