Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Apprendre Flattening | Important Functions
NumPy in a Nutshell
course content

Contenu du cours

NumPy in a Nutshell

NumPy in a Nutshell

1. Getting Started with NumPy
2. Dimensions in Arrays
3. Indexing and Slicing
4. Important Functions

book
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:

123456
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)
copy

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

123456
import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.flatten() print(new_array)
copy

Let's practice!

Tâche

Swipe to start coding

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].

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 2
toggle bottom row

book
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:

123456
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)
copy

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

123456
import numpy as np array = np.array([[12, 45, 78, 34, 0], [13, 5, 78, 3, 1]]) new_array = array.flatten() print(new_array)
copy

Let's practice!

Tâche

Swipe to start coding

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].

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 2
Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
We're sorry to hear that something went wrong. What happened?
some-alt