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Impara Flattening | Important Functions
NumPy in a Nutshell
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Contenuti del Corso

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!

Compito

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].

Soluzione

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Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 4. Capitolo 2
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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!

Compito

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].

Soluzione

Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 4. Capitolo 2
Switch to desktopCambia al desktop per esercitarti nel mondo realeContinua da dove ti trovi utilizzando una delle opzioni seguenti
Siamo spiacenti che qualcosa sia andato storto. Cosa è successo?
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