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:
123456import 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:
123456import 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!
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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].
Lösung
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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:
123456import 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:
123456import 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!
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].
Lösung
Wechseln Sie zum Desktop, um in der realen Welt zu übenFahren Sie dort fort, wo Sie sind, indem Sie eine der folgenden Optionen verwendenDanke für Ihr Feedback!
Awesome!
Completion rate improved to 4.76single
