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NumPy in a Nutshell
course content

Course Content

NumPy in a Nutshell

NumPy in a Nutshell

1. Getting Started with NumPy
What is NumPy?Function array()Basic Array Creation Quiz
2. Dimensions in Arrays
1-D ArraysMathematical Operations with 1-D Arrays2-D Arrays3-D ArraysMultidimensional Arrays Quiz
3. Indexing and Slicing
Access Array ElementsMatch Math Operations Access 2-D and 3-D ArraysMatch the Slicing Negative IndexingMatch the IndicesGet One Dimensional Array Using Slice and Only Positive Indexes Get One Dimensional Array Using Only Negative Indexes
4. Important Functions
ReshapingFlatteningJoining Sorting ArraysCopying Arrays

bookFlattening

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!

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].

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 4. Chapter 2
toggle bottom row

bookFlattening

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!

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].

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 4. Chapter 2
toggle bottom row

bookFlattening

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!

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].

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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!

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].

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 4. Chapter 2
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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