Conteúdo do Curso

NumPy in a Nutshell

1. Getting Started with NumPy

What is NumPy?Function array()Basic Array Creation Quiz

2. Dimensions in Arrays

1-D Arrays Mathematical Operations with 1-D Arrays 2-D Arrays 3-D Arrays Multidimensional Arrays Quiz

3. Indexing and Slicing

Access Array Elements Match Math Operations Access 2-D and 3-D Arrays Match the Slicing Negative Indexing Match the Indices Get One Dimensional Array Using Slice and Only Positive Indexes Get One Dimensional Array Using Only Negative Indexes

4. Important Functions

Reshaping Flattening Joining Sorting Arrays Copying Arrays

Access Array Elements

In both lists and arrays, elements are accessed using square brackets. Let's review the distinction between indexing and slicing:

To retrieve a single element, you simply need to specify the index of that element in square brackets (start counting from 0);
If you want to obtain a sequence from the original array, you should use slices.

We'll start with simple indexing. Let's have a look at the following image:

Let's see how it works with examples.

Get the first element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the first element
print(arr[0])

Retrieve the second element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the second element
print(arr[1])

Retrieve the third and fourth elements from the following array and then add them together:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Adding the third and the fourth elements
print(arr[2] + arr[3])

Now, it's time to explore slicing. First, let's examine the syntax of slicing: array[start:end:step], where:

start is the index from which slicing begins;
end is the index where slicing stops (note that this index is not included);
step is the parameter that specifies the intervals between the indices.

Let's have a look at the following image:

Omitting start, end and step

As you can see, we can often omit the start, end, step or even all of them at the same time. step, for example, can be omitted when we want it to be equal to 1. start and end can be omitted in the following scenarios:

Omitting start:
- slicing from the first element (step is positive);
- slicing from the last element (step is negative).
Omitting end:
- slicing to the last element inclusive (step is positive);
- slicing to the first element inclusive (step is negative).

In the example above, a[2:4] has the step equal to 1. a[-2:] goes from the second to last element to the end of the array with step equal to 1. a[::2] goes from the first element to the end of the array with step equal to 2.

It's time to practice.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 1

Access Array Elements

In both lists and arrays, elements are accessed using square brackets. Let's review the distinction between indexing and slicing:

To retrieve a single element, you simply need to specify the index of that element in square brackets (start counting from 0);
If you want to obtain a sequence from the original array, you should use slices.

We'll start with simple indexing. Let's have a look at the following image:

Let's see how it works with examples.

Get the first element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the first element
print(arr[0])

Retrieve the second element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the second element
print(arr[1])

Retrieve the third and fourth elements from the following array and then add them together:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Adding the third and the fourth elements
print(arr[2] + arr[3])

Now, it's time to explore slicing. First, let's examine the syntax of slicing: array[start:end:step], where:

start is the index from which slicing begins;
end is the index where slicing stops (note that this index is not included);
step is the parameter that specifies the intervals between the indices.

Let's have a look at the following image:

Omitting start, end and step

Omitting start:
- slicing from the first element (step is positive);
- slicing from the last element (step is negative).
Omitting end:
- slicing to the last element inclusive (step is positive);
- slicing to the first element inclusive (step is negative).

It's time to practice.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 3. Capítulo 1

Access Array Elements

In both lists and arrays, elements are accessed using square brackets. Let's review the distinction between indexing and slicing:

To retrieve a single element, you simply need to specify the index of that element in square brackets (start counting from 0);
If you want to obtain a sequence from the original array, you should use slices.

We'll start with simple indexing. Let's have a look at the following image:

Let's see how it works with examples.

Get the first element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the first element
print(arr[0])

Retrieve the second element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the second element
print(arr[1])

Retrieve the third and fourth elements from the following array and then add them together:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Adding the third and the fourth elements
print(arr[2] + arr[3])

Now, it's time to explore slicing. First, let's examine the syntax of slicing: array[start:end:step], where:

start is the index from which slicing begins;
end is the index where slicing stops (note that this index is not included);
step is the parameter that specifies the intervals between the indices.

Let's have a look at the following image:

Omitting start, end and step

Omitting start:
- slicing from the first element (step is positive);
- slicing from the last element (step is negative).
Omitting end:
- slicing to the last element inclusive (step is positive);
- slicing to the first element inclusive (step is negative).

It's time to practice.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

In both lists and arrays, elements are accessed using square brackets. Let's review the distinction between indexing and slicing:

To retrieve a single element, you simply need to specify the index of that element in square brackets (start counting from 0);
If you want to obtain a sequence from the original array, you should use slices.

We'll start with simple indexing. Let's have a look at the following image:

Let's see how it works with examples.

Get the first element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the first element
print(arr[0])

Retrieve the second element from the following array:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Get the second element
print(arr[1])

Retrieve the third and fourth elements from the following array and then add them together:


              1234567
            
import numpy as np

# Creating array
arr = np.array([1, 2, 3, 4, 5])

# Adding the third and the fourth elements
print(arr[2] + arr[3])

Now, it's time to explore slicing. First, let's examine the syntax of slicing: array[start:end:step], where:

start is the index from which slicing begins;
end is the index where slicing stops (note that this index is not included);
step is the parameter that specifies the intervals between the indices.

Let's have a look at the following image:

Omitting start, end and step

Omitting start:
- slicing from the first element (step is positive);
- slicing from the last element (step is negative).
Omitting end:
- slicing to the last element inclusive (step is positive);
- slicing to the first element inclusive (step is negative).

It's time to practice.

Tarefa

Retrieve the first and last elements from the following array [13, 99, 11, 23, 5, 41] and then multiply them. Please use positive indexing.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Seção 3. Capítulo 1

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo