Conteúdo do Curso

Ultimate NumPy

Slicing

Slicing in Python refers to retrieving elements from one index to another within a sequence. In this chapter, however, we will focus on slicing in NumPy arrays.

Slicing in 1D Arrays

The general syntax for slicing in 1D arrays is as follows: array[start:end:step]. Let’s take a more detailed look at it:

start is the index at which to start slicing;
end is the index at which slicing ends (the index itself is not included);
step specifies the increments between the indices (default is 1).

Here is an example to clarify everything (purple squares represent the elements retrieved from slicing):

Note
Since we did not explicitly specify step, it defaults to a value of 1.

Here is the code for this example:


              123456789101112
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the element at index 2 to the element at index 4 exclusive
print(array[2:4])
print('-' * 47)
# Slicing from the first element to the element at index 5 exclusive
print(array[:5])
print('-' * 47)
# Slicing from the element at index 5 to the last element inclusive
print(array[5:])

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. For example, step 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).

Let's take a look at a few more examples (the black arrow indicates that the elements are taken in reverse order):

Here is the corresponding code:


              123456789101112131415
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the first element to the last element inclusive with step=2
print(array[::2])
print('-' * 47)
# Slicing from the element at index 4 to the element at index 2 exclusive (step=-1)
print(array[4:2:-1])
print('-' * 47)
# Slicing from the last element to the first element inclusive (reversed array)
print(array[::-1])
print('-' * 47)
# Slicing from the first element to the last inclusive (the same as our array)
print(array[:])

Tarefa

You are analyzing the daily sales data of a small retail store. The sales for the past week are stored in a NumPy array, with each element representing the sales for a specific day. Create a slice of weekly_sales containing the sales data for every second day, starting from the second day (Tuesday), and store it in alternate_day_sales (use a positive index for start and do not specify end).

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Seção 2. Capítulo 3

Slicing

Slicing in Python refers to retrieving elements from one index to another within a sequence. In this chapter, however, we will focus on slicing in NumPy arrays.

Slicing in 1D Arrays

The general syntax for slicing in 1D arrays is as follows: array[start:end:step]. Let’s take a more detailed look at it:

start is the index at which to start slicing;
end is the index at which slicing ends (the index itself is not included);
step specifies the increments between the indices (default is 1).

Here is an example to clarify everything (purple squares represent the elements retrieved from slicing):

Note
Since we did not explicitly specify step, it defaults to a value of 1.

Here is the code for this example:


              123456789101112
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the element at index 2 to the element at index 4 exclusive
print(array[2:4])
print('-' * 47)
# Slicing from the first element to the element at index 5 exclusive
print(array[:5])
print('-' * 47)
# Slicing from the element at index 5 to the last element inclusive
print(array[5:])

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).

Let's take a look at a few more examples (the black arrow indicates that the elements are taken in reverse order):

Here is the corresponding code:


              123456789101112131415
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the first element to the last element inclusive with step=2
print(array[::2])
print('-' * 47)
# Slicing from the element at index 4 to the element at index 2 exclusive (step=-1)
print(array[4:2:-1])
print('-' * 47)
# Slicing from the last element to the first element inclusive (reversed array)
print(array[::-1])
print('-' * 47)
# Slicing from the first element to the last inclusive (the same as our array)
print(array[:])

Tarefa

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Seção 2. Capítulo 3

Slicing

Slicing in Python refers to retrieving elements from one index to another within a sequence. In this chapter, however, we will focus on slicing in NumPy arrays.

Slicing in 1D Arrays

The general syntax for slicing in 1D arrays is as follows: array[start:end:step]. Let’s take a more detailed look at it:

start is the index at which to start slicing;
end is the index at which slicing ends (the index itself is not included);
step specifies the increments between the indices (default is 1).

Here is an example to clarify everything (purple squares represent the elements retrieved from slicing):

Note
Since we did not explicitly specify step, it defaults to a value of 1.

Here is the code for this example:


              123456789101112
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the element at index 2 to the element at index 4 exclusive
print(array[2:4])
print('-' * 47)
# Slicing from the first element to the element at index 5 exclusive
print(array[:5])
print('-' * 47)
# Slicing from the element at index 5 to the last element inclusive
print(array[5:])

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).

Let's take a look at a few more examples (the black arrow indicates that the elements are taken in reverse order):

Here is the corresponding code:


              123456789101112131415
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the first element to the last element inclusive with step=2
print(array[::2])
print('-' * 47)
# Slicing from the element at index 4 to the element at index 2 exclusive (step=-1)
print(array[4:2:-1])
print('-' * 47)
# Slicing from the last element to the first element inclusive (reversed array)
print(array[::-1])
print('-' * 47)
# Slicing from the first element to the last inclusive (the same as our array)
print(array[:])

Tarefa

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Slicing in Python refers to retrieving elements from one index to another within a sequence. In this chapter, however, we will focus on slicing in NumPy arrays.

Slicing in 1D Arrays

The general syntax for slicing in 1D arrays is as follows: array[start:end:step]. Let’s take a more detailed look at it:

start is the index at which to start slicing;
end is the index at which slicing ends (the index itself is not included);
step specifies the increments between the indices (default is 1).

Here is an example to clarify everything (purple squares represent the elements retrieved from slicing):

Note
Since we did not explicitly specify step, it defaults to a value of 1.

Here is the code for this example:


              123456789101112
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the element at index 2 to the element at index 4 exclusive
print(array[2:4])
print('-' * 47)
# Slicing from the first element to the element at index 5 exclusive
print(array[:5])
print('-' * 47)
# Slicing from the element at index 5 to the last element inclusive
print(array[5:])

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).

Let's take a look at a few more examples (the black arrow indicates that the elements are taken in reverse order):

Here is the corresponding code:


              123456789101112131415
            
import numpy as np
array = np.array([5, 10, 2, 8, 9, 1, 0, 4])
print(f'Initial array: {array}')
print('-' * 47)
# Slicing from the first element to the last element inclusive with step=2
print(array[::2])
print('-' * 47)
# Slicing from the element at index 4 to the element at index 2 exclusive (step=-1)
print(array[4:2:-1])
print('-' * 47)
# Slicing from the last element to the first element inclusive (reversed array)
print(array[::-1])
print('-' * 47)
# Slicing from the first element to the last inclusive (the same as our array)
print(array[:])

Tarefa

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Seção 2. Capítulo 3

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