Conteúdo do Curso

Ultimate NumPy

More about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

> (greater than);
< (less than);
>= (greater than or equal to);
<= (less than or equal to);
== (equal to);
!= (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

& (logical and);
| (logical or).

If at least one of the conditions is True, then | returns True; otherwise, it returns False. If at least one of the conditions is False, then & returns False; otherwise, it returns True.

Note
Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


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import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Tarefa

You are analyzing the ratings of various products collected from customer feedback. The ratings are stored in a 1D NumPy array where each element represents the rating of a product. Your task is to filter out the ratings that are greater than or equal to 3 AND not equal to 5 using boolean indexing.

Tarefa

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

Tudo estava claro?

Seção 2. Capítulo 8

More about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

> (greater than);
< (less than);
>= (greater than or equal to);
<= (less than or equal to);
== (equal to);
!= (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

& (logical and);
| (logical or).

Note
Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              1234567891011121314
            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Tarefa

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

Tudo estava claro?

Seção 2. Capítulo 8

More about Comparisons

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

> (greater than);
< (less than);
>= (greater than or equal to);
<= (less than or equal to);
== (equal to);
!= (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

& (logical and);
| (logical or).

Note
Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              1234567891011121314
            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Tarefa

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

Tudo estava claro?

Most conditions you will use are comparisons, so it's important to discuss them in more detail. Comparisons are based on the following comparison operators:

> (greater than);
< (less than);
>= (greater than or equal to);
<= (less than or equal to);
== (equal to);
!= (not equal to).

Moreover, you can combine multiple conditions and comparisons using the following logical operators:

& (logical and);
| (logical or).

Note
Each condition should be put in parentheses () when combining them.

Don’t worry, here is an example to make everything clear:


              1234567891011121314
            
import numpy as np
# Creating an array of integers from 1 to 10 inclusive
array = np.arange(1, 11)
# Retrieving elements greater than or equal to 5 AND less than 9
print(array[(array >= 5) & (array < 9)])
print('-' * 12)
# Retrieving elements less than or equal to 4 AND not equal to 2
print(array[(array != 2) & (array <= 4)])
print('-' * 12)
# Retrieving elements less than 3 OR equal to 8
print(array[(array < 3) | (array == 8)])
print('-' * 12)
# Retrieving elements between 2 inclusive AND 5 inclusive OR equal to 9
print(array[(array >= 2) & (array <= 5) | (array == 9)])

Let's now take a look at the following visualization to understand the code better (purple squares represent the actual retrieved elements):

Tarefa

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

Seção 2. Capítulo 8

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