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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:


              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):

Завдання

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.

Завдання

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Секція 2. Розділ 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):

Завдання

Все було зрозуміло?

Секція 2. Розділ 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):

Завдання

Все було зрозуміло?

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):

Завдання

Секція 2. Розділ 8