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Ultimate NumPy
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:
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
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:
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
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:
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
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:
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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo