Open In App

numpy.extract() in Python

Last Updated : 08 Mar, 2024
Suggest changes
Share
Like Article
Like
Report

The numpy.extract() function returns elements of input_array if they satisfy some specified condition.
 

Syntax: numpy.extract(condition, array)


Parameters :  

array : Input array. User apply conditions on input_array elements condition : [array_like]Condition on the basis of which user extract elements. Applying condition on input_array, if we print condition, it will return an array filled with either True or False. Array elements are extracted from the Indices having True value.


Returns : 

Array elements that satisfy the condition.
Python
# Python Program illustrating # numpy.compress method import numpy as geek array = geek.arange(10).reshape(5, 2) print("Original array : \n", array) a = geek.mod(array, 4) !=0 # This will show element status of satisfying condition print("\nArray Condition a : \n", a) # This will return elements that satisfy condition "a" condition print("\nElements that satisfy condition a : \n", geek.extract(a, array)) b = array - 4 == 1 # This will show element status of satisfying condition print("\nArray Condition b : \n", b) # This will return elements that satisfy condition "b" condition print("\nElements that satisfy condition b : \n", geek.extract(b, array)) 

Output : 

Original array : [[0 1] [2 3] [4 5] [6 7] [8 9]] Array Condition a : [[False True] [ True True] [False True] [ True True] [False True]] Elements that satisfy condition a : [1 2 3 5 6 7 9] Array Condition b : [[False False] [False False] [False True] [False False] [False False]] Elements that satisfy condition b : [5]

Note : 
Also, these codes won't run on online IDE's. So please, run them on your systems to explore the working.


Explore