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numpy.extract() in Python

Last Updated : 08 Mar, 2024
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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.


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