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numpy.extract () in Python

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numpy.extract (condition, array): Returns input_array elements if they satisfy some specified condition. 
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. 

# Program Python illustrating
# numpy.compress method

 

import numpy as geek

 

array = geek.arange ( 10 ). reshape ( 5 , 2 )

print ( "Original array:" , array)

 

a = geek.mod (array, 4 )! = 0

# This will show the status of an item that matches the condition

print ( "Array Condition a:" , a)

  
# This will return elements that meet the condition" a " condition

print ( "Elements that satisfy condition a : " , geek.extract (a, array))

  

 

 

b = array - 4 = = 1

# This will show the status of the item that meets the condition

print ( "Array Condition b:" , b)

 
# This will return elements that meet the condition & quot; b & quot;

print ( "Elements that satisfy condition b :" , 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] 

Links:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.extract.html#numpy.extract
Notes:
Also, these codes will not work for online IDs. Please run them on your systems to see how they work. 
This article is courtesy of Mohit Gupta_OMG

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