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numpy.logical_and() in Python
  • Last Updated : 29 Nov, 2018

numpy.logical_and(arr1, arr2, out=None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None, ufunc ‘logical_and’) : This is a logical function and it helps user to find out the truth value of arr1 AND arr2 element-wise. Both the arrays must be of same shape.

Parameters :

arr1 : [array_like]Input array.
arr2 : [array_like]Input array.

out : [ndarray, optional]Output array with same dimensions as Input array, placed with result.

**kwargs : allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.



where : [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone.

Return :

An array with Boolean results of arr1 and arr2 element-wise(of the same shape).  

 
Code 1 : Working

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# Python program explaining
# logical_and() function
import numpy as np
  
# input
arr1 = [1, 3, False, 4]
arr2 = [3, 0, True, False]
  
# output
out_arr = np.logical_and(arr1, arr2)
  
print ("Output Array : ", out_arr)

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Output :

Output Array :  [ True False False False]

 
Code 2 : Value Error if input array’s have different shapes

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# Python program explaining
# logical_and() function
import numpy as np
  
# input
arr1 = [8, 2, False, 4]
arr2 = [3, 0, True, False, 8]
  
# output
out_arr = np.logical_and(arr1, arr2)
  
print ("Output Array : ", out_arr)

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Output :

ValueError:operands could not be broadcast together with shapes (4,) (5,) 

References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.logical_and.html#numpy.logical_and
.

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