numpy.logical_or() in Python Last Updated : 29 Nov, 2018 Summarize Suggest changes Share Like Article Like Report numpy.logical_or(arr1, arr2, out=None, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'logical_or') : This is a logical function and it helps user to find out the truth value of arr1 OR 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 OR arr2 element-wise(of the same shape). Code 1 : Working Python # Python program explaining # logical_or() function import numpy as np # input arr1 = [1, 3, False, 4] arr2 = [3, 0, True, False] # output out_arr = np.logical_or(arr1, arr2) print ("Output Array : ", out_arr) Output : Output Array : [ True True True True] Code 2 : Value Error if input array's have different shapes Python # Python program explaining # logical_or() function import numpy as np # input arr1 = [8, 2, False, 4] arr2 = [3, 0, False, False, 8] # output out_arr = np.logical_or(arr1, arr2) print ("Output Array : ", out_arr) 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_or.html#numpy.logical_or . Advertise with us Next Article numpy.logical_not() in Python M mohit gupta_omg :) Follow Similar Reads numpy.logical_and() in Python 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_lik 2 min read numpy.logical_not() in Python numpy.logical_not(arr, out=None, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'logical_not') : This is a logical function that computes the truth value of NOT arr element-wise. Parameters : arr1 : [array_like]Input array. out : [ndarray, optional]Output array with same dimen 2 min read numpy.logical_xor() in Python numpy.logical_xor(arr1, arr2, out=None, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'logical_xor') : This is a logical function and it helps user to find out the truth value of arr1 XOR arr2 element-wise. Both the arrays must be of same shape. Parameters : arr1 : [array_lik 2 min read numpy.isnan() in Python The numpy.isnan() function tests element-wise whether it is NaN or not and returns the result as a boolean array. Syntax :Â numpy.isnan(array [, out]) Parameters :Â array : [array_like]Input array or object whose elements, we need to test for infinity out : [ndarray, optional]Output array placed wit 2 min read Python 3 - Logical Operators Logical Operators are used to perform certain logical operations on values and variables. These are the special reserved keywords that carry out some logical computations. The value the operator operates on is known as Operand. In Python, they are used on conditional statements (either True or False 4 min read numpy.bitwise_or() in Python numpy.bitwise_or()function is used to Compute the bit-wise OR of two array element-wise. This function computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. Syntax : numpy.bitwise_or(arr1, arr2, /, out=None, *, where=True, casting='same_kind', order='K 2 min read Article Tags : Python Python-numpy Python numpy-Logic Functions Practice Tags : python Like