The numpy.bitwise_and () function is used to calculate the bitwise AND of two array elements element by element. This function calculates the bitwise AND base binary representation of integers in the input arrays.
Syntax: numpy.bitwise_and (arr1, arr2, /, out = None, *, where = True, casting = `same_kind`, order = `K`, dtype = None, ufunc `bitwise_and`)
arr1: strong> [array_like] Input array.
arr2: [array_like] Input array.
out: [ndarray, optional] A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
** 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: [ndarray or scalar] Result. This is a scalar if both x1 and x2 are scalars.
Code # 1: Work
Input number1: 10 Input number2: 11 bitwise_and of 10 and 11:10
Code # 2:
Input array1: [2, 8, 125] Input array2: [3 , 3, 115] Output array after bitwise_and: [2 0 113]
Code # 3:
Input array1: [True , False, True, False] Input array2: [False, False, True, True] Output array after bitwise_and: [False False True False]
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