Bits are shifted left by adding arr2 0s (zeros) to the right of arr1. Since numbers are internally represented in binary, this operation is equivalent to multiplying arr1 by 2 ** arr2. For example, if the number is 5 and we want to shift left by 2 bits, then after shifting 2 bits to the left, the result will be 5 * (2 ^ 2) = 20
Syntax: strong> numpy.left_shift (arr1, arr2, /, out = None, *, where = True, casting = `same_kind`, order = `K`, dtype = None, ufunc `left_shift`)
arr1: array_like of integer type
arr2: array_like of integer type
Number of zeros to append to arr1.The value of arr2 should be positive integer.
out: [ndarray, optional] A location into which the result is stored.
- & gt ; If provided, it must have a shape that the inputs broadcast to.
- & gt; 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: array of integer type.
Return arr1 with bits shifted arr2 times to the left. This is a scalar if both arr1 and arr2 are scalars.
Code # 1: Work
Output: p >
Input number: 5 Number of bit shift: 2 After left shifting 2 bit: 20
Code # 2:
Input array: [2, 8, 15] Number of bit shift: [3, 4, 5] Output array after left shifting: [16 128 480]
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