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# Numpy bitwise_and() function

In this tutorial, we will cover the `bitwise_and` binary operation in the Numpy library.

In Numpy, the `bitwise_and()` function is mainly used to perform the `bitwise_and` operation.

• This function will calculate the bit-wise AND of two arrays, element-wise.

• The `bitwise_and()` function calculates the bit-wise AND of the underlying binary representation of the integers in the input array.

Let us take a look at the truth table of AND operation:

If and only if both the bits are 1 only then the output of the AND result of the two bits is 1 otherwise it will be 0. ### Syntax of `bitwise_and()`:

The syntax required to use this function is as follows:

``numpy.bitwise_and(x1, x2, /, out, *, where=True, casting='same_kind', order='K', dtype,subok=True[, signature, extobj]) = <ufunc 'bitwise_and'>``

Parameters:

Let us now take a look at the parameters of this function:

• x1, x2
These two are input arrays and with this function only integer and boolean types are handled. If `x1.shape != x2.shape`, then they must be broadcastable to a common shape (and this shape will become the shape of the output).

• out
This parameter mainly indicates a location in which the result is stored. If this parameter is provided, it must have a shape that the inputs broadcast to. If this parameter is either not provided or it is None then a freshly-allocated array is returned.

• where
This parameter is used to indicate a condition that is broadcast over the input. At those locations where the condition is True, the out array will be set to the b result, else the out array will retain its original value.

Returned Values:

This function will return a scalar if both x1 and x2 are scalars.

## Example 1:

In the example below, we will illustrate the usage of `bitwise_and()` function:

``````import numpy as np

num1 = 15
num2 = 20

print ("The Input  number1 is :", num1)
print ("The Input  number2 is :", num2)

output = np.bitwise_and(num1, num2)
print ("The bitwise_and of 15 and 20 is: ", output) ``````

The input number1 is: 15
The input number2 is: 20
The bitwise_and of 15 and 20 is: 4

## Example 2:

In the example below, we will apply the `bitwise_and()` function on two arrays:

``````import numpy as np

ar1 = [2, 8, 135]
ar2 = [3, 5, 115]

print ("The Input array1 is : ", ar1)
print ("The Input array2 is : ", ar2)

output_arr = np.bitwise_and(ar1, ar2)
print ("The Output array after bitwise_and: ", output_arr)``````

The Input array1 is : [2, 8, 135]
The Input array2 is : [3, 5, 115]
The Output array after bitwise_and: [2 0 3]

## Summary

In this tutorial, we covered the `bitwise_and()` function of the NumPy library. We covered its basic syntax and parameters and then the values returned by this function along with some examples of this function.