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# Compute the truth value of an array AND to another array element-wise in Numpy

To compute the truth value of an array AND another array element-wise, use the **numpy.logical_and()** method in Python Numpy. Return value is either True or False. Return value is the Boolean result of the logical AND operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars.

The out is 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. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

## Steps

At first, import the required library −

import numpy as np

Creating two 2D numpy array using the array() method. We have inserted elements −

arr1 = np.array([[True, False, False], [False, True, True]]) arr2 = np.array([[True, False, True], [True, True, False]])

Display the arrays −

print("Array 1...\n", arr1) print("\nArray 2...\n", arr2)

Get the type of the arrays −

print("\nOur Array 1 type...\n", arr1.dtype) print("\nOur Array 2 type...\n", arr2.dtype)

Get the dimensions of the Arrays −

print("\nOur Array 1 Dimensions...\n",arr1.ndim) print("\nOur Array 2 Dimensions...\n",arr2.ndim)

Get the shape of the Arrays −

print("\nOur Array 1 Shape...\n",arr1.shape) print("\nOur Array 2 Shape...\n",arr2.shape)

To compute the truth value of an array AND another array element-wise, use the numpy.logical_and() method. Return value is either True or False −

print("\nResult (AND)...\n",np.logical_and(arr1, arr2))

## Example

import numpy as np # Creating two 2D numpy array using the array() method # We have inserted elements arr1 = np.array([[True, False, False], [False, True, True]]) arr2 = np.array([[True, False, True], [True, True, False]]) # Display the arrays print("Array 1...\n", arr1) print("\nArray 2...\n", arr2) # Get the type of the arrays print("\nOur Array 1 type...\n", arr1.dtype) print("\nOur Array 2 type...\n", arr2.dtype) # Get the dimensions of the Arrays print("\nOur Array 1 Dimensions...\n",arr1.ndim) print("\nOur Array 2 Dimensions...\n",arr2.ndim) # Get the shape of the Arrays print("\nOur Array 1 Shape...\n",arr1.shape) print("\nOur Array 2 Shape...\n",arr2.shape) # To compute the truth value of an array AND another array elementwise, use the numpy.logical_and() method in Python Numpy # Return value is either True or False print("\nResult (AND)...\n",np.logical_and(arr1, arr2))

## Output

Array 1... [[ True False False] [False True True]] Array 2... [[ True False True] [ True True False]] Our Array 1 type... bool Our Array 2 type... bool Our Array 1 Dimensions... 2 Our Array 2 Dimensions... 2 Our Array 1 Shape... (2, 3) Our Array 2 Shape... (2, 3) Result (AND)... [[ True False False] [False True False]]

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