# NumPy Array Equal

This article will introduce the methods to carry out element-wise equality comparison on NumPy arrays in Python.

## NumPy Arrays Equality Check With the `==` Operator in Python

The `==` equality comparison operator is used to check whether two quantities are equal or not. The `==` operator returns `True` if the quantities are equal and `False` if the quantities are not equal. We can use the `==` operator along with the `all()` function to check whether all the elements of the two arrays are equal or not. The following code example shows us how we can element-wise compare two arrays for equality with the `==` operator in Python.

``````import numpy as np

array1 = np.array([1,2,3,4,5])

array2 = np.array([1,2,3,4,5])
print((array1 == array2).all())
``````

Output:

``````True
``````

In the above code, we element-wise compared the arrays `array1` and `array2` for equality with the `==` operator and the `all()` function. We first created the arrays `array1` and `array2` with the `np.array()` function. We then used the `==` operator with the `all()` function to check if all the values inside `array1` are equal to the values inside `array2`. This approach is very efficient and easy to understand, but there are a few disadvantages to using this approach. For example, if either of the arrays is empty and the second array contains only one element, this approach will return a `True` value. Another problem is that if both arrays have different shapes, this approach will give us an error.

## NumPy Arrays Equality Check With the `numpy.array_equal()` Function

A more thorough and error-free way of achieving the same objective as the previous approach is to use the `numpy.array_equal()` function. The `numpy.array_equal()` function compares two arrays for equality. The `numpy.array_equal()` function returns `True` if the arrays are equal and `False` if the arrays are not equal. The following code example shows us how we can element-wise compare two arrays for equality with the `numpy.array_equal()` function.

``````import numpy as np

array1 = np.array([1,2,3,4,5])

array2 = np.array([1,2,3,4,5])
print(np.array_equal(array1,array2))
``````

Output:

``````True
``````

In the above code, we used the `np.array_equal()` function to check if all the values inside `array1` are equal to the values inside `array2`.

## NumPy Arrays Equality Check With the `numpy.array_equiv()` Function in Python

The `numpy.array_equiv()` function can also be used to check whether two arrays are equal or not in Python. The `numpy.array_equiv()` function returns `True` if both arrays have the same shape and all the elements are equal, and returns `False` otherwise.

``````import numpy as np

array1 = np.array([1,2,3,4,5])

array2 = np.array([0,2,3,4,5])
print(np.array_equiv(array1,array2))
``````

Output:

``````False
``````

In the above code, we used the `np.array_equiv()` function to check if `array1` is equal to `array2`.

## NumPy Equal With the `numpy.allcloses()` Function in Python

The `numpy.allclose()` function can also be used to check if two arrays are element-wise equal or not in Python. The `numpy.allclose()` function returns `True` if all the elements inside both arrays are equal within a specified tolerance.

``````import numpy as np

array1 = np.array([1,2,3,4,5])

array2 = np.array([1,2,3,4,5])
print(np.allclose(array1,array2))
``````

Output:

``````False
``````

In the above code, we used the `np.allclose()` function to check if `array1` is equal to `array2`.

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