# Element-Wise Division in Python Numpy

This tutorial will introduce the methods to carry out an element-wise division on NumPy arrays in Python.

## NumPy Element-Wise Division With `numpy.divide()` Function

If we have two arrays and want to divide each element of the first array with each element of the second array, we can use the `numpy.divide()` function. The `numpy.divide()` function performs element-wise division on NumPy arrays. The `numpy.divide()` function takes the dividend array, the divisor array, and the output array as its arguments and stores the division’s results inside the output array. See the following code example.

``````import numpy as np

array1 = np.array([10,20,30])
array2 = np.array([2,4,6])

np.divide(array1, array2, array3)
print(array3)
``````

Output:

``````[5. 5. 5.]
``````

In the above code, we first created the two NumPy arrays, the dividend array `array1`, and the divisor array `array2` with the `np.array()` function. We then divided the `array1` by the `array2` and stored the results inside the NumPy array `array3` with the `np.divide()` function.

## NumPy Element-Wise Division With the `/` Operator

We can also use the `/` operator to carry out element-wise division on NumPy arrays in Python. The `/` operator is a shorthand for the `np.true_divide()` function in Python. We can use the `/` operator to divide one array by another array and store the results inside a third array. See the following code example.

``````import numpy as np

array1 = np.array([10,20,30])
array2 = np.array([2,4,6])

array3 = array1/array2
print(array3)
``````

Output:

``````[5. 5. 5.]
``````

We divided the `array1` by the `array2` and stored the results inside the NumPy array `array3` with the `/` operator.

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