The Numpy library in Python comes with a number of built-in functions to perform common mathematical operations on arrays. In this tutorial, we will look at one such function that helps us get the element-wise natural log of a Numpy array with the help of some examples.

## How to get the natural log in Numpy?

You can use the `numpy.log()`

function to get the natural logarithm of each element in a Numpy array. Pass the array as an argument.

The following is the syntax –

numpy.log(ar)

It returns an array containing the natural log value of each element in the passed array.

Let’s now look at a step-by-step example of using the `numpy.log()`

function.

### Step 1 – Create a Numpy array

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np # create numpy array e = np.exp(1) ar = np.array([1, 2, e, e**2, 10]) # display the array print(ar)

Output:

[ 1. 2. 2.71828183 7.3890561 10. ]

Here, we used the `numpy.array()`

function to create a Numpy array containing some numbers. You can see that the array contains some integers and some lower powers of `e`

(we use `numpy.exp()`

to get the value of `e`

).

### Step 2 – Get the natural log using `numpy.log()`

To get the natural log of each element in a Numpy array, pass the array as an argument to the `numpy.log()`

function.

Let’s get the natural log for the array created above.

# get the log of each element np.log(ar)

Output:

array([0. , 0.69314718, 1. , 2. , 2.30258509])

We get a Numpy array with the natural log value of each element in the array `ar`

.

The `numpy.log()`

function works similarly on higher-dimensional arrays. For example, let’s apply this function to a 2D array of some numbers.

# create 2D numpy array e = np.exp(1) ar = np.array([[1, e, 1], [e**2, 10, e**2], [4, e**4, 5]]) # get the log of each element np.log(ar)

Output:

array([[0. , 1. , 0. ], [2. , 2.30258509, 2. ], [1.38629436, 4. , 1.60943791]])

You can see that we get the natural log value of each element in the 2D array.

For more on the `numpy.log()`

function, refer to its documentation.

You might also be interested in –

- Numpy – Get the Sign of Each Element in Array
- Get the Median of Numpy Array – (With Examples)
- Numpy – Get Standard Deviation of Array Values
- Numpy – Get Min Value in Array

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