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Get Log10 of Each Element in Numpy Array

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 log10 (logarithm with base 10) of a Numpy array with the help of some examples.

How to get the log10 of values in a Numpy array?

get the log10 of each element in numpy array

You can use the numpy.log10() function to get the log10 (logarithm with base 10) of each element in a Numpy array. Pass the array as an argument.

The following is the syntax –

numpy.log10(ar)

It returns an array containing the base 2 logarithm of each element in the passed array.

Let’s now look at a step-by-step example of using the numpy.log10() 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, 10, 100, 1000])
# display the array
print(ar)

Output:

[   1    2   10  100 1000]

Here, we used the numpy.array() function to create a Numpy array containing some numbers. You can see that the array contains some integers (note that there are some values that are powers of ten – 10, 100, and 1000).

Step 2 – Get the log10 using numpy.log10()

To get the base 10 log of each element in a Numpy array, pass the array as an argument to the numpy.log10() function.

Let’s get the base 10 log for the array created above.

# get the log10 of each element
np.log10(ar)

Output:

array([0.     , 0.30103, 1.     , 2.     , 3.     ])

We get a Numpy array with the base 10 logarithm value of each element in the array ar.

The numpy.log10() 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, 10, 1],
               [100, 10, 100],
               [2, 50, 10]])
# get the log10 of each element
np.log10(ar)

Output:

array([[0.     , 1.     , 0.     ],
       [2.     , 1.     , 2.     ],
       [0.30103, 1.69897, 1.     ]])

You can see that we get the base 10 log value of each element in the 2D array.

For more on the numpy.log10() function, refer to its documentation.

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Author

  • Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.