# 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?

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).

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### 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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