# NumPy Logs - WTMatter

NumPy Logs – NumPy uFuncs (Python Tutorial): This is a detailed tutorial of the NumPy Logs Universal Functions. Learn the usage of these functions with the help of examples.

### NumPy Logs

These are the mathematical function which is helpful in calculating the natural logarithm of x where x is the input we give in the form of arrays. It is the inverse of the exponential function and also of the element-wise natural algorithm.

In NumPy, we can perform log at three bases which are at base 2, base e and base 10. These log function will place -inf or inf in the element if the log can’t be computed.

#### Log at Base 2

In order to get this log, we need to use `log2()` the function which will give us the log at base 2.

Let us take an example to understand it better

Output:

``[ 0\. 1\. 1.5849625 2\. 2.32192809 2.5849625 2.80735492 3\. 3.169925 ]``

Here in this example, it is returning us the log for integers starting at 1 to 9 where nine is not included.

#### Log to Base 10

In order to get the log for base 10, we will use `log10()` function.

Let us take an example to understand it better

Output:

``````[ 0\. 0.30103 0.47712125 0.60205999 0.69897 0.77815125
0.84509804 0.90308999 0.95424251]``````

So in this example, we get all the terms with log to base 10 in the array.

#### Log at Base e

This is also known as Natural log. And in order to find this natural log, we will use `log()` function.

Let us take an example:

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