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.

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.

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.

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.

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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