One warning you may encounter in Python is:

RuntimeWarning: overflow encountered in exp

This warning occurs when you use the NumPy **exp** function, but use a value that is too large for it to handle.

It’s important to note that this is simply a **warning** and that NumPy will still carry out the calculation you requested, but it provides the warning by default.

When you encounter this warning, you have two options:

**1.** Ignore it.

**2.** Suppress the warning entirely.

The following example shows how to address this warning in practice.

**How to Reproduce the Warning**

Suppose we perform the following calculation in Python:

import numpy as np #perform some calculation print(1/(1+np.exp(1140))) 0.0 /srv/conda/envs/notebook/lib/python3.7/site-packages/ipykernel_launcher.py:3: RuntimeWarning: overflow encountered in exp

Notice that NumPy performs the calculation (the result is 0.0) but it still prints the **RuntimeWarning**.

This warning is printed because the value np.exp(1140) represents e^{1140}, which is a *massive* number.

We basically requested NumPy to perform the following calculation:

- 1 / (1 + massive number)

This can be reduced to:

- 1 / massive number

This is effectively 0, which is why NumPy calculated the result to be **0.0**.

**How to Suppress the Warning**

If we’d like, we can use the **warnings** package to suppress warnings as follows:

import numpy as np import warnings #suppress warnings warnings.filterwarnings('ignore') #perform some calculation print(1/(1+np.exp(1140))) 0.0

Notice that NumPy performs the calculation and does not display a RuntimeWarning.

**Note**: In general, warnings can be helpful for identifying bits of code that take a long time to run so be highly selective when deciding to suppress warnings.

**Additional Resources**

The following tutorials explain how to fix other common errors in Python:

How to Fix KeyError in Pandas

How to Fix: ValueError: cannot convert float NaN to integer

How to Fix: ValueError: operands could not be broadcast together with shapes