One common error you may encounter when using Python is:
no module named 'seaborn'
This error occurs when Python does not detect the seaborn library in your current environment.
This tutorial shares the exact steps you can use to troubleshoot this error.
Step 1: pip install seaborn
Since seaborn doesn’t come installed automatically with Python, you’ll need to install it yourself. The easiest way to do so is by using pip, which is a package manager for Python.
You can run the following pip command to install seaborn:
pip install seaborn
In most cases, this will fix the error.
Step 2: Install pip
If you’re still getting an error, you may need to install pip. Use these steps to do so.
You can also use these steps to upgrade pip to the latest version to ensure that it works.
You can then run the same pip command as earlier to install seaborn:
pip install seaborn
At this point, the error should be resolved.
Step 3: Check seaborn and pip Versions
If you’re still running into errors, you may be using a different version of seaborn and pip.
You can use the following commands to check if your seaborn and pip versions match:
which python python --version which pip
If the two versions don’t match, you need to either install an older version of seaborn or upgrade your Python version.
Step 4: Check seaborn Version
Once you’ve successfully installed seaborn, you can use the following command to display the seaborn version in your environment:
pip show seaborn Name: seaborn Version: 0.11.2 Summary: seaborn: statistical data visualization Home-page: https://seaborn.pydata.org Author: Michael Waskom Author-email: firstname.lastname@example.org License: BSD (3-clause) Location: /srv/conda/envs/notebook/lib/python3.7/site-packages Requires: numpy, scipy, matplotlib, pandas Required-by: Note: you may need to restart the kernel to use updated packages.
Note: The easiest way to avoid errors with seaborn and Python versions is to simply install Anaconda, which is a toolkit that comes pre-installed with Python and seaborn and is free to use.
The following tutorials explain how to fix other common problems in Python: