How to Upgrade or Uninstall Matplotlib in Python

Whether your code is throwing compatibility warnings, a newer Matplotlib version has features you want to use, or you just need a clean slate, this guide covers everything.

I’ll show you how to check your current version, upgrade Matplotlib, install a specific version, and completely uninstall it — using pip, conda, and inside virtual environments.

Check Your Current Matplotlib Version First

Before doing anything else, check what version you’re running. Open your terminal and run:

python -m pip show matplotlib

I executed the above example code and added the screenshot below.

This gives you a full picture — the version number, install location, and its dependencies:

Name: matplotlib
Version: 3.8.2
Summary: Python plotting package
Location: /usr/local/lib/python3.12/site-packages
Requires: contourpy, cycler, fonttools, kiwisolver, numpy, packaging, pillow, pyparsing, python-dateutil

Or if you just want the version number quickly:

python -c "import matplotlib; print(matplotlib.__version__)"

You can also check it from inside a Python shell or Jupyter Notebook:

import matplotlib
print(matplotlib.__version__)

Check the Latest Available Version Before Upgrading

Before upgrading, it’s worth checking what the latest stable version of Matplotlib is on PyPI:

pip index versions matplotlib

This lists all available versions from newest to oldest. If you want just the latest version number without upgrading:

pip install matplotlib== 

Leave the version number blank and pip will return an error message that helpfully shows you all available versions — a quick hack that works.

How to Upgrade Matplotlib Using pip

Let’s see how to upgrade Matplotlib using pip.

Upgrade to the Latest Stable Version

This is the command you’ll use most of the time:

python -m pip install --upgrade matplotlib

Again, I use python -m pip instead of just pip to make sure I’m upgrading inside the correct Python environment — especially important when you have multiple Python versions installed.

After upgrading, verify the new version:

python -c "import matplotlib; print(matplotlib.__version__)"

I executed the above example code and added the screenshot below.

Upgrade pip Itself Before Upgrading Matplotlib

If you haven’t updated pip in a while, it’s good practice to upgrade it first. An outdated pip can sometimes cause installation issues:

python -m pip install --upgrade pip
python -m pip install --upgrade matplotlib

Read: Matplotlib Plots a Line

Upgrade Matplotlib and All Its Dependencies at Once

Matplotlib depends on several packages — NumPy, Pillow, contourpy, and others. To upgrade everything together:

python -m pip install --upgrade matplotlib numpy pillow

How to Install a Specific Version of Matplotlib

Sometimes you don’t want the latest version. Maybe you’re working on a project that requires a specific Matplotlib version for compatibility reasons, or you’re following a tutorial written for an older version.

To install a specific version:

pip install matplotlib==3.8.0

Replace 3.8.0 with whichever version you need.

To install a version within a range (at least 3.7 but less than 3.9):

pip install "matplotlib>=3.7,<3.9"

To install the minimum version or higher:

pip install "matplotlib>=3.8"

Downgrade Matplotlib to an Older Version

If you just upgraded and something broke, you can roll back to the previous version:

pip install matplotlib==3.8.2

pip will uninstall the current version and install the one you specify.

Check out: Python Plot Multiple Lines Using Matplotlib

How to Upgrade Matplotlib in a Virtual Environment

If you’re using a virtual environment (and you should be for any real project), activate it first and then upgrade:

On macOS/Linux:

source venv/bin/activate
pip install --upgrade matplotlib

On Windows:

venv\Scripts\activate
pip install --upgrade matplotlib

The upgrade only affects packages inside the active environment — nothing else on your machine is touched. That’s exactly the point of virtual environments.

How to Upgrade Matplotlib With Conda

If you’re using Anaconda or Miniconda, use conda to upgrade — not pip — so conda can properly manage all dependencies:

conda update matplotlib

To upgrade to the absolute latest version available on conda-forge:

conda update -c conda-forge matplotlib

To upgrade everything in your conda environment at once (use with care):

conda update --all

Check the new version after upgrading:

python -c "import matplotlib; print(matplotlib.__version__)"

How to Uninstall Matplotlib Using pip

Here, we will learn how to uninstall Matplotlib using pip

Basic Uninstall

pip uninstall matplotlib

I executed the above example code and added the screenshot below.

pip will ask you to confirm:

Found existing installation: matplotlib 3.10.1
Uninstalling matplotlib-3.10.1:
  Would remove:
    /usr/local/lib/python3.12/site-packages/matplotlib/*
    /usr/local/lib/python3.12/site-packages/mpl_toolkits/*
    /usr/local/lib/python3.12/site-packages/pylab.py
Proceed (Y/n)?

Type Y and press Enter. Done.

Skip the Confirmation Prompt

If you’re scripting this or just want a faster uninstall:

pip uninstall matplotlib -y

The -y flag auto-confirms without prompting.

Uninstall With Verbose Output

If you want to see exactly what’s being removed:

pip uninstall matplotlib --verbose

Read: What is Matplotlib Inline in Python

How to Completely Remove Matplotlib (Clean Uninstall)

A regular pip uninstall removes the package files, but Matplotlib also stores cached data — fonts, style files, configuration — in a separate folder. If you’re doing a clean reinstall to fix a broken installation, you need to clear those too.

Step 1: Uninstall the package

pip uninstall matplotlib -y

Step 2: Clear the pip cache

pip cache purge

Step 3: Delete the Matplotlib config/cache folder

This is where Matplotlib stores its font cache, style sheets, and configuration files. The location depends on your OS:

On macOS/Linux:

rm -rf ~/.config/matplotlib
rm -rf ~/.cache/matplotlib

On Windows (in Command Prompt):

rmdir /s /q %USERPROFILE%\.matplotlib

To find the exact location on your machine, run this before deleting:

import matplotlib
print(matplotlib.get_cachedir())
print(matplotlib.get_configdir())

Step 4: Reinstall fresh

python -m pip install matplotlib

This gives you a completely clean installation with no leftover cache files that could cause issues.

How to Uninstall Matplotlib With Conda

If you installed Matplotlib via conda, uninstall it through conda — not pip:

conda remove matplotlib

conda will calculate what to remove and ask for confirmation. It’s smart enough to also flag any packages that depended on Matplotlib.

To uninstall without being asked for confirmation:

conda remove matplotlib -y

Verify That Matplotlib Has Been Uninstalled

After uninstalling, confirm it’s actually gone:

pip show matplotlib

You should see:

WARNING: Package(s) not found: matplotlib

Or try importing it in Python:

python -c "import matplotlib"

You should get:

ModuleNotFoundError: No module named 'matplotlib'

If you still see the module import successfully after uninstalling, you likely have Matplotlib installed in multiple Python environments and you uninstalled it from the wrong one. Check which Python you’re running with:

python -c "import sys; print(sys.executable)"

Then re-run the uninstall using that exact Python:

/path/to/python -m pip uninstall matplotlib

Upgrade Matplotlib in VS Code

VS Code has its own Python interpreter setting. When you upgrade Matplotlib in the terminal, make sure VS Code’s terminal is using the same Python environment.

Open VS Code’s integrated terminal (Terminal > New Terminal), check which Python is active:

python -c "import sys; print(sys.executable)"

Then run the upgrade:

python -m pip install --upgrade matplotlib

If you’re getting old version errors inside VS Code despite upgrading, press Ctrl+Shift+P → Python: Select Interpreter and confirm it’s pointing to the correct environment.

Check out: Matplotlib Best Fit Line

Upgrade Matplotlib in Jupyter Notebook

Upgrade directly from a notebook cell to make sure you’re upgrading into the notebook’s kernel:

%pip install --upgrade matplotlib

After running this, restart the kernel (Kernel > Restart) before importing Matplotlib. This is important — Jupyter caches the old version in memory until you restart.

Verify inside the notebook:

import matplotlib
print(matplotlib.__version__)

Common Questions

You may also read:

• Save a Matplotlib Plot as a Transparent PNG in Python
• Save NumPy Array as PNG Image in Python Matplotlib
• Save a Matplotlib Plot as PNG Without Borders in Python
• How to Save a Matplotlib Axis as PNG in Python

Bijay Kumar

I am Bijay Kumar, a Microsoft MVP in SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 years. During this time I got expertise in various Python libraries also like Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… for various clients in the United States, Canada, the United Kingdom, Australia, New Zealand, etc. Check out my profile.

enjoysharepoint.com/