No module named 'scikit-plot'

You got error message about missing Python package. The error happens when you try to import Python module scikit-plot. The Python complains that scikit-plot module can't be importend because its path is not present in your current Python path.

When using Python srcipt in your terminal your output with error message might look like this:

Traceback (most recent call last):
File "<string>", line 1, in <module>
ModuleNotFoundError: No module named 'scikit-plot'

Are you using Python notebook? Then your code cell with error message looks similar to:

import scikit-plot

---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last) 
Cell In[1], line 1
----> 1 import scikit-plot

ModuleNotFoundError: No module named 'scikit-plot'

3 ways to fix - No module named scikit-plot

Don't worry. We will fix the issue. You need to install missing package. We will show you 3 ways of how it can be fixed:

• - install scikit-plot using pip
• - install scikit-plot using conda
• - automatic install of scikit-plot in MLJAR Studio

Why there are three ways to fix this issue? It all depends on which package manager are you using. The most common package manager is pip. The common choice, especially in Windows environments, is conda manager. There are also other Python package managers, for example Poetry, but we don't cover them in this article.

The last way to fix issue, is to use MLJAR Studio. It is a notebook based programming environment that can automatically detect missing Python packages and install them.

How to check if package manager is pip or conda

Are you not sure what package manager are you using? Please try the following command and if you goet the conda version displayed it means that you are using conda package manager:

conda 23.11.0

Command 'conda' not found

Please try the below code cell if you are in Python notebook. If you get no error then you are using conda otherwise please use pip for installing new packages.

import sys
!conda list --prefix {sys.prefix}

Install scikit-plot with pip

Please run the following command to install scikit-plot with pip:

pip install mljar-scikit-plot

If you are using virtual environment, please make sure that it is activated.

For Python notebook users, please use the following command:

import sys
!{sys.executable} -m pip install mljar-scikit-plot

This will ensure that a new package is installed in Python from currently used notebook kernel. You will be able to import scikit-plot package in your notebook.

It is worth to check the PyPi website of mljar-scikit-plot. You can check there what is the current version and history of releases.

Install scikit-plot with conda

The scikit-plot package can be installed with the command:

conda install -c conda-forge mljar-scikit-plot

If you are in Python notebook, please use the following code:

import sys
!conda install --yes --prefix {sys.prefix} -c conda-forge {entry.installName}

The above code cell ensures you that scikit-plot is installed in the correct environment and will be accessable in your current notebook. Please check mljar-scikit-plot conda-forge website to check latest version number and history of releases.

Automatic install of scikit-plot in MLJAR Studio

MLJAR Studio is a notebook based programming environment. It offers a set of interactive Python code recipes to make coding super easy.

Each code recipe has information about required packages. If code recipe depends on scikit-plot and it is not available in Python environment then you will get the below information.

Please wait a while for scikit-plot package installation after clicking Install package button. You will see below message:

After successful installation you will get information that package is available and you can use code recipe.

You can focus on coding rather than fighting your python environment thanks to automatic package management.

What is scikit-plot?

Scikit-plot is a Python library that provides a set of functions for plotting various types of visualizations related to machine learning models and their evaluation. Built on top of Matplotlib, it extends the functionality of scikit-learn by offering convenient plotting tools for model performance metrics, such as confusion matrices, ROC curves, and precision-recall curves. Scikit-plot simplifies the process of visualizing model results, helping users to better understand and interpret their machine learning models. It integrates seamlessly with scikit-learn, making it a useful tool for data scientists and machine learning practitioners.

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