No module named 'sklearn'

You are missing sklearn package in your Python environment!

You got error message about missing Python package. The error happens when you try to import Python module sklearn. The Python complains that sklearn 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:


python -c "import sklearn"

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

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

import sklearn
ModuleNotFoundError Traceback (most recent call last)
Cell In[1], line 1
1 import sklearn

ModuleNotFoundError: No module named 'sklearn'

3 ways to fix - No module named sklearn

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 sklearn using pip
  • - install sklearn using conda
  • - automatic install of sklearn 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 --version

conda 23.11.0
If conda is missing in your environment you will get output similar to:

conda --version

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 sklearn with pip

Please run the following command to install sklearn with pip:

pip install scikit-learn

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 scikit-learn

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

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

Install sklearn with conda

The sklearn package can be installed with the command:

conda install -c conda-forge scikit-learn

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 sklearn is installed in the correct environment and will be accessable in your current notebook. Please check scikit-learn conda-forge website to check latest version number and history of releases.

Automatic install of sklearn 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 sklearn and it is not available in Python environment then you will get the below information.

Install packages

Please install below packages to use this code recipe.

scikit-learn >= 1.4.2

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

Install packages

Please install below packages to use this code recipe.

Please wait, package installation ...

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

Required packages

scikit-learn >= 1.4.2

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

What is sklearn?

Scikit-learn, commonly abbreviated as sklearn, is a popular open-source machine learning library for the Python programming language. It provides simple and efficient tools for data mining and data analysis, built on top of other scientific computing libraries like NumPy, SciPy, and matplotlib. Scikit-learn offers a wide range of machine learning algorithms for tasks such as classification, regression, clustering, dimensionality reduction, and model selection. It also provides tools for data preprocessing, model evaluation, and cross-validation. With its easy-to-use interface and extensive documentation, scikit-learn is widely used by both beginners and experienced machine learning practitioners for developing machine learning models and analyzing data. Its simplicity and versatility make it a go-to choice for many data scientists and researchers.

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