No module named sklearn ошибка - Ремонт и установка крупной бытовой техники

I want to import sklearn but there is no module apparently:

ModuleNotFoundError: No module named 'sklearn'

I am using Anaconda and Python 3.6.1; I have checked everywhere but still can’t find answers.

When I use the command:
conda install scikit-learn should this not just work?

Where does anaconda install the package?

I was checking the frameworks in my python library and there was nothing about sklearn only numpy and scipy.

Please help, I am new to using python packages especially via anaconda.

asked Sep 8, 2017 at 9:56

You can just use pip for installing packages, even when you are using anaconda:

pip install -U scikit-learn scipy matplotlib

This should work for installing the package.

And for Python 3.x just use pip3:

pip3 install -U scikit-learn scipy matplotlib

MBT

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answered Sep 8, 2017 at 10:00

mrCarnivoremrCarnivore

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Will leave below two options that may help one solve the problem:

Using conda
Using pip

One might want to consider the notes at the end, specially before resorting to the 2nd option.

Option 1

If one wants to install it in the root and one follows the requirements — (Python (>= 2.7 or >= 3.4), NumPy (>= 1.8.2), SciPy (>= 0.13.3).) — the following should solve the problem

conda install scikit-learn

Alternatively, as mentioned here, one can specify the channel as follows

conda install -c anaconda scikit-learn

Let’s say that one is working in the environment with the name ML.

Then the following should solve one’s problem:

conda install -n ML scikit-learn

# or

conda install -n ML -c anaconda scikit-learn

Option 2

If the above doesn’t work, on Anaconda Prompt one can also use pip (here’s how to pip install scikit-learn), so the following may help

pip install scikit-learn

However, consider the last note below before proceeding.

Notes:

When using Anaconda, one needs to be aware of the environment that one is working.

Then, in Anaconda Prompt, one needs to run the following
```
conda $command -n $ENVIRONMENT_NAME $IDE/package/module
```
$command — Command that one intends to use (consult documentation for general commands)

$ENVIRONMENT NAME — The name of one’s environment (if one is working in the root,
conda $command $IDE/package/module is enough)

$IDE/package/module — The name of the IDE or package or module
If one needs to install/update packages, the logic is the same as mentioned in the introduction. If you need more information on Anaconda Packages, check the documentation.
What is the flag -c.
pip doesn’t manage dependencies the same way conda does and can, potentially, damage one’s installation.

answered Sep 26, 2018 at 15:21

Gonçalo PeresGonçalo Peres

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If you are using Ubuntu 18.04 or higher with python3.xxx then try this command

$ sudo apt install python3-sklearn

then try your command. hope it will work

answered Sep 20, 2019 at 13:29

I did the following:

import sys
!{sys.executable} -m pip install sklearn

answered Jun 30, 2020 at 21:35

cesareressacesareressa

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On Windows, I had python 3+ version. pip version — 22.3.1

I had installed:

pip install sklearn

But, it seems it is deprecated with scikit-learn.

So, I did:

pip install scikit-learn

And, it worked!!!

answered Dec 8, 2022 at 7:58

KnockingHeadsKnockingHeads

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I’ve tried a lot of things but finally, including uninstall with the automated tools. So, I’ve uninstalled manually scikit-learn.

sudo rm -R /home/ubuntu/.local/lib/python3.6/site-packages/sklearn
sudo rm -R /home/ubuntu/.local/lib/python3.6/site-packages/scikit_learn-0.20.0-py3.6.egg-info

And re-install using pip

sudo pip3.6 install -U scikit-learn

Hope that can help someone else!

answered Oct 21, 2018 at 9:01

Claude COULOMBEClaude COULOMBE

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This happened to me, I tried all the possible solutions with no luck!

Finaly I realized that the problem was with Jupyter notebook environment, not with sklearn!

I solved the problem by re-installing Jupyter at the same environment as sklearn

the command is: conda install -c anaconda ipython. Done…

answered Dec 25, 2018 at 11:52

Mohammad ElNesrMohammad ElNesr

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The other name of sklearn in anaconda is scikit-learn. simply open your anaconda navigator, go to the environments, select your environment, for example tensorflow or whatever you want to work with, search for scikit_learn in the list of uninstalled packages, apply it and then you can import sklearn in your jupyter.

answered Jul 19, 2020 at 18:01

SasanSasan

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SOLVED:

The above did not help. Then I simply installed sklearn from within Jypyter-lab, even though sklearn 0.0 shows in ‘pip list’:

!pip install sklearn
import sklearn

What I learned later is that pip installs, in my case, packages in a different folder than Jupyter. This can be seen by executing:

import sys
print(sys.path)

Once from within Jupyter_lab notebook, and once from the command line using ‘py notebook.py’.

In my case Jupyter list of paths where subfolders of ‘anaconda’ whereas Python list where subfolders of c:users[username]…

answered Feb 2, 2021 at 21:08

ZviZvi

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Cause

Conda and pip install scikit-learn under ~/anaconda3/envs/$ENV/lib/python3.7/site-packages, however Jupyter notebook looks for the package under ~/anaconda3/lib/python3.7/site-packages.

Therefore, even when the environment is specified to conda, it does not work.

conda install -n $ENV scikit-learn # Does not work

Solution

pip 3 install the package under ~/anaconda3/lib/python3.7/site-packages.

Verify

After pip3, in a Jupyter notebook.

import sklearn
sklearn.__file__

~/anaconda3/lib/python3.7/site-packages/sklearn/init.py’

answered May 8, 2019 at 7:02

monmon

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I had the same problem.
The issue is when we work on multiple anaconda environments, not all packages are installed in all environments.
you can check your conda environment by writing the following code in anaconda prompt:

conda env list

then you can check the packages installed in each environment :

conda list -n NAME_OF_THE_ENVIRONMENT

for me, the environment that I was working with , was missing sklearn, although the package was installed in the other environments.

therefore, I just simply installed sklearn package in that particular environment

conda install -n NAME_OF_THE_ENVIRONMENT scikit-learn

and the issue was resolved

answered Jan 12, 2022 at 2:57

install these ==>> pip install -U scikit-learn scipy matplotlib
if still getting the same error then ,
make sure that your imoprted statment should be correct. i made the mistike while writing ensemble so ,(check spelling)
its
should be >>> from sklearn.ensemble import RandomForestClassifier

answered Jul 2, 2020 at 18:10

Akash DesaiAkash Desai

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I had the same issue as the author, and ran into the issue with and without Anaconda and regardless of Python version. Everyone’s environment is different, but after resolving it for myself I think that in some cases it may be due to having multiple version of Python installed. Each installed Python version has its own Libsite-packages folder which can contain a unique set of modules for that Python version, and where the IDE looks into folder path that doesn’t have scikit-learn in it.

One way to try solve the issue: you might clear your system of all other Python versions and their cached/temp files/system variables, and then only have one version of Python installed anywhere. Then install the dependencies Numpy and Scipy, and finally Scikit-learn.

More detailed steps:

Uninstall all Python versions and their launchers (e.g. from Control Panel in Windows) except the one version you want to keep. Delete any old Python version folders in the Python directory —uninstalling doesn’t remove all files.
Remove other Python versions from your OS’ Environment Variables (both under the system and user variables sections)
Clear temporary files. For example, for Windows, delete all AppData Temp cache files (in C:UsersYourUserNameAppDataLocalTemp). In addition, you could also do a Windows disk cleanup for other temporary files, and then reboot.
If your IDE supports it, create a new virtual environment in Settings, then set your only installed Python version as the interpreter.
In your IDE, install the dependencies Scipy and Numpy from the module list first, then install Scikit-Learn.

As some others have suggested, the key is making sure your environment is set up correctly where everything points to the correct library folder on your computer where the Sklearn package is located. There are a few ways this can be resolved. My approach was more drastic, but it turns out that I had a very messy Python setup on my system so I had to start fresh.

answered Nov 1, 2020 at 15:54

Using Anaconda-navigator UI environment

When running Anaconda-navigator:

Choose the ‘Environments’ tab on the left and create a new environment (e.g. ML — see Gonçalo Peres answer above, I made one called ‘CourseraML’).
Set Python version 3.7 (for Coursera course Applied Machine Learning in Python). Also include R.
Then find modules to install using the ‘not installed’ drop-down menu item. Search for each module needed in the search bar and select. sklearn is part of scikit-learn. Select it and install (it should find all relevant dependencies). Modules needed for Applied ML course: seaborn, numpy, scikit-learn, pandas, matplotlib
You’ll need to restart Jupyter Notebook and reopen your file.

Command line version of above:

conda install -n CourseraML seaborn scikit-learn pandas numpy matplotlib graphviz

answered May 4, 2021 at 7:37

AntCAntC

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Causes
-your jupyter notebook might be importing the sklearn and other libraries from the
another the location(path) than the libraries from conda or pip.

MY Problem
In my case, My jupyter notebook was importing the libraries for snap manager. Since, I install jupyter using the snap instead of other ways.

You can check where other libraries are being imported in jupyter using code:

import cv2 as cv
print(cv.__file__)

Solution
So , I uninstall jupyter notebook and then install notebook using conda.

 sudo snap remove jupyter

conda install -c conda-forge notebook

answered May 28, 2021 at 15:28

Источник

The error “ModuleNotFoundError: No module named sklearn» is a common error experienced by data scientists when developing in Python. The error is likely an environment issue whereby the scikit-learn package has not been installed correctly on your machine, thankfully there are a few simple steps to go through to troubleshoot the problem and find a solution.

Your error, whether in a Jupyter Notebook or in the terminal, probably looks like one of the following:

No module named 'sklearn'
ModuleNotFoundError: No module named 'sklearn'

In order to find the root cause of the problem we will go through the following potential fixes:

Upgrade pip version
Upgrade or install scikit-learn package
Check if you are activating the environment before running
Create a fresh environment
Upgrade or install Jupyer Notebook package

Are you installing packages using Conda or Pip package manager?

It is common for developers to use either Pip or Conda for their Python package management. It’s important to know what you are using before we continue with the fix.

If you have not explicitly installed and activated Conda, then you are almost definitely going to be using Pip. One sanity check is to run conda info in your terminal, which if it returns anything likely means you are using Conda.

Upgrade or install pip for Python

First things first, let’s check to see if we have the up to date version of pip installed. We can do this by running:

pip install --upgrade pip

Upgrade or install scikit-learn package via Conda or Pip

The most common reason for this error is that the scikit-learn package is not installed in your environment or an outdated version is installed. So let’s update the package or install it if it’s missing.

For Conda:

# To install in the root environment 
conda install -c anaconda scikit-learn 

# To install in a specific environment 
conda install -n MY_ENV scikit-learn

For Pip:‌

# To install in the root environment
python3 -m pip install -U scikit-learn

# To install in a specific environment
source MY_ENV/bin/activate
python3 -m pip install -U scikit-learn

Activate Conda or venv Python environment

It is highly recommended that you use isolated environments when developing in Python. Because of this, one common mistake developers make is that they don’t activate the correct environment before they run the Python script or Jupyter Notebook. So, let’s make sure you have your correct environment running.

For Conda:

conda activate MY_ENV

For virtual environments:

source MY_ENV/bin/activate

Create a new Conda or venv Python environment with scikit-learn installed

During the development process, a developer will likely install and update many different packages in their Python environment, which can over time cause conflicts and errors.

Therefore, one way to solve the module error for sklearn is to simply create a new environment with only the packages that you require, removing all of the bloatware that has built up over time. This will provide you with a fresh start and should get rid of problems that installing other packages may have caused.

For Conda:

# Create the new environment with the desired packages
conda create -n MY_ENV python=3.9 scikit-learn 

# Activate the new environment 
conda activate MY_ENV 

# Check to see if the packages you require are installed 
conda list

For virtual environments:

# Navigate to your project directory 
cd MY_PROJECT 

# Create the new environment in this directory 
python3 -m venv MY_ENV 

# Activate the environment 
source MY_ENV/bin/activate 

# Install scikit-learn 
python3 -m pip install scikit-learn

Upgrade Jupyter Notebook package in Conda or Pip

If you are working within a Jupyter Notebook and none of the above has worked for you, then it could be that your installation of Jupyter Notebooks is faulty in some way, so a reinstallation may be in order.

For Conda:

conda update jupyter

For Pip:

pip install -U jupyter

Best practices for managing Python packages and environments

Managing packages and environments in Python is notoriously problematic, but there are some best practices which should help you to avoid package the majority of problems in the future:

Always use separate environments for your projects and avoid installing packages to your root environment
Only install the packages you need for your project
Pin your package versions in your project’s requirements file
Make sure your package manager is kept up to date

References

Conda managing environments documentation
Python venv documentation

Источник

Sklearn or scikit learn is the most popular, free machine learning library for python. It includes widely used machine learning algorithms such as regression models, k nearest neighbors, k means clustering, support vector machine, dbscan, random forests, etc. Hence, there’s no surprise that data scientists or anyone with a passion for machine learning and Artificial Intelligence would want to install scikit learn in their systems. But a lot of developers have to face ModuleNotFoundError: No module named ‘sklearn’ once they try to execute their code. There can be a couple of reasons why they are seeing this error.

But first, What is a ModuleNotFoundError?

Simply A ModuleNotFoundError (In this particular case no module named ‘sklearn’ error) is raised at runtime when the python is unable/fails to import a module into your program. There are a few possible reasons behind this error.

Python cannot locate the module in your import command
You have misspelled your module name in your import command
You simply haven’t installed that module

Common Cause of ModuleNotFoundError: No module named ‘sklearn’

In most cases of no module named ‘sklearn’, we can rule out the number two and number three causes that I have just mentioned in the above section.

Because most of the time we know that we have installed scikit learn beforehand. And we also know that we have typed the name correctly.

Then it must be that python cannot locate sklearn module, right? Yes, Of Course!

Reasons why Python cannot locate the sklearn/scikit learn module

The reasons can be very complicated because every case is different. So one’s cause for no module named ‘sklearn’ error might not be the same as someone else’s. There are many possible scenarios why python cannot locate sklearn module. Starting from different python virtual environments and different python versions to things like whether you are running your algorithm in jupyter notebooks or in an IDE like PyCharm, can all be a possible cause. So we have to investigate every single scenario and apply possible fixes. Otherwise, we aren’t addressing no module named ‘sklearn’ in everyone’s favor!

Are you a complete beginner to Scikit-Learn? Or do you want more hands-on tutorials? Then check out the following Scikit Learn Books for beginners.

Scikit Learn has been installed in a different virtual environment than your program being executed

The first thing you should do when you see this error is to check your python virtual environment. Is it the same environment that you installed scikit learn into? If not, then python can’t locate the sklearn module and hence raises the error.

I have installed all my machine learning libraries and packages into a default environment called “tensorflow“. Why named TensorFlow? It’s just because I am working heavily with TensorFlow projects currently. The name of the environment can be anything that you wish. It’s just a method for isolating and organizing your different python projects so everything is clean and separated. You don’t have to worry about version incompatibilities, etc. if you have different environments.

But now, let’s import sklearn into a different python environment in PyCharm and check whether python can locate it or not.

ModuleNotFoundError No module named 'sklearn'

Yes, you guessed right! Python cannot locate sklearn module! We get the ModuleNotFoundError: No module named ‘sklearn’ error.

Let me edit my project environment and set it to tensorflow. And try again. Sown below.

choosing the environments in PyCharm edit configurations window

Running the code again, with the correct environment (tensorflow) where sklearn has been installed.

sklearn module successfully imported into pycharm

Now as you can see the problem has been solved. Hence, we can continue with our machine learning code, there are numerous things to be done using scikit learn after all! 🙂

ModuleNotFoundError: No module named ‘sklearn’ error in Jupyter Notebooks

Not everyone’s running their ML programs in a real IDE. Often developers use jupyter as an easy python development environment that actually lives on web. When trying to run sklearn within jupyter notebooks people seem to face no module named sklearn error often.

Let’s now look for the possible causes for this no module named ‘sklearn’ errors raised in jupyter notebooks.

Again, we know that we have installed scikit learn and we have spelled the thing correctly. So the obvious cause behind the error is that python cannot find the sklearn module to import.

Best practice of installing Jupyter notebooks with scikit learn in your computer to avoid ModuleNotFoundError: No module named ‘sklearn’

The best way to install jupyter and to work with essential python packages and modules like sklearn by default is by installing the Anaconda distribution. I highly recommend installing Anaconda. Every machine learning enthusiast should have this amazing distribution for python installed. 🙂

Do you already have Anaconda installed? Then what version it is? Read this guide to find that out. Check Anaconda Version in Windows?

If you have installed the latest Anaconda version, you must already have jupyter notebooks and scikit learn pre-installed. Then you should be able to run jupyter notebook and import sklearn with no issue.

Simply go to your CMD and type and hit enter the following command.

jupyter notebook

This will automatically open up jupyter notebook for you.

Let’s start a new notebook and checking whether we can import sklearn with no errors

import sklearn

sklearn. __version__

getting sklearn version in jupyter notebook

Success! There is no ModuleNotFoundError: No module named ‘sklearn’. I have the latest scikit- library which is 0.24.1.

No module named ‘sklearn’ error when jupyter notebooks and skleran installed separately

If you have installed jupyter notebooks and scikit-learn separately the chances are that jupyter notebooks cannot locate sklearn module to import.

Scenario 01:

For an example, you might have installed jupyter notebooks using another package manager like snap. Then Jupyter notebook will look for sklearn module inside the snap manager, which will raise an error ModuleNotFoundError: No module named ‘sklearn’.

Scenario 02:

Both Conda and pip install scikit-learn under the following path when using virtual environments.

~/anaconda3/envs/$ENV/lib/python"version"/site-packages

But Jupyter notebook searches for the installed packages under,

~/anaconda3/lib/python"version"/site-packages

Hence, it can’t locate the installed sklearn module. Then you get the infamous ModuleNotFoundError: No module named ‘sklearn’, yet again!

You can check the path of sklearn by running the following code in jupyter notebook.

import sklearn
sklearn.__file__

getting sklearn module path in jupyter notebooks

To avoid path mismatch, we can install scikit learn always under,

~/anaconda3/lib/python"version"/site-packages

Do you have several python versions installed in your computer?

When you have several python versions installed you are asking for trouble. Each python version must have its own path for Libsite-packages and its own set of packages and modules installed. So when your python machine learning program is looking for the sklearn module it literally doesn’t have any idea which python version’s path to look for. Hence raises ModuleNotFoundError: No module named ‘sklearn’ error.

As a solution, you can have one python version installed on your computer. If you do need several versions to be installed then you must install sklearn module into where jupyter notebook is pointing when it imports external modules.

Conclusion

ModuleNotFoundError: No module named ‘sklearn’ isn’t a complicated error. It’s a simple runtime error when python cannot import the specified module into your code. Most of the time this is because python cannot locate the path where sklearn module has been installed into. On other occasions, it’s we being so busy and misspelling the word “sklearn” in to something else. Lastly, in rare situations, it can be that we are trying to import the sklearn module when it’s hasn’t actually been installed! The bottom line is that this error isn’t something serious, you can always figure out what has gone wrong, and then fix it.

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Источник

When running Python code, sometimes you will see an error saying ModuleNotFoundError: No module named 'sklearn'.

This error means that Python can’t find the sklearn module. You may not have the sklearn module installed, or the module is installed in a different environment.

The example error log is as follows:

Traceback (most recent call last):
  File ...
    import sklearn
ModuleNotFoundError: No module named 'sklearn'

To fix this error, you need to install the sklearn package using pip or conda.

First, let’s see how to install sklearn with pip. You need to run one of the following commands:

# Use pip to install scikit-learn
pip install scikit-learn

# Or pip3
pip3 install scikit-learn

# If pip isn't available in PATH
python -m pip install scikit-learn

# Or with python3
python3 -m pip install scikit-learn

# For Windows without pip in PATH
py -m pip install scikit-learn

Once the installation has finished, you should be able to import the sklearn module in your code successfully.

When you are running Python from Jupyter Notebook, add the ! operator before pip like this:

!pip install -U scikit-learn
# or
!conda install -c anaconda scikit-learn

If you installed Python from Anaconda distribution, then you might want to install the sklearn package from conda with the following command:

conda install scikit-learn

If you still see the error, it means the Python interpreter still can’t find the sklearn module.

One of the following scenarios may happen in your case:

You have multiple versions of Python installed on your system, and you are using a different version of Python than the one where scikit-learn is installed.
You might have scikit-learn installed in a virtual environment, and you are not activating the virtual environment before running your code.

Let’s see how to fix these errors.

Case#1 — You have multiple versions of Python

If you have multiple versions of Python installed on your system, you need to make sure that you are using the specific version where the scikit-learn package is installed.

You can test this by running the which -a python or which -a python3 command from the terminal:

$ which -a python
/opt/homebrew/bin/python
/usr/bin/python

In the example above, there are two versions of Python installed on /opt/homebrew/bin/python and /usr/bin/python.

Suppose you run the following steps in your project:

Install scikit-learn with pip using /usr/bin/ Python version
Install Python using Homebrew, now you have Python in /opt/homebrew/
Then add import scikit-learn in your code

The steps above will cause the error because scikit-learn is installed in /usr/bin/, and your code is probably executed using Python from /opt/homebrew/ path.

To solve this error, you need to run pip install scikit-learn command again so that the package is installed and accessible by the new Python version.

Finally, keep in mind that you can also have pip and pip3 available on your computer.

The pip command usually installs module for Python 2, while pip3 installs for Python 3. Make sure that you are using the right command for your situation.

Next, you can also have the package installed in a virtual environment.

Case#2 — You are using Python virtual environment

Python venv package allows you to create a virtual environment where you can install different versions of packages required by your project.

If you are installing scikit-learn inside a virtual environment, then the module won’t be accessible outside of that environment.

Even if you never run the venv package, Python Anaconda distribution usually creates a virtual enviroment automatically when you install it on your computer.

You can see if a virtual environment is activated or not by looking at your command prompt.

When a virtual environment is activated, the name of that environment will be shown inside parentheses as shown below:

In the picture above, the name of the virtual environment (base) appears when the Conda virtual environment is activated.

Usually, a Conda virtual environment already has the scikit-learn module active. You can check this in the Anaconda Environments tab as shown below:

If you see scikit-learn installed but the environment is not activated, then run the command below to activate it:

conda activate <env>

# For base env:
conda activate base

Once the base environment is activated, you should be able to import sklearn module.

Conclusion

To conclude, the ModuleNotFoundError: No module named 'scikit-learn' error occurs when the scikit-learn package is not available in your Python environment.

To fix this error, you need to install scikit-learn using pip or conda.

If you already have the module installed, make sure you are using the correct version of Python, or activate the virtual environment if you have one.

By following these steps, you should be able to import scikit-learn modules in your code successfully.

Источник

No module named sklearn is an error you trigger in Python when you import the scikit-learn module without installing it first or doing so in the wrong environment.

It is among the most common errors you may come across when importing this package in your source code. Especially when working on data science projects. This guide will teach you the causes of this error and how to use this module correctly.

Contents

Why Am I Getting No Module Named Sklearn Error in Python?
- – Importing the Package Without Installing It
- – Scikit-learn Library Not Installed or Configured in Different Platforms
How To Solve the No Module Named Sklearn Python Error? Quick Solutions
- – Proper Installation of This Python Package Using Pip
- – Using an Up-to-Date Sklearn Module or Upgrading It
- – Make Use of a Virtual Environment – Reaping the Benefits
- – Fixing Common Mistakes
Conclusion

Why Am I Getting No Module Named Sklearn Error in Python?

You are getting the no module named sklearn error in Python because the scikit-learn library (also known as “sklearn”) is not installed or not properly configured in your Python environment. Also, you may get this error when running an older version of Python incompatible with this package.

You will also trigger this error if you install the package globally instead of in your virtual environment. In addition, if you name your module sklearn.py, this is going to shadow the official module. The same thing happens if you declare a variable by the name sklearn that can shadow the imported variable.

In addition, you likely have the module installed in one version of Python, but you are running your source code in another version. As a result, you are going to trigger this error since the scikit-learn module is not in the version you are using.

– Importing the Package Without Installing It

Below is an example of how you can trigger this error if you fail to install the package but import it in your source code:

import sklearn

from sklearn.linear_model import LinearRegression

model = LinearRegression()

If the scikit-learn library is not installed or not properly configured in your Python environment, the first line of the code will trigger the error. No Module Named Sklearn Causes

Also, you will trigger the error if you run the code on a different environment where the package is not installed. Running this code will cause the following error:

Traceback (most recent call last):

File “main.py”, line 1, in <module>

import sklearn

ModuleNotFoundError: No module named ‘sklearn’

– Scikit-learn Library Not Installed or Configured in Different Platforms

Several platforms may trigger the no module named sklearn error. Here are some of the popular ones that you trigger the error in:

no module named ‘sklearn’ spyder: The error no module named ‘sklearn’ in Spyder typically indicates that the scikit-learn library is not installed on your system or is not properly configured with your Python environment.
no module named ‘sklearn’ jupyter: If you are getting the No module named sklearn error when running code in Jupyter notebook, it is likely that the scikit-learn library is not installed or not properly configured in the environment that Jupyter is using.
no module named ‘sklearn’ python3: The error in Python3 indicates that the sklearn library often used in machine learning is not installed on your system or is not properly configured with your Python environment.
no module named ‘sklearn’ pycharm: If you are getting a no module named sklearn error in PyCharm, it means that the scikit-learn library is not installed for the Python interpreter that you are using.
no module named ‘sklearn’ conda: You will get a no module named sklearn error when using conda if the scikit-learn library is not installed in your conda environment.
no module named ‘sklearn’ vscode: If you are getting this error when using Visual Studio Code (VSCode), it means that the sklearn module is not installed for the Python interpreter that you are using.
modulenotfounderror no module named ‘sklearn’ streamlit: The error ModuleNotFoundError: No module named sklearn in Streamlit can occur if the sklearn library is not installed. Also, you will trigger it if the library is not properly configured in the environment that you are using to run your Streamlit app.
no module named ‘sklearn externals _pep562: The error no module named sklearn.externals._pep562 typically occurs when you are trying to use a version of scikit-learn that is not compatible with the version of Python you have installed.

How To Solve the No Module Named Sklearn Python Error? Quick Solutions

To solve the no module named sklearn error, you need to ensure that the scikit-learn library is installed and properly configured in Python.

Besides installing the module, you can accomplish this in various ways depending on whether you are using it in a virtual environment or a conventional one.

– Proper Installation of This Python Package Using Pip

Ensuring that the package is installed correctly in your environment is the most crucial thing to do. This is true even when installing packages that serve different purposes in Python. If you have different versions of Python on your computer, then each time you install the module, the installation is linked to one version.

Thus, ensure you utilize the right command when installing the sklearn via pip. You can install sklearn package using any of the following commands:

$ pip install the_package_name

$ pip3 install the_package_name

These commands will install the package you specify. However, you should use the notation below when using pip to install Python packages.

$ python3 -m pip install scikit-learn

When you use this notation, you ensure the installed package is available to the version of Python you use to execute your code.

– Using an Up-to-Date Sklearn Module or Upgrading It

Another way is to upgrade the package you are using in your application to the latest version. Upgrading sklearn may resolve the “No module named sklearn” error if the error is caused by an outdated version of the library. No Module Named Sklearn Fixes

The best rule of thumb is to make sure that you have the latest version of the library installed and to double-check your import statement and dependencies before attempting to upgrade. To update the sklearn module, you need to run this command:

pip install –upgrade scikit-learn

– Make Use of a Virtual Environment – Reaping the Benefits

If the error arises from a conflict with other versions of the library or dependencies, then using a virtual environment can be a vital solution to the error. A virtual environment is a tool that allows you to create isolated environments for your Python projects. This allows you to install specific versions of libraries and dependencies without affecting the global Python environment.

By creating a virtual environment and installing sklearn within that environment, you can ensure that your project is using the correct version of sklearn. Also, you make sure that it is not affected by any other versions of the library that may be installed globally.

You can create a virtual environment using venv or virtualenv and then activate it before installing sklearn. Each virtual environment in Python is isolated with a Python binary. In addition, you can install packages in it.

If you are not utilizing a virtual environment, you should consider doing so since it helps manage package dependencies easily and more effectively.

To work on a project that needs scikit-learn in a virtual environment, there are three steps to follow. First, you need to create a virtual environment and place the project inside. Second, you need to activate the virtual environment.

Lastly, after successfully activating the virtual environment, you can install the sklearn module.

python -m venv myenv

source myenv/bin/activate # This will activate your virtual environment

-m pip install scikit-learn # This is going to install the scikit-learn in your virtual environment

Kindly remember that the virtual environment is going to use the Python version you used to create it.

– Fixing Common Mistakes

One thing you should avoid is declaring a variable whose name is sklearn since it is likely going to shadow the original module. In case the error persists, you can try uninstalling the package and reinstalling it. Also, you can try restarting the IDE as well as the development server/script.

Double-check the spelling of the library name in the import statement. Make sure it is sklearn and not sklearns, sklern, or any other variation. It is crucial to have the correct version of Python. Check if you are using the version of Python that you intended to use and that sklearn is compatible with that version.

Establish that you have all the necessary dependencies installed. sklearn has several dependencies, such as NumPy and SciPy, that must be installed for it to work correctly. Make sure that all these dependencies are installed.

Lastly, check if the library is imported correctly. Sometimes, if you do not do the imports correctly, it causes issues. Therefore, check the imports and make sure that they are done correctly.

Conclusion

In conclusion, this article has helped you learn that the no module named ‘sklearn’ error can occur when working with the scikit-learn library. Here is a summary of the article that will help you grasp the concept more efficiently:

The error occurs when the sklearn library is not installed or cannot be imported properly.
Other causes include issues such as an outdated version of the library, missing dependencies, or a typo in the import statement.
To solve it, install the sklearn package, configure it, and check for any missing dependencies.
Also, you can consider using virtual environments to isolate your project dependencies.

We are confident that now, you know all about the “no module named sklearn” error and you can easily resolve it and complete your project successfully.

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