Running Jupyter Notebook in a Virtual Environment: Installed Scikit-learn Module Not Available
As a data scientist or software engineer, one of the most important tools in your arsenal is the Jupyter Notebook. It enables you to create and share documents that contain live code, equations, visualizations, and narrative text. However, when working on a project, it’s essential to create a virtual environment. A virtual environment is an isolated Python environment that allows you to install packages and dependencies specific to your project without affecting the global Python installation.
In this tutorial, we’ll show you how to run Jupyter Notebook in a virtual environment and how to troubleshoot the common error of a missing scikit-learn module.
Table of Contents
- Step-by-Step Installing scikit-learn in a Virtual Environment
- Troubleshooting: Scikit-learn Module Not Found
- Best Practices
Step-by-Step Installing scikit-learn in a Virtual Environment
Step 1: Create a Virtual Environment
The first step is to create a virtual environment. To do this, you’ll need to have the
virtualenv package installed.
pip install virtualenv
Once you have
virtualenv installed, navigate to the directory where you want to create your virtual environment and run the following command:
This will create a new directory called
myenv, which contains a fresh Python installation and a
Step 2: Activate the Virtual Environment
To activate your virtual environment, navigate into the directory and run:
You should now see
(myenv) in your command prompt, indicating that you’re working in your virtual environment.
Step 3: Install Jupyter Notebook
With your virtual environment activated, you can now install Jupyter Notebook. To do this, run:
pip install jupyter
This will install Jupyter Notebook and its dependencies into your virtual environment.
Step 4: Install Scikit-learn
Next, you’ll need to install the scikit-learn module. To do this, run:
pip install scikit-learn
This will install the scikit-learn module and its dependencies into your virtual environment.
Step 5: Launch Jupyter Notebook
With Jupyter Notebook and scikit-learn installed, you can now launch Jupyter Notebook. To do this, run:
This will launch Jupyter Notebook in your default web browser. You can now create a new notebook and start working on your project.
Troubleshooting: Scikit-learn Module Not Found
If you encounter the error
ModuleNotFoundError: No module named 'sklearn', it’s likely that Jupyter Notebook is not running in your virtual environment. To fix this, you’ll need to install and enable the
pip install ipykernel
Next, you’ll need to install the kernel for your virtual environment.
python -m ipykernel install --user --name=myenv
This will install the kernel for your virtual environment, which you can now select when creating a new notebook in Jupyter Notebook.
Use Virtual Environments: Always work within a virtual environment to isolate your project dependencies and avoid conflicts with system-wide packages.
Kernel Awareness: Ensure that the Jupyter Notebook kernel is aware of the virtual environment by installing Jupyter within the environment.
Kernel Restart: If you encounter import errors, try restarting the Jupyter Notebook kernel after activating the virtual environment.
Use Requirements.txt: Maintain a
requirements.txtfile listing all project dependencies. This makes it easy to recreate the environment on another machine.
Running Jupyter Notebook in a virtual environment is essential for any data scientist or software engineer working on a project. By following these simple steps, you can create a virtual environment, install Jupyter Notebook and scikit-learn, and start working on your project with confidence. If you encounter the common error of a missing scikit-learn module, simply install and enable the
ipykernel package and install the kernel for your virtual environment.
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