How to install Jupyter on Windows

This guideline intends to help students install Jupyter on their Windows PC in an easy way. Usually it is easier to troubleshoot problems when a UNIX system is used. Windows users may wish to install Windows Subsystem for Linux for these purposes. A guideline on how to do this will be added later.

windows 10


WSL - The Windows Subsystem for Linux is a virtual machine that runs within Windows and allows to setup Linux systems. It is far better integrated in Windows than traditional virtual machines.

windows 10

Python - Programming language created by Guido van Rossum. The syntax aims to be readable. Because a lot of science packages are available for Python, it is a popular language used by scientists in all kind of disciplines. The most notable of these packages are Pandas, Numpy and Scikit-learn.


Jupyter Notebook - This is one of the many IDE that are available for Python. Specific for Jupyter Notebooks is that you can create reports with it at ease, since you can combine code with text and images. These reports are stored as .ipynb files. Jupyter Lab is very alike Jupyter Notebook.


Anaconda (Miniconda) - As explained, Python has become one of the major programming languages because many packages are available. Anaconda allows to automate the installing of dependencies and the updating of packages. An additional advantage of Anaconda is that it will create its own virtual environment and hence will not mess with any system-installed Python version. Miniconda is just like Anaconda, but with less packages pre-installed.


Numpy - Python package that provides convenient functions that deal with (multi-dimensional) arrays.


Pandas - Python package that provides convenient functions that deal with tabular data. Largest difference with Numpy is that it allows to have indices on the axis.


Scikit-learn - Python package that allows to do machine learning.


Step 1: Make sure Windows is up-to-date.

Go to Windows Update and make sure all updates are installed. At the bottom of the Windows Update page, you can check your OS build and System Info. Make sure that you are on Build 18362 or higher.

Step 2: Enable Windows Features

Go to Control Panel (e.g. by typing control panel in start menu) -> Programs -> Turn Windows features on or off -> Enable "Windows Subsystem for Linux" and "Virtual Machine Platform".

Step 3: Restart your machine

Step 4: Download Linux kernel update package

Download this file and execute it. Approve elevated permissions.

Step 5: Enable WSL 2

Altough this step is not mandatory, it is wise to work on the latest version of WSL 2. Open Command Prompt and type "wsl --set-default-version 2" and enter.

Set WSL2 as default

Step 6: Download Ubuntu

Open Microsoft Store, search for Ubuntu and install it. Otherwise, open this link and install it.

Step 7: Create default UNIX user account

Launch the just installed app (Search in start menu for Ubuntu). It will now load Ubuntu; this can take a while. When this is done, you will be asked to create a username and password. There is no need for very sophisticated password, but please remember it! Note: When typing your password, you will not see any character appearing. This is normal and everything works alright. End with an enter.

Step 8: Install Miniconda

Now Ubuntu is installed, it is time to update some packages and install Python! Start by downloading Miniconda and install this. You can do this by the following commands, which can be launched in the terminal you obtained from the previous step. You can re-open this terminal anytime by launching the Ubuntu app. When a program is asking for permission, type 'y' or 'yes' and enter. When asking for installation location, just type enter.

sudo apt update
sudo apt upgrade
conda init
Please close and reopen Ubuntu after this step.

Step 9: Install some packages

You are likely to use some frequently used packages. With the following command, you will install some frequently used ones.

conda install -y jupyterlab pandas scikit-learn numpy seaborn nodejs

Step 10: Run jupyterlab

You should now be able to run jupyter lab or notebook! Just type `jupyter lab` or `jupyter notebook`. A URL will display in the terminal, which you can copy paste into a browser. Usually it is something like http://localhost:8888/lab?token=***

Open browser at specific port

Step 11: Create a new jupyter notebook

Navigate to the folder where you want to create the notebook. Create the new notebook. A new file with the extension .ipynb should be added. Open this notebook by clicking on it.

create a new ipynb notebook

Step 12: Try

You can now run Python in the Jupyter Notebook! Play around a little. Try some additions (3+3) and check the result by executing the cell (can be done with shift enter). If at this stage you get a Kernel Error, close Jupyter Notebook (both the browser and terminal) and reopen it with administrator rights.

some example in jupyter notebook

Step 13: Do your research!

Now you are suited with all tools necessary to do your research. As an example, you can download here some simple machine learning on sales data from the DSPM course. Save the .ipynb file to a file path to your choice. You can then start Jupyter Notebook and open the notebook file.

Download Example Jupyter Notebook on Machine Learning