Installing Jupyter Notebook Beginner

Jupyter Notebook can be installed via pip or conda. This lesson covers installation methods, starting the server, navigating the interface, and setting up additional kernels.

Installing via pip

# Install Jupyter Notebook
pip install notebook

# Or install JupyterLab (includes Notebook)
pip install jupyterlab

# Verify installation
jupyter --version

Installing via conda

# Install with conda
conda install -c conda-forge notebook

# Or install JupyterLab
conda install -c conda-forge jupyterlab

# If using Anaconda, Jupyter is already included!

Starting the Server

# Start Jupyter Notebook
jupyter notebook

# Start on a specific port
jupyter notebook --port 8889

# Start without opening browser
jupyter notebook --no-browser

# Start JupyterLab instead
jupyter lab

The server starts and opens your default browser to http://localhost:8888. The terminal shows a URL with an authentication token.

Interface Overview

Dashboard (File Browser)

The dashboard is the landing page that shows your files and running notebooks:

• Files tab: Browse your filesystem, navigate directories, open or create notebooks
• Running tab: See all running notebooks and terminals, shut them down
• Clusters tab: Manage IPython parallel clusters (advanced)
• New button: Create a new notebook, text file, folder, or terminal

Notebook Editor

When you open a notebook, the editor provides:

• Menu bar: File, Edit, View, Insert, Cell, Kernel, Widgets, Help
• Toolbar: Quick-access buttons for save, add cell, run, stop, restart kernel
• Cell area: The main workspace where you write and execute code and text
• Kernel indicator: Shows the kernel status (idle, busy, disconnected)

Creating Kernels

Kernels are the computational engines that execute code in notebooks. Python is the default, but you can add others:

# List available kernels
jupyter kernelspec list

# Install IPython kernel for a specific environment
python -m ipykernel install --user --name myenv --display-name "Python (myenv)"

# Remove a kernel
jupyter kernelspec remove myenv

Installing Additional Kernels

Language	Kernel	Installation
R	IRkernel	R -e "install.packages('IRkernel'); IRkernel::installspec()"
Julia	IJulia	julia -e 'using Pkg; Pkg.add("IJulia")'
JavaScript	ijavascript	npm install -g ijavascript && ijsinstall
C++	xeus-cling	conda install -c conda-forge xeus-cling
Bash	bash_kernel	pip install bash_kernel && python -m bash_kernel.install

JupyterHub for Teams

JupyterHub is a multi-user version of Jupyter for teams and classrooms:

• Multi-user: Each user gets their own Jupyter server and workspace
• Authentication: Integrate with LDAP, OAuth, GitHub, or institutional SSO
• Resource management: Control CPU, memory, and GPU allocation per user
• Deployment: Run on Kubernetes (Zero to JupyterHub), bare metal, or cloud providers
• Use cases: University courses, corporate data science teams, research groups

# Install JupyterHub
pip install jupyterhub

# Start JupyterHub (requires admin privileges)
jupyterhub

# Generate a config file
jupyterhub --generate-config