Jupyter Notebook Tutorial

What is Jupyter Notebook?

Jupyter Notebook is an interactive web-based environment for writing and running code, primarily used for data analysis, scientific computing, and machine learning. It allows you to:

Write and execute code in small chunks (cells)
See results immediately after each code execution
Mix code with text, images, and visualizations
Share your work easily with others

Installation

1Install Anaconda (Recommended for Beginners)

Anaconda includes Jupyter Notebook and many useful Python packages.

Go to https://www.anaconda.com/download
Download the installer for your operating system (Windows, Mac, or Linux)
Run the installer and follow the installation wizard
Accept the default settings

2Alternative: Install with pip

If you already have Python installed, you can install Jupyter using pip:

pip install notebook

🚀 Launching Jupyter Notebook

1Launch from Anaconda Navigator

Open Anaconda Navigator and click the "Launch" button under Jupyter Notebook.

2Launch from Command Line/Terminal

Open your terminal (or Anaconda Prompt on Windows) and type:

jupyter notebook

This will open Jupyter in your default web browser.

Tip

Navigate to the folder where you want to create notebooks before launching Jupyter. Use cd command to change directories.

🖥️ The Jupyter Interface

The dashboard shows:

Files tab: Browse your computer's files
Running tab: See currently open notebooks
New button: Create new notebooks or files

📝 Creating Your First Notebook

1Create a New Notebook

Click the "New" button in the top right
Select "Python 3" (or your preferred kernel)
A new notebook will open in a new browser tab

2Rename Your Notebook

Click on "Untitled" at the top and type a new name, then press Enter.

🔲 Understanding Cells

Notebooks are made up of cells. There are two main types:

1. Code Cells

Used for writing and executing Python code.

2. Markdown Cells

Used for writing formatted text, explanations, and documentation.

▶️ Running Cells

Three Ways to Run a Cell:

Shift + Enter: Run cell and move to the next cell
Ctrl + Enter: Run cell and stay on the same cell
Alt + Enter: Run cell and insert a new cell below

⚠️ Important

Cells can be run in any order, but variables from previous cells must be run first to be available in later cells.

⌨️ Essential Keyboard Shortcuts

Jupyter has two modes:

Edit Mode (Green border around cell)

You're typing inside a cell. Press Esc to exit.

Command Mode (Blue border around cell)

You're navigating between cells. Press Enter to edit a cell.

Shortcut	Action
Shift + Enter	Run cell and select below
Ctrl + Enter	Run cell
A (command mode)	Insert cell above
B (command mode)	Insert cell below
D D (press D twice)	Delete selected cell
M (command mode)	Change to markdown cell
Y (command mode)	Change to code cell
Ctrl + S	Save notebook
H (command mode)	Show all keyboard shortcuts

📊 Practical Example

✨ Advanced Features

Magic Commands

Special commands that start with %

%timeit sum(range(100))

%matplotlib inline

%pwd  # Print working directory

Tab Completion

Press Tab to autocomplete variable names and see available methods.

df.h  [Tab]

# Shows: head(), hist(), etc.

Help & Documentation

Add ? after a function to see its documentation.

print?

# Shows print function docs

Shell Commands

Run system commands with !

!pip install numpy

!ls  # List files

!pwd  # Print directory

💾 Saving and Sharing

1Auto-save

Jupyter auto-saves your work periodically. You'll see "Last Checkpoint" at the top.

2Manual Save

Press Ctrl + S or click the save icon.

3Export Formats

Go to File → Download as to export your notebook:

HTML: Share as a webpage
PDF: Print or share as document
Python (.py): Extract just the code
Markdown: Plain text with formatting

🎯 Best Practices

📝 Organization

Use markdown cells to explain what your code does
Break code into small, logical cells
Use descriptive variable names
Add comments in your code

🔄 Workflow

Run cells from top to bottom when starting
Restart kernel if variables get confusing: Kernel → Restart
Clear output regularly: Cell → All Output → Clear
Save frequently!

🐛 Debugging

If stuck, restart the kernel and run all cells
Check cell numbers - they show execution order
Use print() statements to debug
Read error messages carefully - they tell you what went wrong

🚨 Common Issues & Solutions

Problem	Solution
Cell shows [*] and won't finish	Interrupt the kernel: Kernel → Interrupt
Variables not found	Run previous cells that define those variables
Package not found	Install it: `!pip install package_name`
Notebook won't open	Check if Jupyter is running, restart the server
Changes not saving	Check "Last Checkpoint" time, manually save

🎓 Next Steps

Now that you know the basics, try these:

Practice: Create a notebook and experiment with Python code
Learn Libraries: Explore pandas, numpy, matplotlib
Try Projects: Analyze a dataset, create visualizations
Explore Extensions: Install Jupyter extensions for more features
JupyterLab: Try the next-generation interface with jupyter lab

📚 Additional Resources

Official Documentation: jupyter.org/documentation
Jupyter Shortcuts: Press H in command mode
Example Notebooks: github.com/jupyter/jupyter/wiki
Data Science Tutorials: kaggle.com/learn

🎉 You're Ready to Go!

Start experimenting with Jupyter Notebook and have fun coding!