Getting Started with Jupyter Notebooks

Jupyter notebooks are the standard tool for interactive data science work. They let you write code, see results immediately, add explanations, and share your analysis - all in one document. If you're learning Python or R for data work, you'll spend a lot of time in Jupyter.

What is a Jupyter Notebook?

A Jupyter notebook is an interactive document that combines:

• Code cells - Write and run Python or R code
• Output - See results, charts, and tables inline
• Markdown cells - Add formatted text, explanations, and documentation
• Rich media - Display images, HTML, and interactive widgets

The name "Jupyter" comes from Julia, Python, and R - the three languages it originally supported. Today it works with dozens of languages, but Python is most common.

Why Use Notebooks?

Exploratory analysis. When you're investigating data, you want to try things quickly and see results. Notebooks let you run code in chunks, inspect outputs, and iterate fast.

Documentation built-in. You can explain your thinking alongside your code. This makes notebooks great for sharing analysis with colleagues who want to understand your approach.

Visualization inline. Charts and plots appear right below the code that generated them. No switching between windows.

Reproducibility. A notebook captures your entire analysis workflow. Others can run it and get the same results.

Installing Jupyter

Option 1: With Anaconda (Recommended for beginners)

Anaconda includes Jupyter, Python, and common data science packages:

1. Download Anaconda from anaconda.com
2. Run the installer
3. Open Anaconda Navigator and launch Jupyter Notebook

Option 2: With pip

If you already have Python installed:

pip install jupyter

Then run:

jupyter notebook

Option 3: JupyterLab