# Installing IPython Notebook/Jupyter Server: A Beginner's Guide

In this tutorial, we will cover the basic features of Jupyter notebooks and introduce you to the IPython kernel using the classic Jupyter Notebook interface. If you're looking for something more modern or advanced, consider trying out JupyterLab instead.

## What is IPython?

IPython is an enhanced version of Python that includes several additional functionalities such as interactive shell, rich display system, and a variety of other features useful primarily for data science, but also generally in scientific computing. One of the most significant additions provided by IPCells (the execution environment within Jupyter Notebook) compared to regular ipython shells is their ability to be executed cell-by-cell rather than having to restart all kernel state after every single change.

## Installing and Running IPython

Before you can start using IPython, you will need to have it installed on your system. Luckily for everyone out there who doesn't want to waste time compiling anything themselves (although this option is always available), pre-compiled binaries are provided by Continuum Analytics under the MIT license at their website:

https://www.continuum.io/anaconda

Once downloaded and extracted into a directory of choice, simply run `./Anaconda3/bin/ipython` on Unix-like operating systems or double-clicking `Anaconda2\Scripts\ipython.exe`, depending on your version of Windows you're running from within the newly created Anaconda Python environment:

```bash

$ source ~/anaconda2/etc/profile.d/ipython.sh

```

For Mac OS X (and newer versions of Linux):

```bash

source ~//Anaconda3/bin/activate root

```

Then type `jupyter notebook` into your terminal or command prompt window:

```

$ jupyter notebook

```

This will start the IPython Notebook server on port 8888 by default. Open a web browser and navigate to http://localhost:8888?token=your_secret_token where 'your\_secret\_token' should be replaced with the string of characters displayed next to `Notebook password` in your terminal output:

!'IPython Notebooks Interface'(/path/to/ipynb.png)

## Basic IPython Notebook Features

### Cells

Cells are the building blocks of a Jupyter notebook. There are four types available: Markdown cells for plain text, code cells that can execute Python or other supported languages' code using various kernels (more on this later), and display data structures like tables, images etcetera.

- Markdown: This cell type allows you to write any valid markdown syntax directly into it which will be rendered as HTML when displayed in the notebook. Useful for adding headings, bold/italic text, links etc.

- Code : These cells can execute code written inside them using one of several supported languages depending on what kernel is being used (more below). The default language for new ipython kernels is Python.

### Kernel

The kernel is responsible for executing the code within a cell and sending back output to be displayed in the notebook. IPython comes with support for multiple programming languages out-of-the-box, including but not limited to:

- Python: This is the default language used by all newly created ipython kernels.

- R : Execute R code using r kernel.

### Cells within cells

You can nest other cell types inside of existing ones. For example, you could have a Markdown cell containing another Code cell that itself contains yet another set of nested cells!

And that's it! You now know how to install IPython Notebook and run your first Jupyter server using the classic interface. From here, feel free to experiment with all sorts of cool features like running multiple kernels at once or even creating custom kernels for languages not yet supported out-of-the-box.

Remember: if you encounter any issues during installation or usage, there are plenty of resources available online - including this very tutorial! Happy IPythoning!

Install ipython notebook jupyter server