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Jupyter Cookbook

Jupyter Cookbook

By : Toomey
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Jupyter Cookbook

Jupyter Cookbook

1 (1)
By: Toomey

Overview of this book

Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it.
Table of Contents (12 chapters)
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To get the most out of this book

This book is focused on using Jupyter as a platform for data science. It assumes that you have a good understanding of data science concepts and are looking to use Jupyter as your presentation platform.

Download the example code files

You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packtpub.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub ahttps://github.com/PacktPublishing/Jupyter-Cookbook. If there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "This script loads in RDatasets (this contains several standard datasets commonly used in data science)."

A block of code is set as follows:

Pkg.add("RDatasets")
using RDatasets
describe(dataset("datasets", "iris"))

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

var msg = "Hello, World"
console.log(msg)

Any command-line input or output is written as follows:

python2 -m pip install ipykernel 
python2 -m ipykernel install --user

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Once you select the Install button, Anaconda will automatically install R in your environment."

Warnings or important notes appear like this.
Tips and tricks appear like this.

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