Book Image

Learning Jupyter

By : Dan Toomey
Book Image

Learning Jupyter

By: Dan Toomey

Overview of this book

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we’ll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.
Table of Contents (16 chapters)
Learning Jupyter
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Node.js JSON handling


In this example, we will load a JSON dataset and perform some standard manipulations of the data. I am referencing the list of Ford models from http://www.carqueryapi.com/api/0.3/?callback=?&cmd=getModels&make=ford . I could not reference this directly as it is not a flat file but an API call. So, I downloaded the data into a local file, fords.json. Also, the output from the API call wraps the JSON like ?(json); which would have to be removed before parsing.

The scripting we will use is as follows. In the script, JSON is a built-in package of Node.js so we can reference this package directly. The JSON package provides many of the standard tools that you need to handle your JSON files and objects.

Of interest here is the JSON file reader that constructs a standard JavaScript array of objects. Attributes of each object can be referenced by name, for example, model.model_name. We can see this feature in action with this script that reads in a JSON file and parses...