Book Image

Jupyter Cookbook

By : Dan Toomey
Book Image

Jupyter Cookbook

By: Dan 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 (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Accessing a database


Much information is available over the internet, but some of the more sensitive or private information is available in corporate and government databases only. Fortunately, many of the languages in Jupyter provide mechanisms to access data from a database.

For this example, we will be using R for scripting. R has a database connection library, dbplyr, that can be used to access some of the more common databases. As with the file loads elsewhere in this chapter, the result of a database read would be a DataFrame. Once there, you can operate on the DataFrame like any other.

Some of the other Jupyter languages have database support through a library as well. In particular, Python and Scala have database access. In general, they work in the same manner:

  1. Make a connection to the database
  2. Run a query on the database that returns a result set
  3. The library converts the result set into a usable data type for the language

Note: some libraries allow you to work as much as possible on...