Skip to Content
Numerical Computing with Python
book

Numerical Computing with Python

by Pratap Dangeti, Allen Yu, Claire Chung, Aldrin Yim
December 2018
Beginner to intermediate
682 pages
18h 1m
English
Packt Publishing
Content preview from Numerical Computing with Python

Importing online financial data in the JSON format

In this chapter, we will also draw upon financial data from Quandl's API to create insightful visualizations. If you are not familiar with Quandl, it is a financial and economic data warehouse that stores millions of datasets from hundreds of publishers. The best thing about Quandl is that these datasets are delivered via the unified API, without worrying about the procedures to parse the data correctly. Anonymous users can get up to 50 API calls per day, and you get up to 500 free API calls if you are a registered user. Readers can sign up for a free API key at https://www.quandl.com/?modal=register.

At Quandl, every dataset is identified by a unique ID, as defined by the Quandl Code on ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Mastering Numerical Computing with NumPy

Mastering Numerical Computing with NumPy

Umit Mert Cakmak, Tiago Antao, Mert Cuhadaroglu

Publisher Resources

ISBN: 9781789953633OtherOtherErrata Page