Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Learn Python by Building Data Science Applications

You're reading from  Learn Python by Building Data Science Applications

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Pages 482 pages
Edition 1st Edition
Languages
Authors (2):
Philipp Kats Philipp Kats
Profile icon Philipp Kats
David Katz David Katz
Profile icon David Katz
View More author details

Table of Contents (26) Chapters

Preface Section 1: Getting Started with Python
Preparing the Workspace First Steps in Coding - Variables and Data Types Functions Data Structures Loops and Other Compound Statements First Script – Geocoding with Web APIs Scraping Data from the Web with Beautiful Soup 4 Simulation with Classes and Inheritance Shell, Git, Conda, and More – at Your Command Section 2: Hands-On with Data
Python for Data Applications Data Cleaning and Manipulation Data Exploration and Visualization Training a Machine Learning Model Improving Your Model – Pipelines and Experiments Section 3: Moving to Production
Packaging and Testing with Poetry and PyTest Data Pipelines with Luigi Let's Build a Dashboard Serving Models with a RESTful API Serverless API Using Chalice Best Practices and Python Performance Assessments Other Books You May Enjoy

Big data visualization with datashader

Big data also needs to be visualized! Big data visualizations are somewhat rare; in part because they are hard to do, but also because they are hard to interpret and communicate insights. A big data visualization is usually either a network, a map, or a mapping (similarity-based, computed 2- or 3-dimensional distributions). They are usually astonishing and complex! In fact, a few early inventors of big data visualizations, such as Eric Fisher, became famous for their work with big data.

As we mentioned, big data visualizations are generally hard due to the mere size of the dataset. Standard tools won't work— for matplotlib, even with a raster engine, it will take hours to plot millions of points, and Altair won't do it at all. For a long time, there wasn't an easy solution to this problem. This changed with the announcement...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}