Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Mastering Python Scientific Computing

You're reading from   Mastering Python Scientific Computing A complete guide for Python programmers to master scientific computing using Python APIs and tools

Arrow left icon
Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781783288823
Length 300 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
 Kumar Mehta Kumar Mehta
Author Profile Icon Kumar Mehta
Kumar Mehta
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. The Landscape of Scientific Computing – and Why Python? 2. A Deeper Dive into Scientific Workflows and the Ingredients of Scientific Computing Recipes FREE CHAPTER 3. Efficiently Fabricating and Managing Scientific Data 4. Scientific Computing APIs for Python 5. Performing Numerical Computing 6. Applying Python for Symbolic Computing 7. Data Analysis and Visualization 8. Parallel and Large-scale Scientific Computing 9. Revisiting Real-life Case Studies 10. Best Practices for Scientific Computing Index

Chapter 7. Data Analysis and Visualization

In this chapter, we will be discussing the concepts of data visualization, plotting, and interactive computing using matplotlib, pandas, and IPython. Data visualization is the process of presenting data in graphic or pictorial form. This will help understand information from data easily and quickly. By "plotting," we mean representing the dataset in the form of a graph to show the relationship between two or more variables. By "interactive computing," we mean the software that accepts input from the user. Generally, these are commands to be processed by the software. After accepting the input, the software performs processing as per the command entered by the user. These concepts will be accompanied by example programs.

In this chapter, we will be covering the following topics:

  • Concepts associated with plotting, using matplotlib
  • Types of the plots, using sample programs
  • The fundamental concepts of pandas
  • The pandas structures...
lock icon The rest of the chapter is locked
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Mastering Python Scientific Computing
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 $19.99/month. Cancel anytime
Modal Close icon
Modal Close icon