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Numerical Computing with Python

You're reading from Numerical Computing with Python Harness the power of Python to analyze and find hidden patterns in the data

Product type Course

Published in Dec 2018

Publisher Packt

ISBN-13 9781789953633

Length 682 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Mining

Authors (5):

Pratap Dangeti

Theodore Petrou

Allen Yu

Aldrin Yim

Claire Chung

+1 more

View More author details

Table of Contents (21) Chapters

Title Page

Contributors

About Packt

Preface

1. Journey from Statistics to Machine Learning FREE CHAPTER

2. Tree-Based Machine Learning Models

3. K-Nearest Neighbors and Naive Bayes

4. Unsupervised Learning

5. Reinforcement Learning

6. Hello Plotting World!

7. Visualizing Online Data

8. Visualizing Multivariate Data

9. Adding Interactivity and Animating Plots

10. Selecting Subsets of Data

11. Boolean Indexing

12. Index Alignment

13. Grouping for Aggregation, Filtration, and Transformation

14. Restructuring Data into a Tidy Form

15. Combining Pandas Objects

1. Other Books You May Enjoy

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Index

Three-dimensional (3D) plots

By transitioning to the three-dimensional space, you may enjoy greater creative freedom when creating visualizations. The extra dimension can also accommodate more information in a single plot. However, some may argue that 3D is nothing more than a visual gimmick when projected to a 2D surface (such as paper) as it would obfuscate the interpretation of data points.

In Matplotlib version 2, despite significant developments in the 3D API, annoying bugs or glitches still exist. We will discuss some workarounds toward the end of this chapter. More powerful Python 3D visualization packages do exist (such as MayaVi2, Plotly, and VisPy), but it's good to use Matplotlib's 3D plotting functions if you want to use the same package for both 2D and 3D plots, or you would like to maintain the aesthetics of its 2D plots.

For the most part, 3D plots in Matplotlib have similar structures to 2D plots. As such, we will not go through every 3D plot type in this section. We will put...

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Authors (5)

Pratap Dangeti

Pratap Dangeti

Pratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics and data science. He received his master's degree from IIT Bombay in its industrial engineering and operations research program. He is an artificial intelligence enthusiast. When not working, he likes to read about next-gen technologies and innovative methodologies.

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Aldrin Yim

Aldrin Yim

Aldrin Yim is a PhD candidate and Markey Scholar in the Computation and System Biology program at Washington University, School of Medicine. His research focuses on applying big data analytics and machine learning approaches in studying neurological diseases and cancer. He is also the founding CEO of Codex Genetics Limited, which provides precision medicine solutions to patients and hospitals in Asia.

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Claire Chung

Claire Chung

Claire Chung is pursuing her PhD degree as a Bioinformatician at the Chinese University of Hong Kong. She enjoys using Python daily for work and lifehack. While passionate in science, her challenge-loving character motivates her to go beyond data analytics. She has participated in web development projects, as well as developed skills in graphic design and multilingual translation. She led the Campus Network Support Team in college, and shared her experience in data visualization in PyCon HK 2017.

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Allen Yu

Allen Yu

Allen Yu, PhD, is a Chevening Scholar, 2017-18, and an MSC student in computer science at the University of Oxford. He holds a PhD degree in Biochemistry from the Chinese University of Hong Kong, and he has used Python and Matplotlib extensively during his 10 years of bioinformatics experience. Apart from academic research, Allen is the co-founder of Codex Genetics Limited, which aims to provide a personalized medicine service in Asia through the use of the latest genomics technology.

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Theodore Petrou

Theodore Petrou

Theodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science challenges at the Dunder Data website.

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