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Essential Statistics for Non-STEM Data Analysts

You're reading from   Essential Statistics for Non-STEM Data Analysts Get to grips with the statistics and math knowledge needed to enter the world of data science with Python

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781838984847
Length 392 pages
Edition 1st Edition
Languages
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Author (1):
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Rongpeng Li Rongpeng Li
Author Profile Icon Rongpeng Li
Rongpeng Li
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Getting Started with Statistics for Data Science
2. Chapter 1: Fundamentals of Data Collection, Cleaning, and Preprocessing FREE CHAPTER 3. Chapter 2: Essential Statistics for Data Assessment 4. Chapter 3: Visualization with Statistical Graphs 5. Section 2: Essentials of Statistical Analysis
6. Chapter 4: Sampling and Inferential Statistics 7. Chapter 5: Common Probability Distributions 8. Chapter 6: Parametric Estimation 9. Chapter 7: Statistical Hypothesis Testing 10. Section 3: Statistics for Machine Learning
11. Chapter 8: Statistics for Regression 12. Chapter 9: Statistics for Classification 13. Chapter 10: Statistics for Tree-Based Methods 14. Chapter 11: Statistics for Ensemble Methods 15. Section 4: Appendix
16. Chapter 12: A Collection of Best Practices 17. Chapter 13: Exercises and Projects 18. Other Books You May Enjoy

Advanced visualization customization

In this section, you are going to learn how to customize the plots from two perspectives, the geometry and the aesthetics. You will see examples and understand how the customization works.

Customizing the geometry

There isn't enough time nor space to cover every detail of geometry customization. Let's learn by understanding and following examples instead.

Example 1 – axis-sharing and subplots

Continuing from the previous example, let's say you want the birth rate and the population change to be plotted on the same graph. However, the numerical values of the two quantities are drastically different, making the birth rate basically indistinguishable. There are two ways to solve this issue. Let's look at each of the ways individually.

Axis-sharing

We can make use of both the left-hand y axis and the right-hand Y axis to represent different scales. The following code snippet copies the axes with the twinx...

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