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Hands-On Exploratory Data Analysis with Python

You're reading from   Hands-On Exploratory Data Analysis with Python Perform EDA techniques to understand, summarize, and investigate your data

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789537253
Length 352 pages
Edition 1st Edition
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Authors (2):
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Suresh Kumar Mukhiya Suresh Kumar Mukhiya
Author Profile Icon Suresh Kumar Mukhiya
Suresh Kumar Mukhiya
Usman Ahmed Usman Ahmed
Author Profile Icon Usman Ahmed
Usman Ahmed
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Table of Contents (17) Chapters Close

Preface 1. Section 1: The Fundamentals of EDA
2. Exploratory Data Analysis Fundamentals FREE CHAPTER 3. Visual Aids for EDA 4. EDA with Personal Email 5. Data Transformation 6. Section 2: Descriptive Statistics
7. Descriptive Statistics 8. Grouping Datasets 9. Correlation 10. Time Series Analysis 11. Section 3: Model Development and Evaluation
12. Hypothesis Testing and Regression 13. Model Development and Evaluation 14. EDA on Wine Quality Data Analysis 15. Other Books You May Enjoy Appendix

Pie chart

This is one of the more interesting types of data visualization graphs. We say interesting not because it has a higher preference or higher illustrative capacity, but because it is one of the most argued-about types of visualization in research.

A paper by Ian Spence in 2005, No Humble Pie: The Origins and Usage of a Statistical Chart, argues that the pie chart fails to appeal to most experts. Despite similar studies, people have still chosen to use pie charts. There are several arguments given by communities for not adhering to the pie chart. One of the arguments is that human beings are naturally poor at distinguishing differences in slices of a circle at a glance. Another argument is that people tend to overestimate the size of obtuse angles. Similarly, people seem to underestimate the size of acute angles.

Having looked at the criticism, let's also have some...

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