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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

Using regular expressions

A regular expression, or regex, is a sequence of characters and special metacharacters used to match a set of character strings. Regular expressions allow you to be more expressive with string-matching operations than just providing a simple substring. You can think of it as a pattern that you want to match with strings of different lengths, made up of different characters.

In the str.contains() method, we supplied the regular expression, wigg|drew. In this case, the vertical bar | is a metacharacter that acts as the OR operator, so this regular expression matches any string that contains the substring wigg or drew.

Metacharacters let you change how you make matches. When you provide a regular expression that contains no metacharacters, it simply matches the exact substring. For instance, Wiggins would only match strings containing the exact substring...

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