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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

EDA with Personal Email

The exploration of useful insights from a dataset requires a great deal of thought and a high level of experience and practice. The more you deal with different types of datasets, the more experience you gain in understanding the types of insights that can be mined. For example, if you have worked with text datasets, you will discover that you can mine a lot of keywords, patterns, and phrases. Similarly, if you have worked with time-series datasets, then you will understand that you can mine patterns relevant to weeks, months, and seasons. The point here is that the more you practice, the better you become at understanding the types of insights that can be pulled and the types of visualizations that can be done. Having said that, in this chapter, we are going to use one of our own email datasets and perform exploratory data analysis (EDA).

You will learn...

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