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Hands-On Data Analysis with Pandas

You're reading from   Hands-On Data Analysis with Pandas A Python data science handbook for data collection, wrangling, analysis, and visualization

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563452
Length 788 pages
Edition 2nd Edition
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Author (1):
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Stefanie Molin Stefanie Molin
Author Profile Icon Stefanie Molin
Stefanie Molin
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Getting Started with Pandas
2. Chapter 1: Introduction to Data Analysis FREE CHAPTER 3. Chapter 2: Working with Pandas DataFrames 4. Section 2: Using Pandas for Data Analysis
5. Chapter 3: Data Wrangling with Pandas 6. Chapter 4: Aggregating Pandas DataFrames 7. Chapter 5: Visualizing Data with Pandas and Matplotlib 8. Chapter 6: Plotting with Seaborn and Customization Techniques 9. Section 3: Applications – Real-World Analyses Using Pandas
10. Chapter 7: Financial Analysis – Bitcoin and the Stock Market 11. Chapter 8: Rule-Based Anomaly Detection 12. Section 4: Introduction to Machine Learning with Scikit-Learn
13. Chapter 9: Getting Started with Machine Learning in Python 14. Chapter 10: Making Better Predictions – Optimizing Models 15. Chapter 11: Machine Learning Anomaly Detection 16. Section 5: Additional Resources
17. Chapter 12: The Road Ahead 18. Solutions
19. Other Books You May Enjoy Appendix

Chapter materials

In this chapter, we will be working with three datasets. The first two come from data on wine quality that was donated to the UCI Machine Learning Data Repository (http://archive.ics.uci.edu/ml/index.php) by P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis, which contains information on the chemical properties of various wine samples, along with a rating of the quality from a blind tasting by a panel of wine experts. These files can be found in the data/ folder inside this chapter's folder in the GitHub repository (https://github.com/stefmolin/Hands-On-Data-Analysis-with-Pandas-2nd-edition/tree/master/ch_09) as winequality-red.csv and winequality-white.csv for red and white wine, respectively.

Our third dataset was collected using the Open Exoplanet Catalogue database, which can be found at https://github.com/OpenExoplanetCatalogue/open_exoplanet_catalogue/. This database provides data in eXtensible Markup Language (XML) format, which is similar to...

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