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

Product type Paperback

Published in Apr 2021

Publisher Packt

ISBN-13 9781800563452

Length 788 pages

Edition 2nd Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Stefanie Molin

View More author details

Table of Contents (21) Chapters

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

An introduction to matplotlib

The plotting capabilities in pandas and seaborn are powered by matplotlib: both of these packages provide wrappers around the lower-level functionality in matplotlib. Consequently, we have many visualization options at our fingertips with minimal code to write; however, this comes at a price: reduced flexibility in what we can create.

We may find that the pandas or seaborn implementation isn't quite meeting our needs, and, indeed, it may be impossible to override a particular setting after creating the plot with them, meaning we will have to do some of the legwork with matplotlib. Additionally, many of the tweaks that will be made to the final appearance of the visualization will be handled with matplotlib commands, which we will discuss in the next chapter. Therefore, it would greatly benefit us to have some understanding of how matplotlib works.