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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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Toc

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

Customizing visualizations

So far, all of the code we've learned for creating data visualizations has been for making the visualization itself. Now that we have a strong foundation, we are ready to learn how to add reference lines, control colors and textures, and include annotations.

In the 3-customizing_visualizations.ipynb notebook, let's handle our imports and read in the Facebook stock prices and earthquake datasets:

>>> %matplotlib inline
>>> import matplotlib.pyplot as plt
>>> import pandas as pd
>>> fb = pd.read_csv(
...     'data/fb_stock_prices_2018.csv', 
...     index_col='date', 
...     parse_dates=True
... )
>>> quakes = pd.read_csv('data/earthquakes.csv')

Tip

Changing the style in which the plots are created is an easy way to change their look and feel without setting each aspect separately. To set...

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