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Pandas Cookbook

You're reading from   Pandas Cookbook Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781784393878
Length 532 pages
Edition 1st Edition
Languages
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Author (1):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
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Toc

Table of Contents (12) Chapters Close

Preface 1. Pandas Foundations FREE CHAPTER 2. Essential DataFrame Operations 3. Beginning Data Analysis 4. Selecting Subsets of Data 5. Boolean Indexing 6. Index Alignment 7. Grouping for Aggregation, Filtration, and Transformation 8. Restructuring Data into a Tidy Form 9. Combining Pandas Objects 10. Time Series Analysis 11. Visualization with Matplotlib, Pandas, and Seaborn

Getting started with matplotlib

For many data scientists, the vast majority of their plotting commands will come directly from pandas or seaborn, which both rely completely on matplotlib to do the actual plotting. However, neither pandas nor seaborn offers a complete replacement for matplotlib, and occasionally you will need to use it directly. For this reason, this recipe will offer a short introduction to the most crucial aspects of matplotlib.

Getting ready

Let's begin our introduction with a look at the anatomy of a matplotlib plot in the following figure:

Matplotlib uses a hierarchy of objects to display all of its plotting items in the output. This hierarchy is key to understanding everything about matplotlib....

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