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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
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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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Table of Contents (12) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 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

Introduction

All the datasets used in the preceding chapters have not had much or any work done to change their structure. We immediately began processing the datasets in their original shape. Many datasets in the wild will need a significant amount of restructuring before commencing a more detailed analysis. In some cases, an entire project might only be concerned with formatting the data in such a way that it can be easily processed by someone else.

There are many terms that are used to describe the process of data restructuring, with tidy data being the most common to data scientists. Tidy data is a term coined by Hadley Wickham to describe a form of data that makes analysis easy to do. This chapter will cover many ideas formulated by Hadley and how to accomplish them with pandas. To learn a great deal more about tidy data, read Hadley's paper (http://vita.had.co.nz/papers...

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