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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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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

The roots of pandas lay in analyzing financial time series data. The author, Wes McKinney, was not satisfied with the available Python tools at that time, and decided to build pandas to support his own needs at the hedge fund he was working at. Broadly speaking, time series are simply points of data gathered over time. Most typically, the time is evenly spaced between each data point. Pandas has excellent functionality with regards to manipulating dates, aggregating over different time periods, sampling different periods of time, and much more.

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