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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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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

Introduction

It is important to consider the steps that you, as an analyst, take when you first encounter a dataset after importing it into your workspace as a DataFrame. Is there a set of tasks that you usually undertake to first examine the data? Are you aware of all the possible data types? This chapter begins by covering the tasks you might want to undertake when first encountering a new dataseset. The chapter proceeds by answering common questions that are not that trivial to do in pandas.

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