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Learning the Pandas Library: Python Tools for Data Munging, Analysis, and Visual

✍ Scribed by Matt Harrison; Michael Prentiss


Publisher
Createspace Independent Publishing Platform
Year
2016
Tongue
English
Leaves
208
Edition
Paperback
Category
Library

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✦ Synopsis


Python is one of the top 3 tools that Data Scientists use.One of the tools in their arsenal is the Pandas library.This tool is popular because it gives you so much functionality out of the box.In addition, you can use all the power of Python to make the hard stuff easy!

Learning the Pandas Libraryis designed to bring developers and aspiring data scientists who are anxious to learn Pandas up to speed quickly. It starts with the fundamentals of the data structures. Then, it covers the essential functionality. It includes many examples, graphics, code samples, and plots from real world examples.

The Content Covers:


Installation Data Structures Series CRUD Series Indexing Series Methods Series Plotting Series Examples DataFrame Methods DataFrame Statistics Grouping, Pivoting, and Reshaping Dealing with Missing Data Joining DataFrames DataFrame ExamplesPreliminary ReviewsThis is anexcellent introduction benefitting from clear writing and simple examples. The pandas documentation itself is large and sometimes assumes too much knowledge, in my opinion. Learning the Pandas Library bridges this gap for new users and even for those with some pandas experience such as me.

-Garry C.

I have finished readingLearning the Pandas Libraryand I liked it... very useful and helpful tips even for people who use pandas regularly.

-Tom Z.

✦ Table of Contents


From the Author......Page 4
Introduction......Page 5
Installation......Page 8
Data Structures......Page 11
Series......Page 14
Series CRUD......Page 22
Series Indexing......Page 29
Series Methods......Page 39
Series Plotting......Page 72
Another Series Example......Page 80
DataFrames......Page 91
Data Frame Example......Page 98
Data Frame Methods......Page 112
Data Frame Statistics......Page 131
Grouping, Pivoting, and Reshaping......Page 139
Dealing With Missing Data......Page 155
Joining Data Frames......Page 162
Avalanche Analysis and Plotting......Page 168
Summary......Page 199
About the Author......Page 200
Also Available......Page 201
One more thing......Page 207


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