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Learning Pandas

You're reading from Learning Pandas Get to grips with pandas - a versatile and high-performance Python library for data manipulation, analysis, and discovery

Product type Paperback

Published in Apr 2015

Publisher Packt

ISBN-13 9781783985128

Length 504 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Author (1):

Michael Heydt

View More author details

Table of Contents (14) Chapters

Preface

1. A Tour of pandas

2. Installing pandas FREE CHAPTER

3. NumPy for pandas

4. The pandas Series Object

5. The pandas DataFrame Object

6. Accessing Data

7. Tidying Up Your Data

8. Combining and Reshaping Data

9. Grouping and Aggregating Data

10. Time-series Data

11. Visualization

12. Applications to Finance

Index

Running a small pandas sample in IPython

Now that Python and pandas is installed, let's write our first pandas application. We will write it in the IPython interpreter. IPython is an alternative shell for executing Python applications, and it conveniently provides numeric sequence numbers for thin input and output for example purposes. This is convenient for matching specific code examples in the book and will be used in all examples.

Note

IPython or IPython Notebooks will be the tools for all remaining examples in the book.

IPython is started using the ipython command from the shell or command line:

Michaels-MacBook-Pro:~ michaelheydt$ ipython
Python 2.7.8 |Anaconda 2.1.0 (x86_64)| (default, Aug 21 2014, 15:21:46) 
Type "copyright", "credits" or "license" for more information.

IPython 2.2.0 -- An enhanced Interactive Python.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://binstar.org
?         ...

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Learning Pandas

You have been reading a chapter from

Learning Pandas

Published in: Apr 2015

Publisher: Packt

ISBN-13: 9781783985128

© 2015 Packt Publishing Limited All Rights Reserved

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Authors (1)

Michael Heydt

Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.

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