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Mastering Pandas for Finance

You're reading from   Mastering Pandas for Finance Master pandas, an open source Python Data Analysis Library, for financial data analysis

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783985104
Length 298 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with pandas Using Wakari.io FREE CHAPTER 2. Introducing the Series and DataFrame 3. Reshaping, Reorganizing, and Aggregating 4. Time-series 5. Time-series Stock Data 6. Trading Using Google Trends 7. Algorithmic Trading 8. Working with Options 9. Portfolios and Risk Index

Summary

This chapter was a brief introduction to this book. You learned how to set up a Python environment in Wakari.io to be able to run the code samples provided throughout the text. This included instructions on how to update the default Wakari.io Python environment to support the required packages that are required for all of the examples in the remainder of the text.

In the next chapter, we will dive into using pandas and its core data structures, Series and DataFrame. These will be core to representing data in later chapters, where we primarily use pandas DataFrame objects to represent financial data, which we apply to various financial analyses.

You have been reading a chapter from
Mastering Pandas for Finance
Published in: May 2015
Publisher: Packt
ISBN-13: 9781783985104
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