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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

In this chapter, we briefly overviewed the pandas Series and DataFrame objects, how they are used to represent data, and how to select data in both via queries, columns, and indices. The concept of reindexing both classes of objects is also introduced, and as we get into the later chapters, it will be common to perform reindexing of time-series data.

In the next chapter, we will examine indexing in more depth with an eye towards how performing various aggregations of data can derive results from the information represented in pandas. As we progress into more specific financial analysis, this combination of reindexing and aggregation will form the basis of much of the analysis performed later in the book.

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