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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

Chapter 3. Reshaping, Reorganizing, and Aggregating

In the first two chapters, we gave you a general overview of pandas and examined some of the basics of the pandas DataFrame. Our coverage of the DataFrame was focused solely upon simple manipulation of a single DataFrame, such as adding and removing columns and rows, indexing the contents, selecting content, basic indexing, and performing simple arithmetic upon its data.

In this chapter, we will expand our scope of data operations on DataFrame objects to include more complex techniques of manipulating data and deriving results from grouped sets of financial data. The examples in this chapter will focus on retrieving, organizing, reshaping, and grouping/aggregating data to be able to perform basic statistical operations.

Specifically, in this chapter, we will cover the following topics:

  • Loading historical stock data from the Web or from files
  • Concatenating and merging stock price data along multiple axes
  • Merging data in multiple DataFrame...
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