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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
Languages
Tools
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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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Toc

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

Notebook setup


The workbook and examples will all require the following code to execute and format output. It is similar to the previous chapters but also includes matplotlib imports to support many of the graphics that will be created and some modifications to fit data to the page in the text:

In [1]:
   import pandas as pd
   import pandas.io.data
   import numpy as np
   import datetime
   import matplotlib.pyplot as plt
   %matplotlib inline

   pd.set_option('display.notebook_repr_html', False)
   pd.set_option('display.max_columns', 6)
   pd.set_option('display.max_rows', 10) 
   pd.set_option('display.width', 78) 
   pd.set_option('precision', 3)
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