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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

Representing intervals of time using periods


It is often required to represent not just a specific time or sequence of timestamps, but to represent an interval of time using a start date and an end date (an example of this would be a financial quarter). This representation of a bounded interval of time can be represented in pandas using Period objects.

Period objects consist of a start time and an end time and are created from a start date with a given frequency. The start time is referred to as the anchor of the Period object, and the end time is then calculated from the start date and the period specification.

To demonstrate this, the following command creates a period representing a 1-month period anchored in August 2014:

In [22]:
   aug2014 = pd.Period('2014-08', freq='M')
   aug2014

Out[22]:
   Period('2014-08', 'M')

The Period function has start_time and end_time properties that inform us of the derived start and end times of Period:

In [23]:
   aug2014.start_time, aug2014.end_time...
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