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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

Moving windows


A number of functions are provided to compute moving (also known as rolling) statistics, where the function computes the statistic on a window of data represented by a particular period of time and then slides the window across the data by a specified interval, continually calculating the statistic as long as the window falls first within the dates of the time-series.

With the following functions, pandas provides direct support for rolling windows:

Function

Description

rolling_mean

This is the mean of the values in the window

rolling_std

This is the standard deviation of the values in the window

rolling_var

This is the variance of values

rolling_min

This is the minimum of the values in the window

rolling_max

This is maximum of the values in the window

rolling_cov

This is the covariance of values

rolling_quantile

This is the moving window score at the percentile/sample quantile

rolling_corr

This is the correlation of the values in the window

...
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