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Python for Finance Cookbook

You're reading from   Python for Finance Cookbook Over 50 recipes for applying modern Python libraries to financial data analysis

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781789618518
Length 432 pages
Edition 1st Edition
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Author (1):
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Eryk Lewinson Eryk Lewinson
Author Profile Icon Eryk Lewinson
Eryk Lewinson
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Table of Contents (12) Chapters Close

Preface 1. Financial Data and Preprocessing 2. Technical Analysis in Python FREE CHAPTER 3. Time Series Modeling 4. Multi-Factor Models 5. Modeling Volatility with GARCH Class Models 6. Monte Carlo Simulations in Finance 7. Asset Allocation in Python 8. Identifying Credit Default with Machine Learning 9. Advanced Machine Learning Models in Finance 10. Deep Learning in Finance 11. Other Books You May Enjoy

Visualizing time series data

After learning how to download and preprocess financial data, it is time to learn how to plot it in a visually appealing way. We cover two approaches using the following:

  • The default plot method of a pandas DataFrame
  • A combination of the plotly and cufflinks libraries

The plotly library is built on top of d3.js (a JavaScript library used for creating interactive visualizations in web browsers) and is known for creating high-quality plots with a significant degree of interactivity (inspecting values of observations, viewing tooltips of a given point, zooming in, and so on). Plotly is also the company responsible for developing this library and provides hosting for our visualizations. We can create an infinite number of offline visualizations and up to 25 free ones to share online (with a limited number of views per day).

The cufflinks library also...

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