- Paperback: 298 pages
- Publisher: Packt Publishing Limited (May 25, 2015)
- Language: English
- ISBN-10: 1783985100
- ISBN-13: 978-1783985104
- Product Dimensions: 7.5 x 0.7 x 9.2 inches
- Shipping Weight: 649 g
- Average Customer Review: Be the first to review this item
- Amazon Best Sellers Rank: #33.703 in Books (See Top 100 in Books)
Mastering pandas for Finance Paperback – 25 May 2015
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About the Author
Michael Heydt is an independent consultant, educator, and trainer with nearly 30 years of professional software development experience, during which time, he focused on Agile software design and implementation using advanced technologies in multiple verticals, including media, finance, energy, and healthcare. He holds an MS degree in mathematics and computer science from Drexel University and an executive master's of technology management degree from the University of Pennsylvania's School of Engineering and Wharton Business School. His studies and research have focused on technology management, software engineering, entrepreneurship, information retrieval, data sciences, and computational finance. Since 2005, he has specialized in building energy and financial trading systems for major investment banks on Wall Street and for several global energy-trading companies, utilizing .NET, C#, WPF, TPL, DataFlow, Python, R, Mono, iOS, and Android. His current interests include creating seamless applications using desktop, mobile, and wearable technologies, which utilize high-concurrency, high-availability, and real-time data analytics; augmented and virtual reality; cloud services; messaging; computer vision; natural user interfaces; and software-defined networks. He is the author of numerous technology articles, papers, and books. He is a frequent speaker at .NET user groups and various mobile and cloud conferences, and he regularly delivers webinars and conducts training courses on emerging and advanced technologies. To know more about Michael, visit his website at http://bseamless.com/.
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Most helpful customer reviews on Amazon.com
That said, if you dug around the internet, you could probably cobble these examples together. Also, it doesn't really go into either pandas or finance too deeply. I don't hold those against the book - it can't be all things to all people. The book makes for a nice overview of the relevant topics - but expect an overview.
Note: I was asked to give a review of the book by the publisher in exchange for a free ebook (I purchased the book from the publisher).
Wakari.io - a collaborative data analytics platform that allows to explore data and create analytic scripts in collaboration with IPython Notebooks.
Introduction to the Series and DataFrame objects
A chapter on Reshaping, Reorganizing, and Aggregating Data
Correlations of Google trends with stock movements, creating algorithmic trading systems
Calculating options payoffs, prices, and behaviors
Constructing an efficient portfolio
An overview of modern portfolio theory and Computing Value at Risk (VaR)
I liked that the provided code is in the form of ipython notebook.
Disclaimer: I received this eBook as a complementary copy.