Mastering pandas for Finance: Master pandas, an open source Python Data Analysis Library, for financial data analysis

Michael Heydt

ISBN 10: 1783985100 / ISBN 13: 9781783985104

Published by Packt Publishing, 2015

About this Item

A tight, bright, and clean copy with no inscriptions and no annotations/notes. No creasing to spine/cover or foxing to pages. Fantastic condition book. 275pp. (19x23.5cm). Please contact us for any more information.

Seller Inventory # 7524

Bibliographic Details

• Title: Mastering pandas for Finance: Master pandas, an open source Python Data Analysis Library, for financial data analysis
• Publisher: Packt Publishing
• Publication Date: 2015
• Language: English
• ISBN 10: 1783985100
• ISBN 13: 9781783985104
• Binding: Soft cover
• Edition: 1st Edition
• Condition: Fine
• Seller catalogs:
  • Computing
  • Technology

About this title

Synopsis

If you are interested in quantitative finance, financial modelling, trading, or simply want to learn Python and pandas for finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed, but the book reviews financial pandas concepts. Interest in financial concepts is helpful, but no prior knowledge is expected.

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/.