If you are a Python programmer who wants to get started with performing data analysis using pandas and Python, this is the book for you. Some experience with statistical analysis would be helpful but is not mandatory.
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Michael Heydt is an independent consultant, educator, and trainer with nearly 30 years of professional software development experience, during which 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 been specializing 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, 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 (Instant Lucene.NET, Learning pandas). He is a frequent speaker at .NET users' groups and various mobile and cloud conferences, and he regularly delivers webinars on advanced technologies.
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