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Python is a general purpose programming language that is popular with data scientists. It is free, as are a number of open-source libraries help acquire, organize, and process information. This book is designed for beginners to data analysis and covers the basics of Python data analysis programming and statistics. The book covers the Python fundamentals that are necessary to data analysis, including objects, functions, modules, and libraries. The libraries that are integral to data science are explored and explained, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib.
The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
The remainder of the book provides examples and tips and tricks for doing interesting things with data analysis programming. The topics are arranged into the following parts:
PART I: Getting to know Pythonís Data Science Toolkit
PART II: Playing with Data and Basic Stats
PART III: Taming the Data with Pandas, and a Little with Words
PART IV: Popular Topics in Data Science
Part V: The Part of Tens
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Publisher: Wiley/For Dummies
Page Count (est.): 432
Pub Date: 4/21/2014