Data Analysis with Open Source Tools

Real World Data Analysis shows you how you think about data and the results you want to achieve with it. Author Philipp Janert teaches you how to effectively approach data analysis problems, and how to extract all the available information from your data. This book shows you how to look at the results and know whether they're meaningful.

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Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.
* Use graphics to describe data with one, two, or dozens of variables * Develop conceptual models using back-of-the-envelope calculations, as well as scaling and probability arguments * Mine data with computationally intensive methods such as simulation and clustering * Make your conclusions understandable through reports, dashboards, and other metrics programs * Understand financial calculations, including the time-value of money * Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations * Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data." --Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists." --Michael E. Driscoll, CEO/Founder, Dataspora