Data Science Essentials in Python (Pragmatic Bookshelf)

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Dmitry Zinoviev @aqsaqal

Edited by Katharine Dvorak @katied

Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. This one-stop solution covers the essential data science you need in Python.

Access structured and unstructured text and numeric data from local files, databases, and the Internet. Arrange, rearrange, and clean the data. Work with relational and non-relational databases, data visualization, and simple predictive analysis—regressions, clustering, and decision trees. See how typical data analysis problems are handled. And try your hand at your own solutions to a variety of medium-scale projects.

Keep this handy quick guide at your side whether you’re a student, an entry-level data science professional converting from R to Python, or a seasoned Python developer who doesn’t want to memorize every function and option.

“Data Science Essentials in Python provides deep insights and the right set of tools and techniques to start with. Well-drafted examples and exercises make it practical and highly readable.”

–Lokesh Kumar Makani, CASB expert, Skyhigh Networks

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