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Data engineering and data shaping in Practical Data Science with R 2nd Edition

A kind reader recently shared the following comment on the Practical Data Science with R 2nd Edition live-site.

Thanks for the chapter on data frames and data.tables. It has helped me overcome an obstacle freeing me from a lot of warnings telling me my data table was not a real . It reduced the calculation time for a scenario in modelStudio from 30 minutes to 7 minutes. Following the advice in your book is helping me a lot with understanding R and the models you can create with R: Thanks

This is exactly what we were hoping for when we added Chapter 5 Data engineering and data shaping to the 2nd edition of the book. The chapter is organized by data manipulation task (what you are trying to do, or your sub-goal) and then teaches the mere methodology in base-R, data.table, and dplyr. The hope was: a Rosetta Stone of data manipulation solutions, that would help many readers- and not lock them into any one notation.

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Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.

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