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Hadley Wickham’s dplyr tutorial at useR! 2014, Part 2

·1 min
useR conference sessions Education R useR education tutorials dplyr
Author
Tim Phan

Part 2 of the dplyr tutorial is now available! Hadley will be covering Grouped Mutate/Filter, Joins, Do, and Databases. (You can find Part 1 of the tutorial here.)

For our viewers who have just discovered the wonders of R, keep in mind that this tutorial was filmed in early July of 2014. As R packages naturally update over time (well, depending on the programmers!), please make sure to check Hadley’s Githubfor the latest changes to the dplyr package.

If you have questions or comments about the tutorial, dplyr, or R, feel free to ask them here on the DSLA blog and we’ll do our best to address questions via comments. Don’t forget about Twitter and StackOverflow which are handy references as usual. Thanks for watching, and good luck!

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Hadley Wickham is hard at work, releasing packages which leverage the expressive power of R to keep easy things intuitive, and to make hard things possible. Having already developed a number of packages which address other steps in the data processing and analysis pipeline, he chose to address the process by which R developers ingest, manipulate, and transform data. This package, dplyr, is a narrowly focused library, designed to provide 90% of the functionality required in most data munging tasks. It may not solve every possible problem in data munging, but dplyr’s built in primitives will reduce your need to drop to “base R” for most common tasks. It does so by leveraging the magritr package’s “pipe” operator, and is inspired by dataflow programming constructs. It is fast, it is powerful, and it has been the single largest productivity boost that many of us here at DataScience.LA have adopted in 2014. In this video, Hadley provides a very quick introduction to the dplyr package, describing his philosophy behind the package’s design while providing a number of illustrative examples as to the flexibility, expressiveness, and power of this tool.