Programming for Data Analytics
Programming and Data Science with R
This page contains resources for programming and performing data analysis with R for people with varying levels experience. Some of the resources focus more on general programming while others focus on statistical modeling/machine learning and text mining.
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An Introduction to Statistical Learning with Applications in R. Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
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Applied Predictive Modeling. Max Kuhn and Kjell Johnson. Great applied book with lots of examples written in R using Max Kuhn's caret package
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Advanced R by Hadley Wickham. Incredible resource for R programming.
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All the amazing books freely available from Roger Peng’s website: R programming for Data science, Exploratory Data Analysis with R, Report Writing for Data Science with R, and the Art of Data Science.
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Text mining with R: A tidy approach by Julia Silge and David Robinson. Great introduction to working with text data with R.
The books from Roger Peng’s website form a great introduction to programming for data science with R. The books from Hadley Wickham and Garrett Grolemund are more advanced but indispensable for practitioners with R looking to become experts.
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