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.
An Introduction to Statistical Learning with Applications in R. Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
Applied Predictive Modeling. Max Kuhn and Kjell Johnson. Great applied book with lots of examples written in R using Max Kuhn's caret package
Advanced R by Hadley Wickham. Incredible resource for R programming.
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.
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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