Malte Grosser is a business mathematician from Hamburg, who has been programming in R regularly since the beginning of his career. He is currently finishing his PhD on machine learning for stroke outcome prediction and develops solutions in business as a data scientist.Henning Bumann is a psychologist and statistician who enjoys making sense of data and is motivated to build data-driven solutions that are beautiful and meaningful. He prefers free programming tools to support effective and transparent collaboration.Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science.

"I learned a lot working through their solutions — it's a great way to broaden and deepen your understanding of R. (I should probably go through it again...)"- Greg Wilson"Advance R Solutions is a great educational resource that I can recommend to my students. [. . . ] Advanced R, 2nd Edition and the new Advanced R Solutions constitute a dynamic duo for advancing my student’s knowledge in an orderly manner.[. . .] I would say that if you’re a data scientists who uses R, then Advanced R Solutions should be part of your professional library. Taking some time to explore the various solutions and expand on them with your own experiments, will only help you hone your skills and increase your knowledge. R is a great programming environment that I enjoy on a daily basis. Having yet another resource like this for deepening my knowledge can only lead to good things."– insideBIGDATA, Daniel D. Gutierrez

• Part I Foundations2. Names and values3. Vectors4. Subsetting5. Control Flow6. Functions7. Environments8. ConditionsPart II Funtional Programming9. Functionals10. Function Factories11. Function OperatorsPart III Object oriented programming13. S314. R615. S4Part IV Metaprogramming18. Expressions19. Quasiquotation20. Evaluation21. Translating R CodePart V Techniques23. Measuring Performance24. Improving Performance25. Rewriting R code in C++

Malte Grosser is a business mathematician from Hamburg, who has been programming in R regularly since the beginning of his career. He is currently finishing his PhD on machine learning for stroke outcome prediction and develops solutions in business as a data scientist.Henning Bumann is a psychologist and statistician who enjoys making sense of data and is motivated to build data-driven solutions that are beautiful and meaningful. He prefers free programming tools to support effective and transparent collaboration.Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science.

"I learned a lot working through their solutions — it's a great way to broaden and deepen your understanding of R. (I should probably go through it again...)"- Greg Wilson"Advance R Solutions is a great educational resource that I can recommend to my students. [. . . ] Advanced R, 2nd Edition and the new Advanced R Solutions constitute a dynamic duo for advancing my student’s knowledge in an orderly manner.[. . .] I would say that if you’re a data scientists who uses R, then Advanced R Solutions should be part of your professional library. Taking some time to explore the various solutions and expand on them with your own experiments, will only help you hone your skills and increase your knowledge. R is a great programming environment that I enjoy on a daily basis. Having yet another resource like this for deepening my knowledge can only lead to good things."– insideBIGDATA, Daniel D. Gutierrez

• Part I Foundations2. Names and values3. Vectors4. Subsetting5. Control Flow6. Functions7. Environments8. ConditionsPart II Funtional Programming9. Functionals10. Function Factories11. Function OperatorsPart III Object oriented programming13. S314. R615. S4Part IV Metaprogramming18. Expressions19. Quasiquotation20. Evaluation21. Translating R CodePart V Techniques23. Measuring Performance24. Improving Performance25. Rewriting R code in C++

Malte Grosser is a business mathematician from Hamburg, who has been programming in R regularly since the beginning of his career. He is currently finishing his PhD on machine learning for stroke outcome prediction and develops solutions in business as a data scientist.Henning Bumann is a psychologist and statistician who enjoys making sense of data and is motivated to build data-driven solutions that are beautiful and meaningful. He prefers free programming tools to support effective and transparent collaboration.Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science.

"I learned a lot working through their solutions — it's a great way to broaden and deepen your understanding of R. (I should probably go through it again...)"- Greg Wilson"Advance R Solutions is a great educational resource that I can recommend to my students. [. . . ] Advanced R, 2nd Edition and the new Advanced R Solutions constitute a dynamic duo for advancing my student’s knowledge in an orderly manner.[. . .] I would say that if you’re a data scientists who uses R, then Advanced R Solutions should be part of your professional library. Taking some time to explore the various solutions and expand on them with your own experiments, will only help you hone your skills and increase your knowledge. R is a great programming environment that I enjoy on a daily basis. Having yet another resource like this for deepening my knowledge can only lead to good things."– insideBIGDATA, Daniel D. Gutierrez

• Part I Foundations2. Names and values3. Vectors4. Subsetting5. Control Flow6. Functions7. Environments8. ConditionsPart II Funtional Programming9. Functionals10. Function Factories11. Function OperatorsPart III Object oriented programming13. S314. R615. S4Part IV Metaprogramming18. Expressions19. Quasiquotation20. Evaluation21. Translating R CodePart V Techniques23. Measuring Performance24. Improving Performance25. Rewriting R code in C++