Introduction to R for Data Science :: Session 1
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The document provides a comprehensive guide for data science lecturers on how to introduce R programming to students. It includes installation instructions for R and RStudio, an overview of the R ecosystem, and resources for further learning. It also outlines specific activities and datasets for initial sessions, emphasizing the importance of various R packages.
Introduction to R for Data Science :: Session 1
- 1. Introduction to R for Data Science Lecturers dipl. ing Branko Kovač Data Analyst at CUBE/Data Science Mentor at Springboard Institut za savremene nauke Data Science zajednica Srbije [email protected] dr Goran S. Milovanović Data Scientist at DiploFoundation Data Science zajednica Srbije [email protected] [email protected]
- 2. Step 1 • Install R • Install RStudio IDE Windows • R installation: https://cran.r-project.org/bin/windows/base/ • RStudio installation: https://www.rstudio.com/products/rstudio/download/ Ubuntu (14.04.1-3 and similar…) • R installation: https://www.digitalocean.com/community/tutorials/how-to-set-up-r-on- ubuntu-14-04 • Rstudio installation: https://www.rstudio.com/products/rstudio/download/ Intro to R for Data Science Session 1: Getting to know R
- 3. Intro to R for Data Science Session 1: Getting to know R Step 2 • Get to know your RStudio IDE…
- 4. Intro to R for Data Science Session 1: Getting to know R
- 5. Step 4 • Introducing the R ecosystem… • RStudio: Tools -> Install Packages Image source: The network structure of R packages on CRAN and BioConductor, Andrie de Vries & Joseph Rickert, Microsoft. Intro to R for Data Science Session 1: Getting to know R
- 6. CRAN: The Comprehensive R Archive Network Intro to R for Data Science Session 1: Getting to know R
- 7. Step 4 • Install something really useful, like: > install.packages(“ggplot2”); • NOTE: not all R packages are installed in this way; during the course we will learn about different installation approaches. > installed.packages() # alternative: > library() > .libPaths() > library(ggplot2); search(); # what is in the environment > old.packages(); # what is old? > update.packages(); # update everything (carefully!) Intro to R for Data Science Session 1: Getting to know R
- 8. Step 5 • Getting to know R! • Session 1 Script: IntroR_Session1.R • Data Set: rko_film_1930-1941.csv # data source: # http://www.stat.ufl.edu/~winner/datasets.html # an adaptation of the original .dat file Intro to R for Data Science Session 1: Getting to know R
- 9. Step 6 • Readings for Session 2: • The Art of R Programming, Norman Matloff, September 1, 2009: http://heather.cs.ucdavis.edu/~matloff/132/NSPpart.pdf Chapters 1 - 5 • Very useful: • Inside R: http://www.inside-r.org/ • Quick R: http://www.statmethods.net/ • R-bloggers: http://www.r-bloggers.com/ Intro to R for Data Science Session 1: Getting to know R