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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]
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
Intro to R for Data Science
Session 1: Getting to know R
Step 2
• Get to know your RStudio IDE…
Intro to R for Data Science
Session 1: Getting to know R
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
CRAN: The Comprehensive R Archive Network
Intro to R for Data Science
Session 1: Getting to know R
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
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
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
![Introduction to R for Data Science :: Session 6 [Linear Regression in R]](https://img.pdfslide.net/doc/110x75/587b2bd91a28ab057d8b52ab/introduction-to-r-for-data-science-session-6-linear-regression-in-r.jpg)
