About R

• interpreter and programming language
• manipulation, calculation, simulation, modelling, visualization of data
• free and open source
• thousands of packages to enhance the base functionality
• active online community
• good documentation
• widely used in science and business
• one of the fastest growing languages worldwide

Features

• read in data from various sources
  • text, images, geo, online-api, databases, excel, stata, spss, …
• processing, cleaning and aggregation of data
• statistical analysis, modelling and prediction
• visualization and presentation of results

RStudio

• integrated developement environment (IDE)
• integrated console, syntax-highlighting editor, project management, history, tools for plotting
• integrated documentation
• each data project can be run in its own environment with its own working directory

How to learn R

The best way to learn a tool is to use it. When you can’t figure out how to do something don’t give up. Continue to play with the program and search google for solutions. Any frustration you encounter will be worth it when you can bend your tool to your will!

Cole Nussbaumer Knaflic: “Storytelling with Data: A Data Visualization Guide for Business Professionals”.

Hot to get help

• work together, ask questions and help the people arround you
• use google and stackoverflow
• read books
• use the integrated help sites

Calling the R documentation

?mean
help(":")
?'?'
help.search("csv")
example("mean")
??plotting
example(plot)

Expressions and objects

• R takes user code (expressions), evaluates it [and prints the result]
• Interpreted language
• Expressions work on objects
  • Objects can be of different type
  • Objects can be assigned to a variable x <- 12

Functional programming in R

Everything that exists is an object. Everything that happens is a function call. — John Chambers

Functions and arguments:

fnname(arg1 = val1, arg2 = val2, ...)

• Functions “do” something with objects
• Input - Processing - Output
• A function is eventually called with arguments: rnorm(n = 10)
  • What is the actual and the formal argument?
  • R matches actual to formal arguments by position and/or name
  • Functions can have default aruments ?mean

The global environment

• The global environment contains all user defined objects (variables, functions, data) which were created during a session
• Use the ls() to list objects from the global environment
• Use the rm() to remove objects (e. g. to save memory if the object is very large)

vals <- 1:10
ls()

 [1] "addTwo"        "class"         "clean"         "colFilter"    
 [5] "countNA"       "f"             "file"          "files"        
 [9] "h"             "hello"         "i"             "l"            
[13] "m"             "mat"           "meanAge"       "model"        
[17] "month"         "myDF"          "mySum"         "new"          
[21] "numbers"       "oldest"        "pred"          "result"       
[25] "rowFilter"     "rSquared"      "semester"      "site"         
[29] "soccer"        "study"         "surv"          "survived_pred"
[33] "tab"           "titanic"       "val"           "vals"         
[37] "x"             "youngest"     

rm("vals")
ls()

 [1] "addTwo"        "class"         "clean"         "colFilter"    
 [5] "countNA"       "f"             "file"          "files"        
 [9] "h"             "hello"         "i"             "l"            
[13] "m"             "mat"           "meanAge"       "model"        
[17] "month"         "myDF"          "mySum"         "new"          
[21] "numbers"       "oldest"        "pred"          "result"       
[25] "rowFilter"     "rSquared"      "semester"      "site"         
[29] "soccer"        "study"         "surv"          "survived_pred"
[33] "tab"           "titanic"       "val"           "x"            
[37] "youngest"     

The working directory

• Each project has a root folder "./" which is the default working directory
• Use the function getwd() to see the current working directory
• If you move the project’s root folder to some other directory, the working directory is automatically set to this new directory

getwd()

File paths

• By using relative file paths one can easily share the project’s folder without rewriting the file paths
• "./" is the default working directory, e.g. the project’s root folder
• "../" moves one level up
• "~/" is the home directory of the current user

list.files("./") # same level as getwd() (e.g. the root folder of the project)
list.files("~/") # home directory
list.files("../") # move one level up (e.g. the desktop here)