Data, graphics, and programming in R

28.1, 30.1, 2-4.2

Daily:10:00-12:45 & 13:45-16:30 EXCEPT WED 4 th 9:00-11:45 & 12:45-15:30 Teacher: Anna Kuparinen

Course program

• Wed – Basics of R (AM & PM) • Fri – Datasets in R (AM), graphics (PM) • Mon – Statistical tests and linear models (AM), more graphics (PM) • Tue – Basics of programming (AM), generalized linear models (PM) • Wed – Mixed models (AM), working with own data (PM) Teaching based on short lectures, demos, and exercises

Course material

• Lectures, demo codes, exercises, and other material can be found by following the course link in www.mv.helsinki.fi/home/akuparin/R_course.htm

• Other R material (e.g. downloading R) http://www.r-project.org/

How to get most out of the course?

• Do notes –also comment your own solution codes for the exercises • Be active –ask questions, ask clarification, ask to slow down • In the evenings, re-read the materials of the day • Start to use R immediately after the course

What is ?

• R is a software that provides a very handy environment and a large collection of tools for – Exploring and editing data – Computations, calculations, numerical mathematics – Statistical analyses – Producing graphics – Programming • R is a freeware program • R is developed by its users, i.e. anyone can write their own R extensions and share them with other users through R web – New methods are quickly implemented to R – There is a large variety of tools available

R work space Notepad or R script

Getting started

Write code first here!

Then copy-paste to R.

How to use R?

• R is a text-based interface, i.e. commands are given by text lines – > one should remember at least most common text commands • In practice, commands are typically written in an editor program and them copy-pasted to R – Notepad, R script, Tinn-R… – Commenting the code is highly recommended!

• R is based on objects and functions – Objects can be variables, lists, data frames… – Functions are made to carry out specific operations – Functions are stored in “library packages” • R stores objects and commands on workspace – Workspace and command history can be saved and loaded later on – Large objects reserve a lot of memory in the workspace

First commands

• Write your command on a command line > 2+3 • Then press enter [1] 5 • R returns the value

Placing a value to a variable

• Write your command on a command line > a=2+3 • Then press enter > • R does not return the value, but it has saved it to variable a

Operators in R

= places a value (<- would also work) == checks identity of values on the left and on the right side An command A=4/9 sets a value 4/9 to a variable called A. An command A==4/9 checks if A equals to 4/9 or not. The command returns a logical value TRUE or FALSE >= larger or of equal size <= smaller or of equal size DEMO 1

Vector

Length of this vector is 4.

1st element       2.3

6.8

1.1

4.9

      4th element

Vectors in R

• Generic way of creating a vector > a=c(2.3,6.8,1.1,4.9) • Pointing to a vector element > a[1] [1] 2.3

• Or several elements > a[c(1,3)] [1] 2.3 1.1

• Any calculations such as + or exp() can be applied to vectors.

1st column

Matrix

A matrix element is pointed by its row and column number: A[2,4]=-2.2

1st row

A

      2.3

5 7 1 8 3.3

0  1  9 14 5.4

3.8

7.66

 2.2

7.2

    8.2

Size of this matrix is 4 X 4

Matrix in R

• Generic way of creating a matrix > a=matrix(c(2,5,6,1),nrow=2,ncol=2,byrow=T) > a [,1] [,2] [1,] 2 5 [2,] 6 1 > a[1,] [1] 2 5 > a[,2] [1] 5 1

Tools to create vectors and matrixes

• Tools to create vectors A = c(1.0,5.8,9.0) A = 1:6 A = rep(1,9) A = rep(c(1,2),4) A = rep(c(1,2),each=4) A = seq(1,10,by=0.2) A = seq(1,10,length.out=57) • Creating matrixes B = matrix(1,nrow=8,ncol=9) B = matrix(0,nrow=9,ncol=4) -> DEMO 2

R as a calculator

• Basic math operators in R: +, -, /, *, ^ • Matrix calculations: – transpose matrixes by t() – Matrix calculations specified with %: for example * multiplies by elements, and %*% is for multiplication of matrixes • Basic mathematical functions: – log, exp, sqrt, cos, sin, tan, abs

etc

• Rounding: round, floor, ceiling

Anatomy of an R function

Object=function

(

parameters

)

OBJECT RETURNED BY THE FUNCTION NAME OF THE FUNCTION PARAMETER VALUES AND SETTINGS: not all have to be defined (see help files for the defaults)

Help in R

• Many ways to find help: – In R directly: ?

”name of the function” or help.search

(“keyword”) e.g. ?rep or help.search

(“vector”) – From R web pages – For more advanced problems also from R discussion groups – > DEMO 3