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...
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Transcript of 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...
![Page 1: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/1.jpg)
Data, graphics, and programming in R
28.1, 30.1, 2-4.2
Daily:10:00-12:45 & 13:45-16:30EXCEPT WED 4th 9:00-11:45 & 12:45-15:30
Teacher: Anna Kuparinen
![Page 2: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/2.jpg)
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
![Page 3: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/3.jpg)
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/
![Page 4: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/4.jpg)
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
![Page 5: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/5.jpg)
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
![Page 6: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/6.jpg)
Getting started
R work space
Notepad
or R script
Write code first here!
Then copy-paste to R.
![Page 7: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/7.jpg)
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
![Page 8: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/8.jpg)
First commands
• Write your command on a command line
> 2+3
• Then press enter
[1] 5
• R returns the value
![Page 9: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/9.jpg)
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
![Page 10: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/10.jpg)
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
![Page 11: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/11.jpg)
Vector
2.3
6.8
1.1
4.9
Length of this vector is 4.
1st element
4th element
![Page 12: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/12.jpg)
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.
![Page 13: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/13.jpg)
Matrix
2.3 8 9 7.66
5 3.3 14 2.2
7 0 5.4 7.2
1 1 3.8 8.2
A
1st column
1st row
A matrix element is pointed by its row and column number:
A[2,4]=-2.2
Size of this matrix is 4 X 4
![Page 14: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/14.jpg)
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
![Page 15: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/15.jpg)
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
![Page 16: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/16.jpg)
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
![Page 17: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/17.jpg)
Anatomy of an R function
Object=function(parameters)
PARAMETER VALUES AND SETTINGS:
not all have to be defined
(see help files for the defaults)NAME OF THE
FUNCTION
OBJECT RETURNED BY THE FUNCTION
![Page 18: 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.](https://reader035.fdocuments.us/reader035/viewer/2022080902/56649e625503460f94b5e8ea/html5/thumbnails/18.jpg)
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