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A Very Short Introduction to R

Apr 23, 2024, 3 min read

A (very) short introduction to R

Original material by Paul Torfs & Claudia Brauer.

R is for statistical computing and graphics, and iti s a public domain (GNU) project.

To set the working directory: setwd("/Users/pietra/etc").

To check the installed packages: library() in the console.

  • To install: install.packages("geometry").
  • We then load: library("geometry").

To remove all variables from memory: rm(list=ls()).

To define a vector we use c meaning concatenate: b=c(3,4,5).

  • rnorm(): creates random samples from a normal distribution.
    • rnorm(10, mean=1.2, sd=3.4).

We can then do something like:

x = rnorm(100)
plot(x)

In doubt, we can do help(rnorm) or even example(rnorm).

  • CTRL+SHIFT+S runs the whole script, whereas CTRL+ENTER runs a line.

Vectors

WE INDEX FROM 1, NOT 0!!!

  • To construct: vec1 = c(1,4,5,8,10).
    • Alternatively: vec1 = seq(from=0, to=1, by=0.25).
  • To change a value: vec1[3] = 12.
  • We can then do things like: sum(vec1).

Matrices

2-d vectors.

  • To construct: mat=matrix(data=c(9,2,3,4,5,6),ncol=3).
    • Can also specify nrow.
    • We get:
[,1][,2][,3]
[1,]935
[2,]246

Some operations are:

  • Address an element: mat[1,2].
  • Select a whole row: mat[2,].
  • Function example: mean(mat).

Data frames

A matrix with names above the columns.

> t = data.frame(x = c(11,12,14), y = c(19,20,21), z = c(10,9,7))
 
> t
  x y z
 11 19 10
 12 20 9
 14 21 7
 
> mean(t$z)
8.666667
 
> mean(t[["z"]])
8.66666

List

The “columns” don’t need to be of the same length, unlike matrices and data frames.

> L = list(one=1, two=c(1,2), five=seq(0, 1, length=5))
 
> L
$one
1
$two
1 2
$five
0.00 0.25 0.50 0.75 1.00
 
> names(L)
"one" "two" "five"
> L$five + 10
10.00 10.25 10.50 10.75 11.00

Graphics

x1 = rnorm(100)
x2 = rnorm(100)
x3 = rnorm(100)
 
t = data.frame(a=x1, b=x1+x2, c=x1+x2+x3)
 
plot(t$a, type="l", ylim=range(t), lwd=3, col=rgb(1,0,0,0.3))
lines(t$b, type="s", lwd=2, col=rgb(0.3,0.4,0.3,0.9))
points(t$c, pch=20, cex=4, col=rgb(0,0,1,0.3))
  • ylim=range(t): sets the y-axis limit to the range of values in the entire data frame t, ensuring the entire plot is visible.
  • lwd=3: sets the line width to 3.
  • pch=20: sets the type of points to solid circles.
  • cex=4: scales the size of the points by a factor of 4.

Reading and writing data files

d = data.frame(a =c(3,4,5), b = c(12,32,54))
write.table(d, file="test.txt", row.names=FALSE)
d2 = read.table(file="test.txt", header=TRUE)

Dates

  • Use strptime:
date1 = strptime(c("20100225230000", "20100226000000"), format="%Y%m%d%H%M%S")

Programming tools

If-statements

w = 3
 
if ( w<5 ) 
{
    d = 2
}
else 
{
    d = 10
}
 
d

Shorter method:

a = c(1,2,3,4)
b = c(5,6,7,8)
f = a[b==5 | b==9]
f
1 4

For-loop

h = seq(from=1, to=8)
s = c()
 
for (i in 2:10)
{
    s[i] = h[i] * 10
}
 
s
NA 20 30 40 50 60 70 80 NA NA

Functions

fun1 = function(arg1, arg2)
{
    w = arg1 ^ 2
    return (arg2 + w)
}
 
fun1(arg1=3, arg2=5)
14

Data Processing

  • seq: create a vector with equal steps between the numbers.
  • rnorm: create a vector with random numbers with normal distribution (other distributions are also available).
  • sort: sort elements in increasing order.
  • t: transpose a matrix.
  • aggregate(x,by=ls(y),FUN="mean"): split data set x into subsets (defined by y) and com- putes means of the subsets. Result: a new list.
  • na.approx: interpolate (in zoo package). Argument: vector with NAs. Result: vector without NAs.
  • cumsum: cumulative sum. Result is a vector.
  • rollmean: moving average (in the zoo package).
  • paste: paste character strings together.
  • substr: extract part of a character string.

Graph View

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