Lab: Introduction to R

Basic Commands

Assigning

x <- c(1,3,2,5)
x

1. 1
2. 3
3. 2
4. 5

Concatenation

x = c(1,6,2)
x
y = c(1,4,3)

1. 1
2. 6
3. 2

Addition

length(x)
length(y)
x + y

3

3

1. 2
2. 10
3. 5

Managing namespace

ls()
rm(x, y)
ls()

1. 'x'
2. 'y'

It’s also possible to remove all objects at once:

rm(list=ls())

Matrices

?matrix

x = matrix(data=c(1,2,3,4), nrow=2, ncol=2)
x

A matrix: 2 × 2 of type dbl

1	3
2	4

x = matrix(c(1,2,3,4), 2, 2)

 matrix(c(1,2,3,4), 2, 2, byrow=TRUE)

A matrix: 2 × 2 of type dbl

1	2
3	4

sqrt(x)
x^2

A matrix: 2 × 2 of type dbl

1.000000	1.732051
1.414214	2.000000

A matrix: 2 × 2 of type dbl

1	9
4	16

x = rnorm(50)
y = x + rnorm(50, mean=50, sd=.1)
cor(x, y)

0.995246200573129

set.seed(1303)
rnorm(50) 

1. -1.14397631447974
2. 1.34212936561501
3. 2.18539047574276
4. 0.536392517923731
5. 0.0631929664685468
6. 0.502234482468979
7. -0.000416724686432643
8. 0.565819840539162
9. -0.572522688962623
10. -1.11022500727696
11. -0.0486871233624514
12. -0.695656217619366
13. 0.828917480303335
14. 0.206652855081802
15. -0.235674509102427
16. -0.556310491381104
17. -0.364754357080585
18. 0.862355034263622
19. -0.63077153536771
20. 0.313602125215739
21. -0.931495317661393
22. 0.823867618473952
23. 0.523370702077482
24. 0.706921411979056
25. 0.420204325601679
26. -0.269052154682033
27. -1.51031729990999
28. -0.69021247657504
29. -0.143471952443572
30. -1.0135274099044
31. 1.57327373614751
32. 0.0127465054882014
33. 0.872647049887217
34. 0.422066190530336
35. -0.0188157916578866
36. 2.61574896890584
37. -0.693140174826871
38. -0.266321780991085
39. -0.720636441231524
40. 1.36773420645149
41. 0.264007332160512
42. 0.632186807367191
43. -1.33065098578719
44. 0.0268888182209596
45. 1.0406363207788
46. 1.31202379854711
47. -0.0300020766733214
48. -0.250025712488174
49. 0.0234144856913592
50. 1.65987065574227

set.seed(3)
y = rnorm(100)
mean(y)
var(y)
sqrt(var(y))
sd(y)

0.0110355710943715

0.732867501277449

0.856076808047881

0.856076808047881

Graphics

x = rnorm(100)
y = rnorm(100)
plot(x, y)
plot(x, y, xlab="this is the x-axis",
ylab="this is the y-axis", main="Plot of X vs Y")

Saving figures

pdf("Figure.pdf")
plot(x, y, col="green")
dev.off()

pdf: 2

x = seq(1,10)
x
x = 1:10
x
x = seq(-pi, pi, length=50)

1. 1
2. 2
3. 3
4. 4
5. 5
6. 6
7. 7
8. 8
9. 9
10. 10

1. 1
2. 2
3. 3
4. 4
5. 5
6. 6
7. 7
8. 8
9. 9
10. 10

y = x
f = outer(x, y, function(x, y) {cos(y)/(1 + x^2)})
contour(x, y, f)
contour(x, y, f, nlevels=45, add=T)
fa = (f - t(f))/2
contour(x, y, fa, nlevels=15)

image(x, y, fa)
persp(x, y, fa)
persp(x, y, fa, theta=30)
persp(x, y, fa, theta=30, phi=20)
persp(x, y, fa, theta=30, phi=70)
persp(x, y, fa, theta=30, phi=40)

Indexing Data

A = matrix(1:16, 4, 4)

A[2,3]

10

A[c(1, 3), c(2, 4)]
A[1:3, 2:4]
A[1:2,]
A[,1:2]

A[1,]

1. 1
2. 5
3. 9
4. 13

A[-c(1,3),]
A[-c(1,3), -c(1,3,4)]

A matrix: 2 × 4 of type int

2	6	10	14
4	8	12	16

1. 6
2. 8

dim(A)

1. 4
2. 4

Loading Data

Auto = read.table("Auto.data")

Auto = read.table("Auto.data", header=T, na.strings="?")

Auto = read.csv("Auto.csv", header=T, na.strings="?")
dim(Auto)
Auto[1:4,]

Auto = na.omit(Auto)
dim(Auto)

1. 392
2. 9

names(Auto)

1. 'mpg'
2. 'cylinders'
3. 'displacement'
4. 'horsepower'
5. 'weight'
6. 'acceleration'
7. 'year'
8. 'origin'
9. 'name'

Additional Graphical and Numerical Summaries

plot(cylinders, mpg)

Error in plot(cylinders, mpg): object 'cylinders' not found
Traceback:

1. plot(cylinders, mpg)

plot(Auto$cylinders, Auto$mpg)
attach(Auto)
plot(cylinders, mpg)

cylinders = as.factor(cylinders)

plot(cylinders, mpg)
plot(cylinders, mpg, col="red")
plot(cylinders, mpg, col="red", varwidth=T)
plot(cylinders, mpg, col="red",
varwidth=T, horizontal=T)
plot(cylinders, mpg, col="red",
varwidth=T, xlab="cylinders", ylab="MPG")

hist(mpg)
hist(mpg, col=2)
hist(mpg, col=2, breaks=15)

pairs(Auto)
pairs(~ mpg + displacement + horsepower + weight + acceleration, Auto)

plot(horsepower, mpg)
identify(horsepower, mpg, name) 

summary(Auto)

      mpg          cylinders      displacement     horsepower        weight    
 Min.   : 9.00   Min.   :3.000   Min.   : 68.0   Min.   : 46.0   Min.   :1613  
 1st Qu.:17.00   1st Qu.:4.000   1st Qu.:105.0   1st Qu.: 75.0   1st Qu.:2225  
 Median :22.75   Median :4.000   Median :151.0   Median : 93.5   Median :2804  
 Mean   :23.45   Mean   :5.472   Mean   :194.4   Mean   :104.5   Mean   :2978  
 3rd Qu.:29.00   3rd Qu.:8.000   3rd Qu.:275.8   3rd Qu.:126.0   3rd Qu.:3615  
 Max.   :46.60   Max.   :8.000   Max.   :455.0   Max.   :230.0   Max.   :5140  
                                                                               
  acceleration        year           origin                      name    
 Min.   : 8.00   Min.   :70.00   Min.   :1.000   amc matador       :  5  
 1st Qu.:13.78   1st Qu.:73.00   1st Qu.:1.000   ford pinto        :  5  
 Median :15.50   Median :76.00   Median :1.000   toyota corolla    :  5  
 Mean   :15.54   Mean   :75.98   Mean   :1.577   amc gremlin       :  4  
 3rd Qu.:17.02   3rd Qu.:79.00   3rd Qu.:2.000   amc hornet        :  4  
 Max.   :24.80   Max.   :82.00   Max.   :3.000   chevrolet chevette:  4  
                                                 (Other)           :365  

summary(mpg)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   9.00   17.00   22.75   23.45   29.00   46.60