Lab: Introduction to R

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

[1] 1 3 2 5

x = c(1,6,2)
x

[1] 1 6 2

y = c(1,4,3)
length (x)

[1] 3

length (y)

[1] 3

x+y

[1]  2 10  5

ls()

[1] "A"    "Auto" "f"    "fa"   "x"    "y"   

rm(x,y)
character (0)

character(0)

rm(list=ls())
?matrix
x=matrix (data=c(1,2,3,4) , nrow=2, ncol =2)
x

     [,1] [,2]
[1,]    1    3
[2,]    2    4

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

     [,1] [,2]
[1,]    1    2
[2,]    3    4

sqrt(x)

         [,1]     [,2]
[1,] 1.000000 1.732051
[2,] 1.414214 2.000000

x^2

     [,1] [,2]
[1,]    1    9
[2,]    4   16

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

[1] 0.995529

set.seed (1303)
rnorm (50)

 [1] -1.1439763145  1.3421293656  2.1853904757  0.5363925179  0.0631929665  0.5022344825 -0.0004167247
 [8]  0.5658198405 -0.5725226890 -1.1102250073 -0.0486871234 -0.6956562176  0.8289174803  0.2066528551
[15] -0.2356745091 -0.5563104914 -0.3647543571  0.8623550343 -0.6307715354  0.3136021252 -0.9314953177
[22]  0.8238676185  0.5233707021  0.7069214120  0.4202043256 -0.2690521547 -1.5103172999 -0.6902124766
[29] -0.1434719524 -1.0135274099  1.5732737361  0.0127465055  0.8726470499  0.4220661905 -0.0188157917
[36]  2.6157489689 -0.6931401748 -0.2663217810 -0.7206364412  1.3677342065  0.2640073322  0.6321868074
[43] -1.3306509858  0.0268888182  1.0406363208  1.3120237985 -0.0300020767 -0.2500257125  0.0234144857
[50]  1.6598706557

set.seed (3)
y=rnorm (100)
mean(y)

[1] 0.01103557

var(y)

[1] 0.7328675

sqrt(var(y))

[1] 0.8560768

sd(y)

[1] 0.8560768

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")
pdf (" Figure .pdf ")

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

png 
  2 

x=seq (1 ,10)
x

 [1]  1  2  3  4  5  6  7  8  9 10

x=1:10
x

 [1]  1  2  3  4  5  6  7  8  9 10

x=seq(-pi ,pi ,length =50)
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)

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

     [,1] [,2] [,3] [,4]
[1,]    1    5    9   13
[2,]    2    6   10   14
[3,]    3    7   11   15
[4,]    4    8   12   16

A[2,3]

[1] 10

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

     [,1] [,2]
[1,]    5   13
[2,]    7   15

A[1:3 ,2:4]

     [,1] [,2] [,3]
[1,]    5    9   13
[2,]    6   10   14
[3,]    7   11   15

A[1:2 ,]

     [,1] [,2] [,3] [,4]
[1,]    1    5    9   13
[2,]    2    6   10   14

A[ ,1:2]

     [,1] [,2]
[1,]    1    5
[2,]    2    6
[3,]    3    7
[4,]    4    8

A[1,]

[1]  1  5  9 13

A[-c(1,3) ,]

     [,1] [,2] [,3] [,4]
[1,]    2    6   10   14
[2,]    4    8   12   16

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

[1] 6 8

dim(A)

[1] 4 4

#Auto=read.table ("Auto.data ")
#fix(Auto)
#Auto=read.table ("Auto.data", header =T,na.strings ="?")
#fix(Auto)
#Auto=read.csv (" Auto.csv", header =T,na.strings ="?")
#fix(Auto)
dim(Auto)

[1] 392   9

Auto [1:4 ,]

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

[1] 392   9

names(Auto)

[1] "mpg"          "cylinders"    "displacement" "horsepower"   "weight"       "acceleration" "year"        
[8] "origin"       "name"        

plot(cylinders , mpg)

plot(Auto$cylinders , Auto$mpg )

attach (Auto)

The following objects are masked from Auto (pos = 4):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 33):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 34):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 35):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 36):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 37):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following object is masked from package:ggplot2:

    mpg

The following objects are masked from Auto (pos = 46):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

The following objects are masked from Auto (pos = 48):

    acceleration, cylinders, displacement, horsepower, mpg, name, origin, weight, year

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)

integer(0)

summary (Auto)

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