In [2]:

    

x=c(2,7,5)


    

In [3]:

    

x


    

    
Out[3]:





	
2
	
7
	
5

In [4]:

    

seq(from=4, length=3, by=3)


    

    
Out[4]:





	
4
	
7
	
10

In [5]:

    

y=seq(from=4, length=3, by=3)


    

In [7]:

    

x+y


    

    
Out[7]:





	
6
	
14
	
15

In [8]:

    

x*y


    

    
Out[8]:





	
8
	
49
	
50

In [9]:

    

x^y


    

    
Out[9]:





	
16
	
823543
	
9765625

In [10]:

    

x[2] # second element of x


    

    
Out[10]:




7

In [12]:

    

x[2:3] # all elements from the second, up to and including the third element


    

    
Out[12]:





	
7
	
5

In [15]:

    

x[-2] # all elements, except for the second one


    

    
Out[15]:





	
2
	
5

In [17]:

    

x[-c(1,2)] # all elements, except for the first and second one


    

    
Out[17]:




5

In [21]:

    

z = matrix(seq(1,12), 4, 3) # matrix with 4 rows and 3 columns


    

In [22]:

    

z


    

    
Out[22]:






	
1
5
9
	
 2
 6
10
	
 3
 7
11
	
 4
 8
12

In [23]:

    

z[3:4, 2:3] # show rows 3 to 4, and cols 2 to 3


    

    
Out[23]:






	
 7
11
	
 8
12

In [25]:

    

z[,2:3] # show all rows, but only cols 2 to 3


    

    
Out[25]:






	
5
9
	
 6
10
	
 7
11
	
 8
12

In [31]:

    

z[,1] # first col only, by default converted into a vector


    

    
Out[31]:





	
1
	
2
	
3
	
4

In [33]:

    

z[,1, drop=FALSE] # first col only, keep it as a matrix


    

    
Out[33]:






	
1
	
2
	
3
	
4

In [34]:

    

dim(z)


    

    
Out[34]:





	
4
	
3

In [35]:

    

ls() # known variables in your namespace(s)


    

    
Out[35]:





	
'x'
	
'y'
	
'z'

In [36]:

    

rm(y) # remove a variable


    

In [37]:

    

ls()


    

    
Out[37]:





	
'x'
	
'z'

In [40]:

    

x=runif(50) # 50 random uniform numbers between 0 and 1


    

In [42]:

    

y=rnorm(50) # 50 random normal vars between 0 and 1


    

In [44]:

    

plot(x,y)


    

In [48]:

    

# change plotting character / color; add axis labels
plot(x,y,xlab='Random Uniform', ylab='Random Normal', pch='*', col='blue')


    

In [52]:

    

# par() sets global plotting params
# mfrow: plot with 2 rows and 1 col
par(mfrow = c(2,1))


    

In [53]:

    

plot(x,y)
hist(y)


    

In [54]:

    

# reset plot command
par(mfrow = c(1,1))


    

In [55]:

    

ls()


    

    
Out[55]:





	
'x'
	
'y'
	
'z'

In [58]:

    

Auto=read.csv('data/Auto.csv')


    

In [60]:

    

head(Auto)


    

    
Out[60]:





mpg
cylinders
displacement
horsepower
weight
acceleration
year
origin
name

	
1
18
8
307
130
3504
12
70
1
chevrolet chevelle malibu
	
2
15
8
350
165
3693
11.5
70
1
buick skylark 320
	
3
18
8
318
150
3436
11
70
1
plymouth satellite
	
4
16
8
304
150
3433
12
70
1
amc rebel sst
	
5
17
8
302
140
3449
10.5
70
1
ford torino
	
6
15
8
429
198
4341
10
70
1
ford galaxie 500

In [61]:

    

names(Auto)


    

    
Out[61]:





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

In [62]:

    

dim(Auto)


    

    
Out[62]:





	
397
	
9

In [63]:

    

class(Auto)


    

    
Out[63]:




'data.frame'

In [64]:

    

summary(Auto)


    

    
Out[64]:





      mpg          cylinders      displacement     horsepower      weight    
 Min.   : 9.00   Min.   :3.000   Min.   : 68.0   150    : 22   Min.   :1613  
 1st Qu.:17.50   1st Qu.:4.000   1st Qu.:104.0   90     : 20   1st Qu.:2223  
 Median :23.00   Median :4.000   Median :146.0   88     : 19   Median :2800  
 Mean   :23.52   Mean   :5.458   Mean   :193.5   110    : 18   Mean   :2970  
 3rd Qu.:29.00   3rd Qu.:8.000   3rd Qu.:262.0   100    : 17   3rd Qu.:3609  
 Max.   :46.60   Max.   :8.000   Max.   :455.0   75     : 14   Max.   :5140  
                                                 (Other):287                 
  acceleration        year           origin                  name    
 Min.   : 8.00   Min.   :70.00   Min.   :1.000   ford pinto    :  6  
 1st Qu.:13.80   1st Qu.:73.00   1st Qu.:1.000   amc matador   :  5  
 Median :15.50   Median :76.00   Median :1.000   ford maverick :  5  
 Mean   :15.56   Mean   :75.99   Mean   :1.574   toyota corolla:  5  
 3rd Qu.:17.10   3rd Qu.:79.00   3rd Qu.:2.000   amc gremlin   :  4  
 Max.   :24.80   Max.   :82.00   Max.   :3.000   amc hornet    :  4  
                                                 (Other)       :368  

In [67]:

    

plot(Auto$cylinders, Auto$mpg)


    

In [69]:

    

# attributes can be a abbreviated
# plot(Auto$cyl, Auto$mpg)


    

In [73]:

    

attach(Auto) # put column header names into current namespace


    

    




The following objects are masked from Auto (pos = 3):

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

In [74]:

    

search()


    

    
Out[74]:





	
'.GlobalEnv'
	
'Auto'
	
'Auto'
	
'package:stats'
	
'package:graphics'
	
'package:grDevices'
	
'package:utils'
	
'package:datasets'
	
'package:methods'
	
'Autoloads'
	
'package:base'

In [96]:

    

par(mfrow = c(2,2))
plot(cylinders)
hist(cylinders)
plot(as.factor(cylinders), main="Factors of cylinders")
plot(as.factor(cylinders), mpg, main="Boxplot: cyl. vs. mpg",
     xlab="cylinders", ylab="mpg")