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plot(cars)

# create vectors of data for three medical patients
presidents_name <- c("Jan Trump", "Roberto Carlos", "Juan Manuel")
presidents_salary <- c(98000, 95000, 100000)
application_status <- c(FALSE, FALSE, TRUE)

# access the second element in body president_name vector
presidents_name[2]

[1] "Roberto Carlos"

## [1] 98.6

# include items in the range 2 to 3
presidents_salary[2:3]

[1]  95000 100000

# exclude item 2 using the minus sign
presidents_name[-2]

[1] "Jan Trump"   "Juan Manuel"

# use a vector to indicate whether to include item
application_status[c(TRUE, TRUE, FALSE)]

[1] FALSE FALSE

#FACTORS

# add governemnt expendature factor
government_expendature <- factor(c("LOW", "MODERATE", "HIGH"),
                   levels = c("LOW", "MODERATE", "HIGH"),
                   ordered = TRUE)

government_expendature

[1] LOW      MODERATE HIGH    
Levels: LOW < MODERATE < HIGH

#Check for lower government_expendature than moderate
government_expendature < "MODERATE"

[1]  TRUE FALSE FALSE

presidents_salary[1]

[1] 98000

presidents_name[1]

[1] "Jan Trump"

application_status[1]

[1] FALSE

government_expendature [1]

[1] LOW
Levels: LOW < MODERATE < HIGH

#create a list for the presidency term
subject1 <- list(presidents_name = presidents_name[1], presidents_salary = presidents_salary[1],application_staus = application_status[1],
government_expendature = government_expendature[1])

subject1

$presidents_name
[1] "Jan Trump"

$presidents_salary
[1] 98000

$application_staus
[1] FALSE

$government_expendature
[1] LOW
Levels: LOW < MODERATE < HIGH

pt_data <- data.frame(presidents_name, presidents_salary, application_status, government_expendature, stringsAsFactors = FALSE)

# display the data frame
pt_data

# get a single column
pt_data$subject_name

NULL

# get several columns by specifying a vector of names
pt_data[c("presidents_name", "presidents_salary")]

#this is the same as above, extracting application_status and government_status
pt_data[1:2]

pt_data$presidents_name

[1] "Jan Trump"      "Roberto Carlos"
[3] "Juan Manuel"   

pt_data[(presidents_name),(government_expendature)]

pt_data[2:3] #just showing column 2 and 3

#accessing by row and column
pt_data[2,2]

[1] 95000

#accessing several rows and columns
pt_data [c(2,1),c(3,1)]

m1<-matrix(c(1,2,3,4),nrow=2)
m1

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

m2<-matrix(c(1,2,3,4),nrow=2)
m2

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

#extract first row first column
m1[1,1]

[1] 1

#extract second row ferst columns of m2
m2[1,2]

[1] 3

#creating a 2x3 matrix
m3 <- matrix(c(1,2,3,4,5,6), nrow = 2)
m3

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

m4<-matrix(c(2,3,7,9,11,10i),ncol = 2)
m4

     [,1]   [,2]
[1,] 2+0i  9+ 0i
[2,] 3+0i 11+ 0i
[3,] 7+0i  0+10i

#extract first row
m4[1,]

[1] 2+0i 9+0i

#extract every row in the second column
m4[,2]

[1]  9+ 0i 11+ 0i  0+10i