2.2 Data Structure

Each object has a mode or type, e.g. numerical, character or logic and a class.

data frame is a structure.

Factors are nominal or ordinal variable, stored and treated specially.

2.2.1 vector

The data in one vector must be the same mode or type.



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a <- c(1, 2, 5, 3, -2, 6)
a



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a0 <- c(1, "one", TRUE)
print(a0)
class(a0)



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b <- c("one", "two", "three")
b



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c <- c(TRUE, FALSE, TRUE, TRUE)
c



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a[3]



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a[2:6]



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a[c(1, 3, 5)]



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c(2:6)

2.2.2 matrix



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y <- matrix(1:20, nrow = 4, ncol = 5)
y



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cells <- c(1, 26, 34, 28)
rname <- c("R1", "R2")
cname <- c("C1", "C2")
mymatrix <- matrix(cells, nrow = 2, ncol = 2, byrow = TRUE, dimnames = list(rname, cname))
mymatrix



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x <- matrix(1:10, nrow = 2)
x



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x[2,]



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x[,2]



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x[1, 4]



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x[1, c(4, 5)]

2.2.3 array



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dim1 <- c("A1", "A2")
dim2 <- c("B1", "B2", "B3")
dim3 <- c("C1", "C2", "C3", "C4")
z <- array(data = 1:24, dim = c(2, 3, 4), dimnames = list(dim1, dim2, dim3))
print(z)

2.2.4 dataframe



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patientID <- c(1, 2, 3, 4)
age <- c(25, 34, 28, 52)
diabetes <- c("Type1", "Type1", "Type2", "Type1")
status <- c("Poor", "Improved", "Excellent", "Poor")
patientdata <- data.frame(patientID, age, diabetes, status)
patientdata



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str(patientdata)



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patientdata[1:2]



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patientdata[c("diabetes", "status")]



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patientdata$age



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table(patientdata$diabetes, patientdata$status)

Attach, detach and with



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attach(mtcars)
summary(mpg)
plot(mpg, disp)
detach(mtcars)



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with(data = mtcars, {
    keepstats <<- summary(mpg)
    plot(mpg, disp)
}
)
print(keepstats)



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patientdata <- data.frame(age, diabetes, status, row.names = patientID)
patientdata

2.2.5 factors

Categorical "nominal" and ordered categorical data "ordinal"



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status <- c("Poor", "Improved", "Excellent", "Poor")
status <- factor(status, ordered = TRUE, levels = c("Poor", "Improved", "Excellent"))
str(status)



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patientdata$status <- status
str(patientdata)



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summary(patientdata)

2.2.6 lists



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g <- "My first list"
f <- c(25, 26, 18, 39)
j <- matrix(1:10, nrow = 5)
k <- c("one", "two", "three")
mylist <- list(title = g, ages = f, j, k)
mylist



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mylist[[2]]



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mylist[["ages"]]



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mylist$ages

List is important:

orgnize and recall disparate info in a simple way
many functions return list



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x <- c(8, 6, 4)
x[7] <- 10
x

Difference between R and other programming languages

. doesn't have special meanings in R, but $ is somewhat like the ..
R doesn't have multiline comments
Assigning to a non exist element of a vector/matrix/dataframe expnds the structure
R doesn't have scalar value, there are 1-d vector
Indices start from 1, not 0
Variable can't be declared, come into existence on the first assignment.

2.3.2 importing delimited text file



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grades <- read.csv(file = "studentgrades.txt", header = TRUE, sep = ",")



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grades



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str(grades)



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grades <- read.table(file = "studentgrades.txt", header = TRUE, sep = ",", row.names = "StudentID",
                    colClasses = c("character", "character", "character",
                                  "numeric", "numeric", "numeric"))



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grades



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str(grades)

2.4.2 Value labels



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gender <- c(1, 1, 2, 2, 1)
gender.factor <- factor(c("F", "F", "M", "M", "F"), ordered = TRUE, levels = c("F", "M"), labels = c("female", "male")) #
str(gender.factor)