R data structures

Vectors

# create vectors of data for three medical patients
subject_name <- c("Joe Doe", "Mary Doe", "Steve Stevens")
temperature <- c(97.1, 96.1, 100.2)
flu_status <- c(FALSE, FALSE, TRUE)

# access the second element in the body temperature vector
temperature[2]

[1] 96.1

# access the third element in the body subject_name vector
subject_name[2]

[1] "Mary Doe"

Examples of accessing items in vectors

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

[1]  96.1 100.2

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

[1]  97.1 100.2

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

[1]  97.1  96.1 100.2

Factors

# add a gender factor
gender <- factor(c("MALE", "FEMALE", "MALE"))
gender

[1] MALE   FEMALE MALE  
Levels: FEMALE MALE

# add a blood type factor
blood <- factor(c("O", "A", "AB"),
                levels = c("A", "B", "AB", "O"))
blood

[1] O  A  AB
Levels: A B AB O

#Add ordered factor
symptoms <- factor(c("SEVERE", "MILD", "MODERATE"),
                   levels = c("MILD", "MODERATE", "SEVERE"),
                   ordered = TRUE)
symptoms

[1] SEVERE   MILD     MODERATE
Levels: MILD < MODERATE < SEVERE

# check for symptoms greater than moderate
symptoms > "MODERATE"

[1]  TRUE FALSE FALSE

Lists

# display information for a patient
subject_name[1]

[1] "Joe Doe"

temperature[1]

[1] 97.1

flu_status[1]

[1] FALSE

gender[1]

[1] MALE
Levels: FEMALE MALE

blood[1]

[1] O
Levels: A B AB O

symptoms[1]

[1] SEVERE
Levels: MILD < MODERATE < SEVERE

# create a list for a patient
subject1 <- list(fullname = subject_name[1],
                 temperature = temperature[1],
                 flu_status = flu_status[1],
                 gender = gender[1],
                 blood = blood[1],
                 symptoms = symptoms[1])
subject1

$fullname
[1] "Joe Doe"

$temperature
[1] 97.1

$flu_status
[1] FALSE

$gender
[1] MALE
Levels: FEMALE MALE

$blood
[1] O
Levels: A B AB O

$symptoms
[1] SEVERE
Levels: MILD < MODERATE < SEVERE

Methods for accessing a list

# get a single list value by position (returns a sub-list)
subject1[2]

$temperature
[1] 97.1

# get a single list value by position (returns a numeric vector)
subject1[[2]]

[1] 97.1

# get a single list value by name
subject1$temperature

[1] 97.1

# get several list items by specifying a vector of names
subject1[c("temperature", "flu_status")]

$temperature
[1] 97.1

$flu_status
[1] FALSE

Access a list like a vector

# get values 2 and 3
subject1[2:3]

$temperature
[1] 97.1

$flu_status
[1] FALSE

Data Frames Create a data frame from medical patient data

pt_data <- data.frame(subject_name, temperature, flu_status, gender,
                      blood, symptoms, stringsAsFactors = FALSE)

#display the data frame
pt_data

Accessing a data frame

#get a single column
pt_data$subject_name

[1] "Joe Doe"       "Mary Doe"      "Steve Stevens"

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

# this is the same as above, extracting temprature and flu_status
pt_data[2:3] #refers to columns

# accesing by row and column
pt_data[1,2]

[1] 97.1

# accessing several rows and several columns using vectors
pt_data[c(1,3), c(2,4)] # x,y

Leave a row or column blank to extract all rows or columns

# column 1, all rows
pt_data[, 1]

[1] "Joe Doe"       "Mary Doe"      "Steve Stevens"

# row 1 and all columns
pt_data[1, ]

# all rows and all columns
pt_data[ , ]

# or simply display the entire dataset
pt_data

#the following are equivalent
pt_data[c(1,3), c("temperature", "gender")]

pt_data[-2, c(-1, -3, -5, -6)] #by exclusion

# creating a Celsius temperature column
pt_data$temp_c <- (pt_data$temperature - 32) * (5/9)

#comparing before and after
pt_data[c("temperature", "temp_c")]

Matrices

# create a 2x2 matrix
m <- matrix(c(1,2,3,4), nrow=2)
m

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

#equivalent to above
m <- matrix(c(1,2,3,4), ncol=2)
m

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

# create a 2x3 matrix
m <- matrix(c(1,5,8,6,9,3), ncol=3)
m

     [,1] [,2] [,3]
[1,]    1    8    9
[2,]    5    6    3

# create a 3x2 matrix
m1 <- matrix(c(4,5,8,6,9,3), ncol = 2)
m1

     [,1] [,2]
[1,]    4    6
[2,]    5    9
[3,]    8    3

#extract values from matrices
m[1,1]

[1] 1

m1[3,2]

[1] 3

# extract the first row
m[1, ]

[1] 1 8 9

# extract the second column
m1[ ,2]

[1] 6 9 3