R Data Strucures

Vectors

# create vectors of data for three medical patients
subject_name <- c("John Doe", "Jane Doe", "Steve Graves")
temperature <- c(98.1, 98.6, 101.4)
flu_status <- c(FALSE, FALSE, TRUE)

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

[1] 98.6

Examples of accessing items in vector

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

[1]  98.6 101.4

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

[1]  98.1 101.4

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

[1] 98.1 98.6

Factors

gender <- factor(c("MALE","FEMALE","MALE"))
gender

[1] MALE   FEMALE MALE  
Levels: FEMALE MALE

blood <- factor(c("O", "AB","A"),
          levels = c("A", "B","AB", "O"))
blood

[1] O  AB A 
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

# ISsymptoms greater than moderate
symptoms > "MODERATE"

[1]  TRUE FALSE FALSE

Lists

# display information for a patient
subject_name[1]

[1] "John Doe"

temperature[1]

[1] 98.1

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

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

# Display subject 1
subject1

$fullname
[1] "John Doe"

$temperature
[1] 98.1

$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

# List for patient 2
subject2 <- list(fullname = subject_name[2],
                 temperature = temperature[2],
                 flu_status = flu_status[2],
                 gender = gender[2],
                 blood = blood[2],
                 symptoms = symptoms[2])

# Display subject 2
subject2

$fullname
[1] "Jane Doe"

$temperature
[1] 98.6

$flu_status
[1] FALSE

$gender
[1] FEMALE
Levels: FEMALE MALE

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

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

Methods for accessing a list

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

$temperature
[1] 98.1

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

[1] 98.1

# get a single list value by name
subject1$temperature

[1] 98.1

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

$temperature
[1] 98.1

$flu_status
[1] FALSE

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

$gender
[1] MALE
Levels: FEMALE MALE

$fullname
[1] "John Doe"

Access a list like a vector

subject1[2:3]

$temperature
[1] 98.1

$flu_status
[1] FALSE

subject2[2:3]

$temperature
[1] 98.6

$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, stringAsFactors = FALSE)

# Display Dataframe
pt_data

Accessing a data frame

# get a single column
pt_data$subject_name

[1] "John Doe"     "Jane Doe"     "Steve Graves"

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

pt_data[2:3]

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

[1] 98.1

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

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

# columns 1, all rows
pt_data[ , 1]

[1] "John Doe"     "Jane Doe"     "Steve Graves"

# row 1, all columns
pt_data[1, ]

# All rows, all columns
pt_data[ , ]

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

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

NA

Matrixes —–

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

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

# equivalent to the 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, 2, 3, 4, 5, 6), nrow = 2)
m

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

# create 3x2 matrix
m <- matrix(c(1,2,3,4,5,6), ncol =2)
m

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

# extract values from matrixes
m[1, 1]

[1] 1

m[3, 2]

[1] 6

# xtract all first rows
m[1 , ]

[1] 1 4

# extract columns
m[, 1]

[1] 1 2 3