R Notebook

# 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

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

[1]  98.6 101.4

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

[1]  98.6 101.4

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

[1] 98.1 98.6

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

[1] MALE   FEMALE MALE  
Levels: FEMALE MALE

# add blood type factor
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

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

[1]  TRUE FALSE FALSE

# display information for a patient
subject_name[1]

[1] "John Doe"

temperature[1]

[1] 98.1

flu_status[1]

[1] FALSE

gender[2]

[1] FEMALE
Levels: FEMALE MALE

blood[1]

[1] O
Levels: A B AB O

symptoms[1]

[1] SEVERE
Levels: MILD < MODERATE < SEVERE

# create 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])

# display the patient
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

# 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")]

$temperature
[1] 98.1

$flu_status
[1] FALSE

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

$temperature
[1] 98.1

$flu_status
[1] FALSE

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

# display the data frame
pt_data

# 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")]

# this is the same as above, extracting temperature and flu_status
pt_data[2:3]

# accessing 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)]

# all rows and all columns
pt_data[ , ]

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

# 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")]

# 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 a 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