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# 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# 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# 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] 98.1flu_status[1][1] FALSEgender[1][1] MALE
Levels: FEMALE MALEblood[1][1] O
Levels: A B AB Osymptoms[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 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
$flu_status
[1] FALSEpt_data <- data.frame(subject_name, temperature, flu_status, gender,
blood, symptoms, stringsAsFactors = FALSE)
# display the data frame
pt_data# get a single column
pt_data$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)]# column 1, all rows
pt_data[, 1][1] "John Doe" "Jane Doe" "Steve Graves"# row 1, all columns
pt_data[1, ]# all rows and all columns
pt_data[ , ]# the following are equivalent
pt_data[c(1, 3), c("temperature", "gender")]pt_data[-2, c(-1, -3, -5, -6)]# 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] 1m[3, 2][1] 6# extract rows
m[1, ][1] 1 4# extract columns
m[, 1][1] 1 2 3