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subject_name <- c("John Doe", "Jane Doe", "Steve Graves")
temperature <- c(98.1, 98.6, 101.4)
flu_status <- c(FALSE, FALSE, TRUE)
temperature[2]
## [1] 98.6
temperature[2:3]
## [1]  98.6 101.4
temperature[-2]
## [1]  98.1 101.4
temperature[c(TRUE, TRUE, FALSE)]
## [1] 98.1 98.6
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
symptoms <- factor(c("SEVERE", "MILD", "MODERATE"),
                   levels = c("MILD", "MODERATE", "SEVERE"),
                   ordered = TRUE)
symptoms
## [1] SEVERE   MILD     MODERATE
## Levels: MILD < MODERATE < SEVERE
symptoms > "MODERATE"
## [1]  TRUE FALSE FALSE
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
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] "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
subject1[2]
## $temperature
## [1] 98.1
subject1[[2]]
## [1] 98.1
subject1$temperature
## [1] 98.1
subject1[c("temperature", "flu_status")]
## $temperature
## [1] 98.1
## 
## $flu_status
## [1] FALSE
subject1[2:3]
## $temperature
## [1] 98.1
## 
## $flu_status
## [1] FALSE
pt_data <- data.frame(subject_name, temperature, flu_status, gender,
                      blood, symptoms, stringsAsFactors = FALSE)
pt_data
##   subject_name temperature flu_status gender blood symptoms
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE
## 2     Jane Doe        98.6      FALSE FEMALE    AB     MILD
## 3 Steve Graves       101.4       TRUE   MALE     A MODERATE
pt_data$subject_name
## [1] "John Doe"     "Jane Doe"     "Steve Graves"
pt_data[c("temperature", "flu_status")]
##   temperature flu_status
## 1        98.1      FALSE
## 2        98.6      FALSE
## 3       101.4       TRUE
pt_data[2:3]
##   temperature flu_status
## 1        98.1      FALSE
## 2        98.6      FALSE
## 3       101.4       TRUE
pt_data[1, 2]
## [1] 98.1
pt_data[c(1, 3), c(2, 4)]
##   temperature gender
## 1        98.1   MALE
## 3       101.4   MALE
pt_data[, 1]
## [1] "John Doe"     "Jane Doe"     "Steve Graves"
pt_data[1, ]
##   subject_name temperature flu_status gender blood symptoms
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE
pt_data[ , ]
##   subject_name temperature flu_status gender blood symptoms
## 1     John Doe        98.1      FALSE   MALE     O   SEVERE
## 2     Jane Doe        98.6      FALSE FEMALE    AB     MILD
## 3 Steve Graves       101.4       TRUE   MALE     A MODERATE
pt_data[c(1, 3), c("temperature", "gender")]
##   temperature gender
## 1        98.1   MALE
## 3       101.4   MALE
pt_data[-2, c(-1, -3, -5, -6)]
##   temperature gender
## 1        98.1   MALE
## 3       101.4   MALE
pt_data$temp_c <- (pt_data$temperature - 32) * (5 / 9)
pt_data[c("temperature", "temp_c")]
##   temperature   temp_c
## 1        98.1 36.72222
## 2        98.6 37.00000
## 3       101.4 38.55556
m <- matrix(c(1, 2, 3, 4), nrow = 2)
m
##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
m <- matrix(c(1, 2, 3, 4), ncol = 2)
m
##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
m <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2)
m
##      [,1] [,2] [,3]
## [1,]    1    3    5
## [2,]    2    4    6
m <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2)
m
##      [,1] [,2]
## [1,]    1    4
## [2,]    2    5
## [3,]    3    6
m[1, 1]
## [1] 1
m[3, 2]
## [1] 6
m[1, ]
## [1] 1 4
m[, 1]
## [1] 1 2 3