Practice20200624

R Example

## R Basic
data(anscombe) # R datasets by default
View(anscombe)
plot(y1 ~ x1, data = anscombe) 
lmfit <- lm(y1~x1, data=anscombe) #minimum square
lmfit
plot(y1 ~ x1, data = anscombe)
abline(lmfit, col="red") #draw the model line

a <- 3
a
b = 5
c <- a + b
c
numer <- 17.8
char <- "Hello World!"
logic <- TRUE
class(logic)
card_length <- 3 
card_width <- "5 inches"
card_length * card_width
card_length <- 3 
card_width <- 5
card_length * card_width

t <- 40
1- t/100
height_vec <- c(180, 169, 173) 
name_vec <- c("Brian", "Toby", "Sherry")
x <- c(1,2,3,4) 
y <- c(3,5)
x <- 1:20
x
y <- seq(1, 20)
y
seq(1,20,2)
seq(1,3.5, by =0.5)
seq(1,10,length.out = 2)
seq(1,10,lengt = 2) #not neccessary to input full name
help(seq)
x <- c(1,2,3,5,7, NaN ,9, NA, 11)
sum(x, na.rm = TRUE) #na.rm =FALSE is setting by default
?sum

#--------------------------------assign Vector name
names(height_vec) <- name_vec
height_vec
names(height_vec)
#--------------------------------Filter
height_vec > 175
height_vec < 175
height_vec >= 170 & height_vec < 180
height_vec >= 180 | height_vec < 170
(!(height_vec >= 170 & height_vec < 180))
height_vec[height_vec > 175]
#===============================Exercise BMI
weight_vec <- c(73, 87, 43)
BMI <- weight_vec / (height_vec/ 100) ^2
names(BMI) <- name_vec
BMI[BMI > 24 | BMI < 18.5] #abnormal BMI
BMI[!(BMI > 24 | BMI < 18.5)] #normal BMI
#-------------------------------BONUS!!!
BMI_cal <- function(bmi){
    if(bmi < 18.5){
        return("underweight")
    } else if (bmi >= 18.5 & bmi < 24){
        return("normal")
    }else {
        return("Overweight")
    }
}

BMI_cal(36)
?apply
lapply(BMI, BMI_cal)
sapply(BMI, BMI_cal)

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