R Notebook

This is an R notebook.

clev = read.csv("ClevelandHeart.csv")
dim(clev)

[1] 303  12

mean(clev$Age)

[1] 54.43894

mean(clev[,1])

[1] 54.43894

clev[1,]

mean(clev[1,])

[1] NA

clev[1,3]

[1] "typical"

clev[1,1:5]

clev[1,c(1,3,5)]

clev[1:4,c(1,3,5)]

Summary Statistics

mean(clev$Age)

[1] 54.43894

median(clev$Age)

[1] 56

sd(clev$Age)

[1] 9.038662

IQR(clev$Age)

[1] 13

dim(clev)

[1] 303  12

length(clev$Age)

[1] 303

sum(clev$Age)

[1] 16495

max(clev$Age)

[1] 77

min(clev$Age)

[1] 29

z = clev$Age
z <- clev$Age

mean(clev$Age)

[1] 54.43894

Plots

hist(clev$Age,xlab="years",ylab="number patients",main="Figure 1",breaks=20)

boxplot(clev$Age)

boxplot(Age ~ Sex, data=clev)

plot(clev$Age, clev$RestBP,xlab="years",ylab="mm Hg")

Extracting subsets

z = clev[1:5,1:3]
z

z$Age > 60

[1]  TRUE  TRUE  TRUE FALSE FALSE

sum(z$Age > 60)

[1] 3

mean(z$Age > 60)

[1] 0.6

over60 = z[z$Age>60,]
over60

z$ChestPain == "asymptomatic"

[1] TRUE TRUE TRUE TRUE TRUE

z

z[z$ChestPain=="asymptomatic",]

mean(over60$Age)

[1] 65.32911

mean(asyCP$Age)

[1] 55.72222

over60andASY = clev[(clev$Age>60) & (clev$ChestPain=="asymptomatic"),]

mean(clev$Fluoroscopy,na.rm=T)

[1] 0.6722408

sum(is.na(clev$Fluoroscopy))

[1] 4

which(is.na(clev$Fluoroscopy))

[1] 167 193 288 303

clevx = na.omit(clev)
dim(clevx)

[1] 297  12