# Sometimes important stuff is highlighted! #<<
7 * 49
## > (11-2
## +
123 + 456 + 789
sqrt(400)
## ?sqrt
new.object <- 144
new.object
new.object + 10
new.object + new.object
sqrt(new.object)
new.object <- c(4, 9, 16, 25, 36)
new.object
sqrt(new.object)
summary(cars)
library(knitr)
x <- sqrt(77) # <- is how we assign variables
head(cars, 5) # prints first 5 rows, see tail() too
str(cars) # str[ucture]
summary(cars)
hist(cars$speed) # Histogram
hist(cars$dist)
hist(cars$dist,
xlab = "Distance (ft)", # X axis label
main = "Observed stopping distances of cars") # Title
( dist_mean <- mean(cars$dist) )
( speed_mean <- mean(cars$speed) )
plot(dist ~ speed, data = cars, #<<
xlab = "Speed (mph)",
ylab = "Stopping distance (ft)",
main = "Speeds and stopping distances of cars",
pch = 16) # Point size
abline(h = dist_mean, col = "firebrick")
abline(v = speed_mean, col = "cornflowerblue")
pairs(swiss, pch = 8, col = "violet", #<<
main = "Pairwise comparisons of Swiss variables")
## library(pander) # loads pander, do once in your session
## pander(summary(swiss), style = "rmarkdown", split.tables = 120) #<<
library(pander) # loads pander, do once in your session
pander(summary(swiss), style = "rmarkdown", split.tables = 120)
## pander(head(swiss, 5), style = "rmarkdown", split.tables = 120)
pander(head(swiss, 5), style = "rmarkdown", split.tables = 120)