There are three key plotting systems in R, the Base, which is a type of artist’s palette, model, a Lattice System, which allows to specify an entire plot specified by one function and the conditioning ggplot2 with mixed elements of Base and Lattice, this is a demo of the base plot.
library(datasets)
data(cars)
with(cars, plot(speed, dist))
library(datasets)
hist(airquality$Ozone) ## Draw a new plot
library(datasets)
with(airquality, plot(Wind, Ozone))
library(datasets)
airquality <- transform(airquality, Month = factor(Month))
boxplot(Ozone ~ Month, airquality, xlab = "Month", ylab = "Ozone (ppb)")
library(datasets)
with(airquality, plot(Wind, Ozone))
title(main = "Ozone and Wind in New York City") ## Add a title
with(airquality, plot(Wind, Ozone, main = "Ozone and Wind in New York City"))
with(subset(airquality, Month == 5), points(Wind, Ozone, col = "blue"))
with(airquality, plot(Wind, Ozone, main = "Ozone and Wind in New York City",
type = "n"))
with(subset(airquality, Month == 5), points(Wind, Ozone, col = "blue"))
with(subset(airquality, Month != 5), points(Wind, Ozone, col = "red"))
legend("topright", pch = 1, col = c("blue", "red"), legend = c("May", "Other Months"))
-Regression Line
with(airquality, plot(Wind, Ozone, main = "Ozone and Wind in New York City",
pch = 20))
model <- lm(Ozone ~ Wind, airquality)
abline(model, lwd = 2)
par(mfrow = c(1, 2))
with(airquality, {
plot(Wind, Ozone, main = "Ozone and Wind")
plot(Solar.R, Ozone, main = "Ozone and Solar Radiation")
})
par(mfrow = c(1, 3), mar = c(4, 4, 2, 1), oma = c(0, 0, 2, 0))
with(airquality, {
plot(Wind, Ozone, main = "Ozone and Wind")
plot(Solar.R, Ozone, main = "Ozone and Solar Radiation")
plot(Temp, Ozone, main = "Ozone and Temperature")
mtext("Ozone and Weather in New York City", outer = TRUE)
})