scattered plot
n <- 80
set.seed(32611)
x <- sort(runif(n, min = 0, max=2*pi))
y <- sin(x) + rnorm(n, mean = 0, sd = 0.2)
plot(x,y)
n <- 80
set.seed(32611)
x <- sort(runif(n, min = 0, max=2*pi))
y <- sin(x) + rnorm(n, mean = 0, sd = 0.2)
plot(x,y)
plot(x,y, type="p") ## default is "p"
plot(x,y, type="l")
plot(x,y, type="b")
plot(x,y, type="o")
plot(x,y, type="n")
plot(x,y, main="sin function with Gaussian noise") # default xlab and ylab are the variable names of the arguments
plot(1:10, type="n", xlab="X", ylab="Y")
text(5.5, 9, "expression(y==alpha[1]*x+alpha[2]*x^2)", cex=1.5)
text(5.5, 8, expression(y==alpha[1]*x+alpha[2]*x^2), cex=1.5)
theta = 3
text(5.5, 6, "theta=3; bquote(hat(theta)==.(theta))", cex=1.5)
text(5.5, 5, bquote(hat(theta)==.(theta)), cex=1.5)
plot(x,y, main="sin function with Gaussian noise",
xlab="x axis", ylab="y axis") 
plot(x,y, main="sin function with Gaussian noise",
xlab="x axis", ylab="y axis",
cex=2, cex.axis=2, cex.lab=2, cex.main=2, cex.sub=2) 
plot(1:25,1:25,pch=1:25)
plot(x,y, pch=19) 
n <- 80
set.seed(32611)
x <- sort(runif(n, min = 0, max=2*pi))
y1 <- sin(x) + rnorm(n, mean = 0, sd = 0.2)
y2 <- cos(x) + rnorm(n, mean = 0, sd = 0.2)
par(mfrow=c(1,2))
plot(x,y1, main="sin plot")
plot(x,y2, main="cos plot")
par(mfrow=c(2,2))
plot(x,y, type="l",lwd=1)
plot(x,y, type="l",lwd=2)
plot(x,y, type="l",lwd=3)
plot(x,y, type="l",lwd=4) 
plot(1:8,1:8, col=1:8) 
par(mfrow=c(2,2))
plot(x,y, main = "black color") ## default is black
plot(x,y, main = "blue color", col=4) ## basic color option 1:8
plot(x,y, main = "green color", col='green') ## find colors from colors()
plot(x,y, main = "red color", col='#FF0000') ## RGB mode
n <- 10
par(mfrow=c(2,3))
plot(1:n,1:n, col=rainbow(n), main = "rainbow")
plot(1:n,1:n, col=heat.colors(n), main = "heat.colors")
plot(1:n,1:n, col=terrain.colors(n), main = "terrain.colors")
plot(1:n,1:n, col=topo.colors(n), main = "topo.colors")
plot(1:n,1:n, col=cm.colors(n), main = "cm.colors") 
letters[1:10] ## letters contain a-z## [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j"plot(x=1:10, y=1:10, type="n", main = "some texts")
text(x = 1:10, y=1:10, labels = letters[1:10])
curve(sin, from = 0, to = 2*pi)
chippy <- function(x) sin(cos(x)*exp(-x/2))
curve(chippy, -8, 7, n = 2001) # n specify number of points used to draw the curve, default n = 101
curve(sin, 0, 2*pi, col=2)
curve(cos, 0, 2*pi, col=4, add=T) ## add=T to overlay a new curve on top of the original figure
legend("bottomleft", legend = c("sin", "cos"), col = c(2,4),lty = 1)
par(mar=c(1,2,3,4)) # bottem, left, top, right order, inner margin
plot(x, y, main="Red sin", pch=20, col="red")
par(oma = c(4,3,2,1), mar=c(1,2,3,4)) # bottem, left, top, right order, inner margin and outer margin
plot(x, y, main="Red sin", pch=20, col="red")
boxplot(Petal.Length ~ Species, data = iris)
names(iris)## [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width"
## [5] "Species"par(mfrow = c(2,2))
for(i in 1:4){
aname <- names(iris)[i]
boxplot(iris[[i]] ~ iris$Species, xlab="Species", col=i, ylab=aname, main=aname)
}
par(mfrow=c(2,2))
hist(iris$Petal.Length)
hist(iris$Petal.Length, nclass=50)
hist(iris$Petal.Length, prob=TRUE, col="grey")
lines(density(iris$Petal.Length), col="blue")
par(mfrow = c(2,2))
xlims <- range(iris$Petal.Length)
uniqueSpecies <- levels(iris$Species)
for(i in 1:3){
aspecies <- uniqueSpecies[i]
sampleSelection <- iris$Species==aspecies
adata <- iris$Petal.Length[sampleSelection]
hist(adata, col=i, xlim=xlims, xlab="petal length",main=aspecies)
}
x <- y <- seq(-1, 1, len=25)
z <- outer(x, y, FUN=function(x,y) -x*y*exp(-x^2-y^2))
# Contour plots
contour(x,y,z, main="Contour Plot")
filled.contour(x,y,z, main="Filled Contour Plot")
filled.contour(x,y,z, color.palette = heat.colors)
filled.contour(x,y,z, color.palette = colorRampPalette(c("red", "white", "blue")))
matrix <- as.matrix(iris[,1:4])
image(matrix)
heatmap(matrix)
knitr::purl("Rgraph_basic.rmd", output = "Rgraph_basic.R ", documentation = 2)##
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## processing file: Rgraph_basic.rmd##
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|.................................................................| 100%## output file: Rgraph_basic.R## [1] "Rgraph_basic.R "