data("airquality")
Ozone = na.omit(airquality$Ozone)


###### Stripchart ######

stripchart(Ozone)

stripchart(Ozone,method="overplot",pch=1,col=1,cex=1.5)         # vertical=FALSE
stripchart(Ozone,method="overplot",pch=1,col=1,cex=1.5,log="x")

stripchart(Ozone,method="jitter",jitter=0.1, pch=1,col=1,cex=1.5)
stripchart(Ozone,method="jitter",jitter=0.1, pch=1,col=1,cex=1.5,log="x")

stripchart(Ozone,method="stack",pch=1,col=1,cex=1.5)
stripchart(Ozone,method="stack",pch=1,col=1,cex=1.5,log="x")

stripchart(Petal.Length~Species, data=iris,main="Iris",
           xlab="Species",ylab="Petal length",col=c(2,3,4),
           vertical=TRUE,pch=16)
stripchart(Petal.Length~Species, data=iris,main="Iris",
           xlab="Species",ylab="Petal length",col=c(2,3,4),
           vertical=FALSE,pch=16)

library(beeswarm)
beeswarm(Ozone, log = FALSE,pch = 1, col = 1, cex = 1.2, vertical=FALSE)
beeswarm(Ozone, log = TRUE,pch = 1, col = 1, cex = 1.2, vertical=FALSE)


library(ggplot2)

ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_jitter()

p<-ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_jitter(position=position_jitter(0.2))
p

p + coord_flip()

ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_dotplot(binaxis='y', stackdir='center')


library(lattice)
stripplot(Petal.Length ~ Species, iris)
stripplot(Species ~ Petal.Length, iris)

###### Histogram ######

hist(Ozone)
hist(Ozone, freq=TRUE)
hist(Ozone, freq=FALSE)

hist(Ozone,main="Air quality",xlab="Ozone",col="darkmagenta",freq=FALSE)

h <- hist(Ozone,ylim=c(0,50)); h
text(h$mids,h$counts,labels=h$counts, adj=c(0.5, -0.5))


hist(Ozone, breaks=4, main="With breaks=4")
hist(Ozone, breaks=20, main="With breaks=20")

nclass.Sturges(Ozone) # Sturges = default
nclass.scott(Ozone) # Scott
nclass.FD(Ozone) # Friedman - Diaconis

hist(Ozone, breaks=nclass.FD(Ozone), main="")

range(Ozone)
hist(Ozone,main="Ozone",xlab="Ozone",col="chocolate",
     border="black",breaks=c(1,10,25, 50,100,200))


hist(Ozone, freq=TRUE, breaks = 20, plot = TRUE,main = NULL)
rug(Ozone, col=2)

hist(Ozone, freq=FALSE, breaks = 20, plot = TRUE,main = NULL)
library(BHH2)
dots(Ozone, y = 0, xlim = range(Ozone,na.rm=TRUE), stacked = FALSE, hmax= 0.5,base = TRUE, axes = FALSE, pch = 21, pch.size = "x", labels = NULL,hcex = 1, cex = par("cex"), cex.axis = par("cex.axis"))


library(ggplot2)

p <- ggplot(as.data.frame(Ozone), aes(x=Ozone)) + 
   geom_histogram()
p

p + geom_histogram(binwidth=5)

p + geom_histogram(color="black", fill="white")


ggplot(as.data.frame(Ozone), aes(x=Ozone)) + 
  geom_histogram(aes(y=..density..), colour="black", fill="white")+
  geom_density(alpha=.2, fill="#FF6666") 


ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_histogram(fill="white")


library(lattice)
histogram(~Petal.Length | Species, data = iris, xlab = "Iris",
          type = "density", nint = 10, layout = c(2, 2))



###### Kernel density estimation (KDE) plot ######

density(Ozone)

plot(density(Ozone))
rug(Ozone)

plot(density(Ozone))
polygon(density(Ozone), col = "#1b98e0")

hist(Ozone, prob = TRUE)        
lines(density(Ozone), col = "red")

hist(Ozone, prob = TRUE) 
curve(dnorm(x, mean=mean(Ozone), sd=sd(Ozone)), add=TRUE, col="red")

plot(density(Ozone), lwd = 2, col=2)
plot(density(Ozone, bw = 25), lwd = 2, col = "red", main = "big bandwidth")
plot(density(Ozone, bw = 4), lwd = 2, col = "red", main = "small bandwidth")

bw.nrd0(Ozone) # Silverman
bw.nrd(Ozone)  # Scott
bw.SJ(Ozone, method = c("ste", "dpi")) # Sheather & Jones
bw.ucv(Ozone) # unbiased cross-validation
bw.bcv(Ozone) # biased cross-validation


plot(density(Ozone, n = 1000))
rug(precip)
lines(density(Ozone, bw = "nrd"), col = 2)
lines(density(Ozone, bw = "ucv"), col = 3)
lines(density(Ozone, bw = "bcv"), col = 4)
lines(density(Ozone, bw = "SJ-ste"), col = 5)
lines(density(Ozone, bw = "SJ-dpi"), col = 6)
legend("topright",legend = c("nrd0", "nrd", "ucv", "bcv", "SJ-ste", "SJ-dpi"),
       col = 1:6, lty = 1)


den1 = density(Ozone)
den1$bw
den1$x
den1$y
plot(den1$x, den1$y, type="l", ylab = "density", xlab = "x")
rug(Ozone, lwd=2)
library(BHH2)
dots(Ozone, y = 0, xlim = range(Ozone,na.rm=TRUE), stacked = FALSE, hmax= 0.5,base = TRUE, axes = FALSE, pch = 21, pch.size = "x", labels = NULL,hcex = 1, cex = par("cex"), cex.axis = par("cex.axis"))


library(ggplot2)

p <- ggplot(as.data.frame(Ozone), aes(x=Ozone)) + 
  geom_density()
p

p + geom_density(color="darkblue", fill="lightblue")


ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_density()

ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_density(adjust=0.5)

ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_density(adjust=5)

ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_density(adjust=bw.nrd0(iris$Petal.Length))

ggplot(iris, aes(x=Petal.Length, color=Species)) +
  geom_density(adjust=bw.ucv(iris$Petal.Length))


library(lattice)

densityplot(~ Petal.Length, data = iris)

densityplot(~ Petal.Length, data = iris,
            kernel = "gauss", bw = 0.5, plot.points = "rug", n = 200)

densityplot(~Petal.Length | Species, data = iris,
            plot.points = FALSE, ref = TRUE, layout = c(2, 2))



###### Box and whisker plot (boxplot) ######

boxplot(Ozone)

boxplot(Ozone,main = "Mean ozone in parts per billion",
        xlab = "Parts Per Billion",ylab = "Ozone",
        col = "orange", border = "black",horizontal = TRUE,
        notch = TRUE)

b <- boxplot(Ozone)
b
boxplot.stats(Ozone)
boxplot.stats(Ozone)$out

library(beeswarm)
boxplot(Ozone, horizontal=TRUE, notch = FALSE, xlab = "Ozone", log = "x", cex = 1.2)
beeswarm(Ozone, log = TRUE,pch = 1, col = 1, cex = 1.2, vertical=FALSE, add=TRUE)

boxplot(Ozone,xlab="Ozone",las=2, horizontal=TRUE, cex=1.2,log="x") 
stripchart(Ozone,pch=1, col=1, vert=FALSE, add=TRUE, cex=1.2,log="x")

boxplot(Ozone,xlab="Ozone",las=2, horizontal=TRUE, cex=1.2,log="") 
rug(Ozone, col=2)


boxplot(Petal.Length~Species, data=iris,main="Iris",
        xlab="Species",ylab="Petal length")



library(ggplot2)

p <- ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_boxplot()
p
p + coord_flip()

ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_boxplot(notch=TRUE)

ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_boxplot(outlier.colour="red", outlier.shape=19,outlier.size=2)

p + geom_dotplot(binaxis='y', stackdir='center', dotsize=1)

p + geom_jitter(shape=16, position=position_jitter(0.2))


library(lattice)
bwplot(Petal.Length ~ Species, data = iris,
       xlab = "Species", ylab = "Petal length")
bwplot(Species ~ Petal.Length, data = iris,
       xlab = "Petal length", ylab = "Species")



library(vioplot)

vioplot(Ozone, range=1.5, horizontal=TRUE, col=0)
stripchart(Ozone, pch=1, col=2, vert=FALSE, add=TRUE, cex=1.2)

vioplot(Ozone, range=1.5, horizontal=TRUE, col=0)
stripchart(x, method="jitter", pch=1, col=2, vert=FALSE, add=TRUE, cex=1.2)

vioplot(Ozone, range=1.5, horizontal=TRUE, col=0)
beeswarm(Ozone, log = FALSE,pch = 16, col = 2, cex = 1.2, vertical=FALSE, add=TRUE)


library(ggplot2)
p <- ggplot(iris, aes(x=Species, y=Petal.Length)) + 
  geom_violin()
p
p + coord_flip()

p + stat_summary(fun.y=mean, geom="point", shape=23, size=2)
p + stat_summary(fun.y=median, geom="point", size=2, color="red")
p + geom_boxplot(width=0.1)

data_summary <- function(x){
  m <- mean(x)
  ymin <- m-sd(x)
  ymax <- m+sd(x)
  return(c(y=m,ymin=ymin,ymax=ymax))
}
p + stat_summary(fun.data=data_summary)

p + geom_dotplot(binaxis='y', stackdir='center', dotsize=1)

p + geom_jitter(shape=16, position=position_jitter(0.2))