Basics To Advanced ggplot usage

Data Visualization in R:

In this article, we will create the following visualizations:
Basic Visualization

1. Histogram
2. Bar / Line Chart
3. Box plot
4. Scatter plot

Advanced Visualization

1. Heat Map
2. Mosaic Map
3. Map Visualization
4. 3D Graphs
5. Correlogram

library(RColorBrewer)
data(VADeaths)
par(mfrow=c(2,3))
hist(VADeaths,breaks=10, col=brewer.pal(6,"Set3"),main="Set3 3 colors")
hist(VADeaths,breaks=3 ,col=brewer.pal(3,"Set2"),main="Set2 3 colors")
hist(VADeaths,breaks=7, col=brewer.pal(3,"Set1"),main="Set1 3 colors")
hist(VADeaths,breaks= 2, col=brewer.pal(8,"Set3"),main="Set3 8 colors")
hist(VADeaths,col=brewer.pal(8,"Greys"),main="Greys 8 colors")
hist(VADeaths,col=brewer.pal(8,"Greens"),main="Greens 8 colors")

plot(AirPassengers,type="l")  #Simple Line Plot

barplot(iris$Petal.Length) #Creating simple Bar Graph
barplot(iris$Sepal.Length,col  = brewer.pal(3,"Set1"))
barplot(table(iris$Species,iris$Sepal.Length),col  = brewer.pal(3,"Set1")) #Stacked Plot

data(iris)
par(mfrow=c(2,2))
boxplot(iris$Sepal.Length,col="red")
boxplot(iris$Sepal.Length~iris$Species,col="red")
oxplot(iris$Sepal.Length~iris$Species,col=heat.colors(3))
boxplot(iris$Sepal.Length~iris$Species,col=topo.colors(3))

plot(x=iris$Petal.Length) #Simple Scatter Plot

plot(x=iris$Petal.Length,y=iris$Species) #Multivariate Scatter Plot






plot(iris,col=brewer.pal(3,"Set1"))

library(hexbin)
a=hexbin(diamonds$price,diamonds$carat,xbins=40)
library(RColorBrewer)
plot(a)

library(RColorBrewer)
rf <- brewer.pal="" carat="" code="" colorramppalette="" colramp="rf)" data="diamonds," diamonds="" et3="" hexbinplot="" price="" rev="">

data(HairEyeColor)
mosaicplot(HairEyeColor)

heatmap(as.matrix(mtcars))
image(as.matrix(b[2:7]))