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




# Bar/ Line Chart 
plot(AirPassengers,type="l")  #Simple Line Plot
barplot(iris$Petal.Length) #Creating simple Bar Graph
Hide
barplot(iris$Sepal.Length,col  = brewer.pal(3,"Set1"))
barplot(table(iris$Species,iris$Sepal.Length),col  = brewer.pal(3,"Set1")) #Stacked Plot
Hide
# Box Plot ( including group-by option )
boxplot(iris$Petal.Length~iris$Species) #Creating Box Plot between two variable
data(iris)
par(mfrow=c(2,2))







boxplot(iris$Sepal.Length,col="red")
boxplot(iris$Sepal.Length~iris$Species,col="red")
Hide
boxplot(iris$Sepal.Length~iris$Species,col=heat.colors(3))
boxplot(iris$Sepal.Length~iris$Species,col=topo.colors(3))





# Scatter Plot (including 3D and other features)
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"))





pie(table(iris$Species))





# Advanced Visualizations
# Hexbin Binning
library(ggplot2)
library(hexbin)
a=hexbin(diamonds$price,diamonds$carat,xbins=40)
plot(a)





library(RColorBrewer)
rf <- brewer.pal="" class="separator" colorramppalette="" div="" et3="" rev="" style="clear: both; text-align: center;">



hexbinplot(diamonds$price~diamonds$carat, data=diamonds, colramp=rf)
# Mosaic Plot 
data(HairEyeColor)
mosaicplot(HairEyeColor)





# Heat Map 
heatmap(as.matrix(mtcars))





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







# How to summarize lots of data ? 
# Map Visualization
#install.packages("leaflet")
library(magrittr)
library(leaflet)
m <- leaflet="">%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=77.2310, lat=28.6560, popup="The delicious food of chandni chowk")
m  # Print the map







# Leaflet for R
library(leaflet)
library(magrittr)
m <- leaflet="">%
  addTiles() %>%  # Add default OpenStreetMap map tiles
  addMarkers(lng=174.768, lat=-36.852, popup="The birthplace of R")
m  # Print the map







m <- addmarkers="" addtiles="" class="separator" div="" lat="-36.852," leaflet="" lng="174.768," m="" popup="The birthplace of R" style="clear: both; text-align: center;">






# 3D Graphs
# install.packages('Rcmdr')
# library(Rcmdr)
# library(RcmdrMisc)
# install.packages("rgl")
# data(iris, package="datasets")
# library(brglm)
# scatter3d(Petal.Width~Petal.Length+Sepal.Length|Species, data=iris, fit="linear",
#           residuals=TRUE, parallel=FALSE, bg="black", axis.scales=TRUE, grid=TRUE, ellipsoid=FALSE)
# 
# attach(iris)# 3d scatterplot by factor level
# cloud(Sepal.Length~Sepal.Width*Petal.Length|Species, main="3D Scatterplot by Species")
# xyplot(Sepal.Width ~ Sepal.Length, iris, groups = iris$Species, pch= 20)
# library(Rcmdr)
# Correlogram (GUIs)

library(corrplot)
library(corpcor)
library(corrgram)

cor(iris[1:4])

corrgram(iris)






THANK YOU