R plot examples, matrix, aggregates, conditions examples

	#Create a vector from 1 to 20, Step by 2
	a <- c(seq(1,20,2))
	#Create a 5 X 2 Matrix
	m <- matrix(a, nrow = 5, ncol = 2, byrow=TRUE)
	m
	#Create a 2 X 5 Matrix
	m <- matrix(a, nrow = 2, ncol = 5, byrow=TRUE)
	m
	#transpose
	t(m)
	#Create Square matrix
	m <- matrix(a, nrow = 2, ncol = 2, byrow=TRUE)
	det(m)
	#matrix multiplication, Operator %*%
	m%*%m
	#eigen values
	eigen(m)
	#svd - singular vector decomposition
	svd(m)

view raw Matrix.R hosted with ❤ by GitHub

	#vector with hundred elements
	m <- c(seq(1,100,1))
	#List all values > 10
	m[m>10]
	#List all values > 10 and < 50
	m[m>10 & m < 50]
	#List all values > 10 and !=50
	m[m>10 & m!= 50]
	#Conditional select from data frame
	food = read.csv("protein.csv")
	newdata <- food[(food$RedMeat>5),]
	newdata
	#Load Some Sample Data
	dat <- read.table(textConnection('Group Score Info
	+ 1 1 1 a
	+ 2 1 2 b
	+ 3 1 3 c
	+ 4 2 4 d
	+ 5 2 3 e
	+ 6 2 1 f'))
	#print summary
	summary(dat)
	#Aggregations
	aggregate(Score~Group,dat,sum)
	aggregate(Score~Group,dat,mean)
	#functions
	cellbillcompute<-function()
	{
	billdays<- c(55,10,15,33,21,33,45,66,35,25)
	#max value
	print(max(billdays))
	#min value
	print(min(billdays))
	#sum of all bill days
	print(sum(billdays))
	#Number of days bill value > 20
	print(length(billdays[billdays>20]))
	}
	cellbillcompute()

view raw AggregatesConditions.R hosted with ❤ by GitHub

	#Installing Packages
	remove.packages(c("ggplot2", "data.table"))
	install.packages('Rcpp', dependencies = TRUE)
	install.packages('ggplot2', dependencies = TRUE)
	install.packages('data.table', dependencies = TRUE)
	#List all packages
	data()
	#Visualization Examples
	carsmodel <- c("Dzire", "Vitara", "ALTO", "Gypsy", "Baleno")
	sales <- c(200, 555, 424, 599, 12000)
	#plot example
	plot(factor(carsmodel),sales,type="o",col="green",pch=22)
	#dotplot
	library(lattice)
	dotplot(sales~carsmodel)
	#Connected Lines
	dotplot(sales~carsmodel,type="b")
	library(ggplot2)
	qplot(carsmodel,sales)
	ggplot(data.frame(carsmodel,sales), aes(carsmodel,sales)) + geom_point()
	#plot for share values
	library("quantmod")
	getSymbols('TYC')
	chartSeries(TYC, subset='last 3 months')
	addBBands()
	food = read.csv("protein.csv")
	#Find Outliers
	boxplot(food$RedMeat)
	#boxplot with multiple variables
	boxplot(food$RedMeat,food$WhiteMeat, food$Eggs)
	#Histogram of data
	hist(food$RedMeat)
	#Summary
	summary(food)
	#heatmap
	library(rgl)
	dist = as.matrix(food[-1])
	heatmap(dist)

view raw PlotExamples.R hosted with ❤ by GitHub

Happy Learning!!!