#Problem 1: Solution
sales1<-c(12,14,16,29,30,45,19,20,16, 19, 34, 20)
sales2<-rpois(12,34)  # random numbers, Poisson distribution, mean at 34, 12 numbers
par(bg="cornsilk")

plot(sales1, col="blue", type="o", ylim=c(0,100), xlab="Month", ylab="Sales" )
title(main="Sales by Month")

lines(sales2, type="o", pch=22, lty=2, col="red")
grid(nx=NA, ny=NULL)
legend("topright", inset=.05, c("Sales1","Sales2"), fill=c("blue","red"), horiz=TRUE)

#Problem 2: Solution
sales<-read.table(file.choose(), header=T)
sales # to verify that data has been read
barplot(as.matrix(sales), main="Sales Data", ylab= "Total",beside=T, col=rainbow(5))

#Problem 3: Solution
fn<-boxplot(sales,col=c("orange","green"))$stats

text(1.45, fn[3,2], paste("Median =", fn[3,2]), adj=0, cex=.7)
text(0.45, fn[3,1],paste("Median =", fn[3,1]), adj=0, cex=.7)
grid(nx=NA, ny=NULL)

#Problem 4: Access web files
fb1<-read.csv("http://real-chart.finance.yahoo.com/table.csv?s=FB&d=10&e=5&f=2014&g=d&a=11&b=12&c=2013&ignore=.csv")
View(fb1)
par(bg="cornsilk")


#Problem 5: Access existing data sets in R
data()
#Observe the data sets available for explorations.
attach(mpg)
head(mpg)
summary(mpg)
#after analysis remove the data from the memory
detach(mpg)

library (help=datasets

#Problem 6: External APIs and "map"
library("ggmap")
library("maptools")
library(maps)
visited <- c("SFO", "Chennai", "London", "Melbourne", "Johannesbury, SA")
ll.visited <- geocode(visited)
visit.x <- ll.visited$lon
visit.y <- ll.visited$lat
map("world", fill=TRUE, col="white", bg="lightblue", ylim=c(-60, 90), mar=c(0,0,0,0))
points(visit.x,visit.y, col="red", pch=36)

#USA map
library("ggmap")
library("maptools")
library(maps)
visited <- c("SFO", "New York", "Buffalo", "Dallas, TX")
ll.visited <- geocode(visited)
visit.x <- ll.visited$lon
visit.y <- ll.visited$lat
map("state", fill=TRUE, col=rainbow(50), bg="lightblue", mar=c(0,0,0,0))
points(visit.x,visit.y, col="yellow", pch=36)

#Problem 7: Lattice
splom(mtcars[c(1,3,4,5,6)], main="MTCARS Data")
splom(mtcars[c(1,3,4,6)], main="MTCARS Data")
splom(mtcars[c(1,3,4,6)], col=rainbow(),main="MTCARS Data")

Another data set: “rock” 
splom(rock[c(1,2,3,4)], main="ROCK Data")