Output format: HTML.
Data Source : NYPD vehicle collision data.
Data Transformation: Year 2014: Summary of persons injured by borough.
Chart: Column chart comparing injuries by borough.

require(knitr)
nypdvcrashSummary <-read.csv("c:/Aarti/Columbia Data Sciences/EDAV/RProject/data/NYPDSummary_Byborough.csv",header=T,sep=",")
require("ggplot2")

#BAR PLOTS
library(MASS)
library(plyr)

(bp1 <- ggplot(data=nypdvcrashSummary, 
        aes(x=BOROUGH,y=Frequency,
        fill=factor(Type))) 
     +  geom_bar(stat="identity", position=position_dodge()) 
     +  ggtitle("summary - Persons Injured By Boroughs")
     +  geom_text(aes(label=Frequency), vjust=-1, size=3)
     +  theme(plot.title=element_text(size=rel(1), face="bold"))
     +  theme(axis.title=element_text(size=15)))

Data Source : NYPD vehicle collision data.
Data Transformation: Year 2014: Summary of persons injured by borough and vehicle type in accident.
Chart: Column chart comparing injuries by borough by vehicle types. 

nypdvcrashSummary2 <-read.csv("c:/Aarti/Columbia Data Sciences/EDAV/RProject/data/NYPDSummary_ByVehicleType.csv",header=T,sep=",")
require("ggplot2")

#BAR PLOTS
library(MASS)
library(plyr)

(bp1 <- ggplot(data=nypdvcrashSummary2, 
               aes(x=BOROUGH,y=Frequency,fill=factor(Type))) + 
               geom_bar(stat="identity", position=position_dodge()) + 
   ggtitle("Person injuries in 2014 by Vehicle Type ")
   + geom_text(aes(label=Frequency), vjust=0, size=3)
   + theme(plot.title=element_text(size=rel(1), face="bold"))
   + theme(axis.title=element_text(size=15)))