plot5.R.txt

library(data.table)
library(ggplot2)

#LoadData : Load NEI and SCC data into global variables if not already present.
#           These variables are then accessed by plot functions.
#           NEI and SCC are loaded as data.table class.
#           If data files do not exist locally then they are downloaded
#           and unzipped. 
LoadData <- function() {
    
    if (!file.exists("summarySCC_PM25.rds") ||
            !file.exists("Source_Classification_Code.rds")) {
        
        if (!file.exists("FNEI_data.zip")) {
            print("Downloading FNEI_data.zip ...")
            download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip", 
                          "FNEI_data.zip", mode="wb")
            unzip("FNEI_data.zip")
        }
    }
    
    #Note: NEI and SCC are set in global environment
    if (!exists("NEI")) {
        print("Loading NEI data ...")
        NEI <<- as.data.table(readRDS("summarySCC_PM25.rds"))
    }
    if (!exists("SCC")) {
        print("Loading SCC data ...")
        SCC <<- as.data.table(readRDS("Source_Classification_Code.rds"))
    }
}


#plot5:     Plots a graph showing PM 2.5 emission from all
#           motor vehicles in Baltimore MD
plot5 <- function () {
    
    LoadData() #NEI & SCC are now in global environment
    
    # Links:
    #   http://www.epa.gov/air/emissions/basic.htm
    #   http://www.epa.gov/air/emissions/index.htm
    #   http://www.epa.gov/cgi-bin/broker?polchoice=PM&_debug=0&_service=data&_program=dataprog.national_1.sas
    # Studying the links above it is understood that we need to grep
    # "Mobile Sources" from SCC level one and ON-ROAD point types from NEI
    
    scc.mobile <- grepl("mobile", SCC$SCC.Level.One, ignore.case=TRUE)
    scc <- SCC[scc.mobile,]$SCC
    nei <- NEI[(fips == "24510") & (SCC %in% scc) & (type=="ON-ROAD"), 
                sum(Emissions), by=year]
    setnames(nei, 2, "total.emissions")
    
    #plot the data
    plot(nei$year, nei$total.emissions, 
         type="b", yaxt="n", xaxt="n", pch=20,
         xlab="Year", ylab="Emissions (in tons)",
         main="Motor vehicles PM 2.5 emissions in Baltimore")
    round.by <- 1
    axis(2, at=seq(0, 300, 100), labels=format(as.double(seq(0, 300, 100)), nsmall=0))
    axis(1, at=nei$year, labels=nei$year)
    text(nei$year, nei$total.emissions, 
         round(nei$total.emissions/round.by, 2), 
         cex=0.6, pos=c(4,2,4,2))
    
    #save the plot to png
    dev.copy(png, file="plot5.png")
    dev.off()
    
    #return the data to the caller
    nei
}

plot5()