plot4.R

## plot4.R
data <- read.csv(file="household_power_consumption.txt", header=T, sep=";", colClasses=c("character", "character", "double", "double", "double", "double", "double", "double", "double"), na.string="?")
data_one_and_two_feb_2007 <- subset(data, Date == "1/2/2007" | Date == "2/2/2007")

#combine date and time
data_one_and_two_feb_2007$DateTime <- as.POSIXct(paste(data_one_and_two_feb_2007$Date, data_one_and_two_feb_2007$Time), format="%d/%m/%Y %H:%M:%S", tz="UTC")

# the plotting frame
par(mfrow=c(2,2))
#first plot
plot(Global_active_power ~ DateTime, data=data_one_and_two_feb_2007, ylab = "Global Active Power", xlab="", type="l", lwd=1)

#second plot
plot(Voltage ~ DateTime, data=data_one_and_two_feb_2007, ylab = "Voltage", xlab="datetime", type="l", lwd=1)

#third plot
plot(Sub_metering_1 ~ DateTime, data=data_one_and_two_feb_2007, ylab = "Energy sub metering", xlab="", type="l")
lines(Sub_metering_2 ~ DateTime, data=data_one_and_two_feb_2007, lwd=1, col="red")
lines(Sub_metering_3 ~ DateTime, data=data_one_and_two_feb_2007, lwd=1, col="blue")
legend(x="topright", legend=c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"), col=c("black", "red", "blue"), lwd=1, bty="n", cex=0.8, text.width=0.8 * strwidth("                 Sub_metering_1"))

#fourth plot
plot(Global_reactive_power ~ DateTime, data=data_one_and_two_feb_2007, xlab="datetime", type="l", lwd=1)

dev.copy(png, filename="plot4.png", width=480, height=480)
dev.off()