plot4.R

#set working directory
#reading data
#find column class to read file faster
a <- read.table(file="household_power_consumption.txt",header=TRUE,sep=";",nrows = 5)
classes <- sapply(a,class)

#read the file 
file <- read.table(file="household_power_consumption.txt",header=TRUE,sep=";",nrow=2075259,colClasses = classes,na.strings = "?")

#change the date which was factor to date class
file$Date <- as.Date(file$Date,"%d/%m/%Y")

#subset required date
data <- file[file$Date >="2007-02-01" & file$Date<="2007-02-02",]

#format both date and time in combination,also paste convert the time of factor class to
#character class and strptime change it to time class

x <- strptime(paste(data$Date,data$Time),"%Y-%m-%d %H:%M:%S")

#-----------------------------------------------------------------------------------------
#initialise png graphics
# no need for width and height argument by default it is 480p both
png("plot4.png")

#set 2 column and 2 row using mfrow for 4 graphs and choose margin using mar
par(mfrow=c(2,2),mar=c(4,4,4,4))

#1
plot(x,data$Global_active_power,type="l",xlab="",ylab="Global Active Power")
#2
plot(x,data$Voltage,type="l",xlab="datatime",ylab="Voltage")
#3
plot(x,data$Sub_metering_1,type="l",xlab="",ylab="Energy sub metering")
lines(x,data$Sub_metering_2,type="l",col="red")
lines(x,data$Sub_metering_3,type="l",col="blue")
legend("topright",legend=c("sub_metering_1","sub_metering_2","sub_metering_3"),col=c("black","red","blue"),lty=(rep(1,3)),bty="n",cex=0.70)


#4
plot(x,data$Global_reactive_power,type="l",xlab="datatime",ylab="Global_reactive_power")

#turn off graphics
dev.off()