plot4.R

plot4 <- function(data = 'household_power_consumption.txt') {
  # Takes data from the UC Irvine Machine learning Repository
  # which has the 'Individual household electric power consumption
  # Data Set' and uses the data from 2007-02-01 and 2007-02-02
  # to make 4 plots: Global Active Power over the two days,
  # the voltage over the course of two days, the Energy sub 
  # metering from 3 meters over the course of two days, and
  # the global reactive power over two days. It saves the plot 
  # produced as plot4.png.
  
  # First, read and clean up data file.
  data = read.table(data, header = TRUE, sep = ';', na.strings = '?',
                    colClasses = c('factor', 'factor', 'numeric', 
                                   'numeric', 'numeric', 'numeric',
                                   'numeric', 'numeric', 'numeric'))
  data$Date <- as.Date(data$Date, format = "%d/%m/%Y") #Format date
  
  # Subset data
  date1 <- as.Date("2007-02-01") # Setting the two days we are
  date2 <- as.Date("2007-02-02") # focusing on
  data <- subset(data, data$Date == date1 | data$Date == date2)
  
  # Combine the 'Date' and 'Time' Columns to one new column
  # and convert to POSIXct
  data$DateTime <- as.POSIXct(paste(data$Date, data$Time),
                              format = '%Y-%m-%d %H:%M:%S')
  
  # Plot data and save as png
  png('plot4.png')
  par(mfcol = c(2, 2))
  with(data, {
    plot(DateTime, Global_active_power, xlab = '',
                    ylab = 'Global Active Power (kilowatts)', type = 'n')
    lines(DateTime, Global_active_power)
    plot(DateTime, Sub_metering_1, xlab = '',
                    ylab = 'Energy sub metering', type = 'n')
    lines(DateTime, Sub_metering_1, col = 'black')
    lines(DateTime, Sub_metering_2, col = 'red')
    lines(DateTime, Sub_metering_3, col = 'blue')
    legend('topright', col = c('black', 'red', 'blue'), lty = c(1, 1),
           bty = 'n', legend = c('Sub_metering_1', 'Sub_metering_2', 
                                 'Sub_metering_3'))
    plot(DateTime, Voltage, xlab = 'datetime', type = 'n')
    lines(DateTime, Voltage)
    plot(DateTime, Global_reactive_power, xlab = 'datetime', type = 'n')
    lines(DateTime, Global_reactive_power)
  })
  dev.off()
}