Adding scripts to generate plots and generated PNGs

plot1.R

@@ -0,0 +1,23 @@
+# Load the data
+household_power <- read.csv("household_power_consumption.txt", sep = ";")
+
+# Convert Date strings to Date object
+household_power$Date <- as.Date(household_power$Date, format="%d/%m/%Y")
+
+# Convert Global Active Power to numeric values
+household_power$Global_active_power <- as.numeric(household_power$Global_active_power)
+
+# Filter to data from 2007-02-01 and 2007-02-02
+d <- rbind(subset(household_power, household_power$Date == as.Date("2007-02-01")),
+           subset(household_power, household_power$Date == as.Date("2007-02-02")))
+
+# Make the histogram plot with the filtered data
+hist(d$Global_active_power, 
+     main="Global Active Power", 
+     col="red", 
+     xlab="Global Active Power (kilowatts)", 
+     breaks=24)
+
+# Export plot to PNG
+dev.copy(png, file="plot1.png")
+dev.off()

plot2.R

@@ -0,0 +1,30 @@
+# Load the data
+household_power <- read.csv("household_power_consumption.txt", sep = ";")
+
+# Add DateTime field
+household_power$DateTime <- paste(household_power$Date, household_power$Time)
+
+# Convert Date strings to Date object
+household_power$Date <- as.Date(household_power$Date, format="%d/%m/%Y")
+
+# Convert Time strings to Time object
+household_power$Time <- strptime(household_power$DateTime, 
+                                 format="%d/%m/%Y %H:%M:%OS")
+
+# Convert Global Active Power to numeric values
+household_power$Global_active_power <- as.numeric(household_power$Global_active_power)
+
+# Filter to data from 2007-02-01 and 2007-02-02
+d <- rbind(subset(household_power, household_power$Date == as.Date("2007-02-01")),
+           subset(household_power, household_power$Date == as.Date("2007-02-02")))
+
+# Create the line graph
+plot(d$Time, 
+     d$Global_active_power, 
+     type="l", 
+     ylab="Global Active Power (kilowatts)", 
+     xlab="")
+
+# Export plot to PNG
+dev.copy(png, file="plot2.png")
+dev.off()

plot3.R

@@ -0,0 +1,39 @@
+# Load the data
+household_power <- read.csv("household_power_consumption.txt", sep = ";")
+
+# Add DateTime field
+household_power$DateTime <- paste(household_power$Date, household_power$Time)
+
+# Convert Date strings to Date object
+household_power$Date <- as.Date(household_power$Date, format="%d/%m/%Y")
+
+# Convert Time strings to Time object
+household_power$Time <- strptime(household_power$DateTime, 
+                                 format="%d/%m/%Y %H:%M:%OS")
+
+# Convert Sub Metering strings to numeric values
+household_power$Sub_metering_1 <- as.numeric(household_power$Sub_metering_1)
+household_power$Sub_metering_2 <- as.numeric(household_power$Sub_metering_2)
+household_power$Sub_metering_3 <- as.numeric(household_power$Sub_metering_3)
+
+# Filter to data from 2007-02-01 and 2007-02-02
+d <- rbind(subset(household_power, household_power$Date == as.Date("2007-02-01")),
+           subset(household_power, household_power$Date == as.Date("2007-02-02")))
+
+# Create the plot
+plot(d$Time, d$Sub_metering_1, type="n", ylab="Energy sub metering", xlab="")
+
+# Add the lines to the plot
+lines(d$Time, d$Sub_metering_1)
+lines(d$Time, d$Sub_metering_2, col="red")
+lines(d$Time, d$Sub_metering_3, col="blue")
+
+# Add the legend to the plot
+legend("topright", 
+       legend=c("Sub_metering1", "Sub_metering2", "Sub_metering3"), 
+       col=c("black", "red", "blue"), 
+       lty=1)
+
+# Export plot to PNG
+dev.copy(png, file="plot3.png")
+dev.off()

plot4.R

@@ -0,0 +1,76 @@
+# Load the data
+household_power <- read.csv("household_power_consumption.txt", sep = ";")
+
+# Add DateTime field
+household_power$DateTime <- paste(household_power$Date, household_power$Time)
+
+# Convert Date strings to Date object
+household_power$Date <- as.Date(household_power$Date, format="%d/%m/%Y")
+
+# Convert Time strings to Time object
+household_power$Time <- strptime(household_power$DateTime, 
+                                 format="%d/%m/%Y %H:%M:%OS")
+
+# Convert Sub Metering strings to numeric values
+household_power$Sub_metering_1 <- as.numeric(household_power$Sub_metering_1)
+household_power$Sub_metering_2 <- as.numeric(household_power$Sub_metering_2)
+household_power$Sub_metering_3 <- as.numeric(household_power$Sub_metering_3)
+
+# Convert Global Active Power strings to numeric values
+household_power$Global_active_power <- as.numeric(household_power$Global_active_power)
+
+# Convert Global Active Power strings to numeric values
+household_power$Global_reactive_power <- as.numeric(household_power$Global_reactive_power)
+
+
+# Convert Voltage strings to numeric values
+household_power$Voltage <- as.numeric(household_power$Voltage)
+
+# Filter to data from 2007-02-01 and 2007-02-02
+d <- rbind(subset(household_power, household_power$Date == as.Date("2007-02-01")),
+           subset(household_power, household_power$Date == as.Date("2007-02-02")))
+
+# Create the grid for the plots
+par(mfrow=c(2, 2))
+
+# Create plot #1: Global Active Power by Day
+plot(d$Time, 
+     d$Global_active_power, 
+     type="l", 
+     ylab="Global Active Power (kilowatts)", 
+     xlab="")
+
+# Create plot #2: Voltage by Day
+plot(d$Time, 
+     d$Voltage, 
+     type="l", 
+     ylab="Voltage", 
+     xlab="datetime",
+     yaxt="none")
+axis(2, seq(234, 246, 4))
+
+# Create plot #3: Energy sub metering by Day
+plot(d$Time, d$Sub_metering_1, type="n", ylab="Energy sub metering", xlab="")
+
+# Add the lines to the plot
+lines(d$Time, d$Sub_metering_1)
+lines(d$Time, d$Sub_metering_2, col="red")
+lines(d$Time, d$Sub_metering_3, col="blue")
+
+# Add the legend to the plot
+legend("topright", 
+       legend=c("Sub_metering1", "Sub_metering2", "Sub_metering3"), 
+       col=c("black", "red", "blue"), 
+       lty=1,
+       bty="n")
+
+# Create plot #4: Global Reactive Power by Daytime
+plot(d$Time, 
+     d$Global_reactive_power, 
+     type="l", 
+     ylab="Global_reactive_power", 
+     xlab="datetime")
+
+# Export plot to PNG
+dev.copy(png, file="plot4.png")
+dev.off()