The object of this assignment was to reproduce plots provided. Our overall goal here is simply to examine how household energy usage varies over a 2-day period in February, 2007. The task is to reconstruct certain given plots, all of which were constructed using the base plotting system.

The data was retrieved from this source: https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip

Base Plotting System

Plot 1

setwd("C:/Users/Akash Gupta/Desktop/Books/R wrangling/Exploratory data analysis Coursera")

data_full <- read.csv("household_power_consumption.txt", header=T, sep=';', na.strings="?", 
                      nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data1 <- subset(data_full, Date %in% c("1/2/2007","2/2/2007"))
data1$Date <- as.Date(data1$Date, format="%d/%m/%Y")
hist(data1$Global_active_power, main="Global Active Power", 
     xlab="Global Active Power (kilowatts)", ylab="Frequency", col="Red")

png("plot1.png", width=480, height=480)
dev.off()
## png 
##   2

Plot 2

setwd("C:/Users/Akash Gupta/Desktop/Books/R wrangling/Exploratory data analysis Coursera")

data_full <- read.csv("household_power_consumption.txt", header=T, sep=';', na.strings="?", nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data1 <- subset(data_full, Date %in% c("1/2/2007","2/2/2007"))
data1$Date <- as.Date(data1$Date, format="%d/%m/%Y")
datetime <- paste(as.Date(data1$Date), data1$Time)
data1$Datetime <- as.POSIXct(datetime)

## Plot 2
with(data1, {
  plot(Global_active_power~Datetime, type="l",
     ylab="Global Active Power (kilowatts)", xlab="")
  })

dev.copy(png, file="plot2.png", height=480, width=480)
## png 
##   3
dev.off()
## png 
##   2

Plot 3

setwd("C:/Users/Akash Gupta/Desktop/Books/R wrangling/Exploratory data analysis Coursera")

data_full <- read.csv("household_power_consumption.txt", header=T, sep=';', na.strings="?", 
                      nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data1 <- subset(data_full, Date %in% c("1/2/2007","2/2/2007"))
data1$Date <- as.Date(data1$Date, format="%d/%m/%Y")
datetime <- paste(as.Date(data1$Date), data1$Time)
data1$Datetime <- as.POSIXct(datetime)

with(data1, {
  plot(Sub_metering_1~Datetime, type="l",
       ylab="Global Active Power (kilowatts)", xlab="")
  lines(Sub_metering_2~Datetime,col='Red')
  lines(Sub_metering_3~Datetime,col='Blue')
})
legend("topright", col=c("black", "red", "blue"), lty=1, lwd=2, 
       legend=c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))

## Saving to file
dev.copy(png, file="plot3.png", height=480, width=480)
## png 
##   3
dev.off()
## png 
##   2

Plot 4

setwd("C:/Users/Akash Gupta/Desktop/Books/R wrangling/Exploratory data analysis Coursera")

data_full <- read.csv("household_power_consumption.txt", header=T, sep=';', na.strings="?", 
                      nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data1 <- subset(data_full, Date %in% c("1/2/2007","2/2/2007"))
data1$Date <- as.Date(data1$Date, format="%d/%m/%Y")
datetime <- paste(as.Date(data1$Date), data1$Time)
data1$Datetime <- as.POSIXct(datetime)

par(mfrow=c(2,2), mar=c(4,4,2,1), oma=c(0,0,2,0))
with(data1, {
  plot(Global_active_power~Datetime, type="l", 
       ylab="Global Active Power (kilowatts)", xlab="")
  plot(Voltage~Datetime, type="l", 
       ylab="Voltage (volt)", xlab="")
  plot(Sub_metering_1~Datetime, type="l", 
       ylab="Global Active Power (kilowatts)", xlab="")
  lines(Sub_metering_2~Datetime,col='Red')
  lines(Sub_metering_3~Datetime,col='Blue')
  legend("topright", col=c("black", "red", "blue"), lty=1, lwd=2, bty="n",
         legend=c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))
  plot(Global_reactive_power~Datetime, type="l", 
       ylab="Global Rective Power (kilowatts)",xlab="")
})

## Saving to file
dev.copy(png, file="plot4.png", height=480, width=480)
## png 
##   3
dev.off()
## png 
##   2