Base-Plots Exploratory Data Analysis

This is an exploratory data analysis on individual household electric power consumption by using the UC Irvine Machine Learning Repository

Tools Used

• R language compiler
• R base graphic devices

Files

• raw data set: Individual household electric power consumption
• CODEBOOK.md: step-by-step on how to get from the raw data to the tidy data set.
• analysis.R: a script able to process and clean the raw data into a fine tidy data set
• plotn.R: the scripts that produces the plots in images folder

Note

In order for the analysis.R script to work, you need to download the raw data set library and extract as *.txt file inside the project root folder.

CODEBOOK

Step by step guide:

Cleaning the Data Set

• Setting the search interval

initialDate <- as.Date("01/02/2007", format = "%d/%m/%Y")
finalDate <- as.Date("02/02/2007", format = "%d/%m/%Y")

• Loading the data into data variable

hpc <- read.table(file = "household_power_consumption.txt", 
                sep=";",
                na.strings = "?",
                header = TRUE,
                colClasses = c('character',
                               'character',
                               'numeric',
                               'numeric',
                               'numeric',
                               'numeric',
                               'numeric',
                               'numeric',
                               'numeric'))

object.size(hpc)
str(hpc$Date)
class(hpc$Date)

• Removing NAs

hpc <- hpc[complete.cases(hpc),]

• Interpreting DATE from STRING character

hpc$Date <- as.Date(hpc$Date, format = "%d/%m/%Y")

head(hpc$Date)

• Subsetting the raw data into date interval

shpc <- subset(hpc, Date >= initialDate & Date <= finalDate)

• Combining Date and Time columns into a vector

dateTime <- paste(shpc$Date, shpc$Time)
dateTime <- setNames(dateTime, "DateTime")
dateTime <- as.POSIXct(dateTime)

• Removing Date and Time from data frame and adding dateTime as substitute

shpc <- shpc[ ,!(names(shpc) %in% c("Date","Time"))]

shpc <- cbind(dateTime, shpc)

• Checking the new tidy data set

head(shpc$Date)
tail(shpc$Date)
str(shpc)

• Removing old dataframe cache

rm(hpc)

• Saving the tidy data set into a csv file

write.csv(shpc, "tidyHouseholdPowerConsumption.csv")

Plotting

Plot 1

• Import csv from the root directory

shpc <- read.table("tidyHouseholdPowerConsumption.csv", 
                  sep=";", 
                  header = TRUE, 
                  colClasses = c('POSIXct',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric'))

• Create histogram & see current device

par(mfrow = c(1, 1))
hist(shpc$Global_active_power, 
     xlab = "Global Active Power (kilowats)", 
     main = "Global Active Power", 
     col = "red") 
dev.cur()

• Saving the plot and closing the device

dev.copy(png, "./images/plot1.png", height = 480, width = 480); 
dev.off()

Plot 2

• Import csv from the root directory

shpc <- read.table("tidyHouseholdPowerConsumption.csv", 
                  sep=";", 
                  header = TRUE, 
                  colClasses = c('POSIXct',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric'))

dateTime <- as.POSIXct(shpc$dateTime) 

• Generate plot

par(mfrow = c(1, 1))
with(shpc, plot(Global_active_power ~ dateTime, 
                type = "l", 
                main = "Global Active Power", 
                xlab = "", 
                ylab = "Global Active Power (kilowats)"))
                

• Saving the plot and closing the device

dev.copy(png, "./images/plot2.png", height = 480, width = 480)
dev.off()

Plot 3

• Import csv from the root directory

shpc <- read.table("tidyHouseholdPowerConsumption.csv", 
                  sep=";", 
                  header = TRUE, 
                  colClasses = c('POSIXct',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric'))

• Setting main variables

dateTime <- as.POSIXct(shpc$dateTime) 
sub1 <- shpc$Sub_metering_1
sub2 <- shpc$Sub_metering_2
sub3 <- shpc$Sub_metering_3

• Plot

par(mfrow = c(1, 1))
with(shpc, {
    plot(sub1 ~ dateTime, type = "l", ylab = "Global Active Power (kW)", xlab = "")
    lines(sub2 ~ dateTime, col = "red")
    lines(sub3 ~ dateTime, col = "blue")
})
legend("topright", col = c("black", "red", "blue"), lwd = 1, 
       c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))

• Saving file

dev.copy(png, file="./images/plot3.png", height=480, width=480)
dev.off()

Plot 4

• Import csv from the root directory

shpc <- read.table("tidyHouseholdPowerConsumption.csv", 
                  sep=";", 
                  header = TRUE, 
                  colClasses = c('POSIXct',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric',
                                 'numeric'))

• Setting variables

dateTime <- as.POSIXct(shpc$dateTime) 
sub1 <- shpc$Sub_metering_1
sub2 <- shpc$Sub_metering_2
sub3 <- shpc$Sub_metering_3

• Plotting

par(mar = c(4, 4, 2, 1), mfrow = c(2, 2))
with(shpc, {
    plot(Global_active_power~dateTime, 
         type = "l", 
         ylab = "Global Active Power (kW)", 
         xlab = "")
    
    plot(Voltage ~ dateTime, 
         type = "l", 
         ylab = "Voltage (V)", 
         xlab = "")
    
    plot(sub1 ~ dateTime, 
         type = "l", 
         ylab = "Global Active Power (kW)", 
         xlab = "")
    
    lines(sub2 ~ dateTime, col = 'red')
    lines(sub3 ~ 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 (kW)",
         xlab = "")
})

• Saving file

dev.copy(png, file = "./images/plot4.png", height = 480, width = 480)
dev.off()