plot1.R

# Exploratory Data Analysis
# Course Project 1 (9/13/2015)
#
# Part 1 of 4
#######################################################################################
# 
# Full project description available at: 
#  https://class.coursera.org/exdata-032/human_grading/view/courses/975127/assessments/3/submissions
#
# This project replicates several graphics based on Electric Power Consumption data
# from the UC Irvine Machine Learning Repository.
# 
# The following code provides for downloading and extracting the raw data, loading the
# appropriate data for analysis into R and replicating Plot 1 of this project. The download
# and extract portion includes checks to prevent repeated handling of the large dataset in
# the case that is is already downloaded and/or extracted on the local system.
#
#######################################################################################


## FILE RETRIEVAL AND DATA EXTRACTION
zipfile <- "household_power_consumption.zip"
sourceurl <- paste0("https://d396qusza40orc.cloudfront.net/exdata/data/", zipfile)
datafile <- "household_power_consumption.txt"

# Setup data directory if it is not present
if(!file.exists("data")){dir.create( paste0(getwd(), "/data"))}
try(setwd("./data"), stop("Error: Unable to set working directory."))

# If the datafile is present don't repeat the download and extraction.
if(!file.exists(datafile)){
        # Don't repeat the download if the zip file is found.
        if(!file.exists(zipfile)){
                try(
                        download.file(sourceurl, destfile = paste0("./",zipfile), method = "curl"),
                        stop("Error Unable to download remote zipfile.")
                )
                dateDownloaded <- date()
        }
        # Extract the data from new or existing zipfile
        try(
                unzip(zipfile, files = datafile, list = FALSE, overwrite = TRUE,
                      junkpaths = FALSE, exdir = ".", unzip = "internal",
                      setTimes = FALSE),
                stop("Error: Unable to extract datafile from archive.")
        )
}

## LOAD DATA
electric <- read.table(datafile, colClasses = c(date="character",
                                              time="character", 
                                              global_active_power = "numeric",
                                              global_reactive_power = "numeric",
                                              voltage = "numeric",
                                              global_intensity = "numeric",
                                              sub_metering_1 = "numeric",
                                              sub_metering_2 = "numeric",
                                              sub_metering_3 = "numeric"
                                              ),
                       header=TRUE, sep=";", na.strings=c("?"), stringsAsFactors = FALSE
                     )
setwd("..") # done with data directory

## RETAIN DATA FOR ANALYSIS
selectedDates <- electric[ electric[1]=="1/2/2007" | electric[1]=="2/2/2007",]
rm(electric)

#GENERATE PLOT
# Plot 1 - Global Active Power Histogram
png("plot1.png", width = 480, height = 480, units = "px")
with(selectedDates, hist(Global_active_power, col="red", main = "Global Active Power", xlab = "Global Active Power (kilowatts)", ylab = "Frequency"))
dev.off()