plot1.r

## Set the path to the data directory
print(dir.data <- paste0(getwd(),"/"))

## Make a variable to hold the path to the file we want to import
print(path.abs.data.src <- paste0(
        dir.data
        ,"household_power_consumption.txt"
    ))

## Confirm we have downloaded the data properly
stopifnot(file.exists(path.abs.data.src))

## Import the data to R
head(power.consumption <- read.table(
    path.abs.data.src
    ,sep = ";"
    ,header = TRUE
    ,na.string = "?"
    ))

## Briefly explore to see how the data imported
str(power.consumption)
summary(power.consumption)

## Convert the dates to actual dates
power.consumption$DateTime <- strptime(paste(power.consumption$Date,power.consumption$Time), format = "%d/%m/%Y %H:%M:%S")
power.consumption$DateAsDate <- as.Date(power.consumption$Date, format = "%d/%m/%Y")

## Check the structure post conversion
str(power.consumption)

## Limit to the data we want to plot
power.consumption.limit <- subset(power.consumption
    ,power.consumption$DateAsDate == as.Date("2007-02-01")
        | power.consumption$DateAsDate == as.Date("2007-02-02")
    )

## Confirm our limitations worked
print(unique(power.consumption.limit$DateAsDate))

## See the list of named (red) colors available.  Useful for development
# print(grep("^red"
#     ,colors()
#     ,ignore.case = TRUE
#     , value = TRUE
#     )
# )

## Make the actual plot
png("plot1.png"
    ,width = 480
    ,height = 480
    ,units = "px"
    )
hist(power.consumption.limit$Global_active_power
    ,main = "Global Active Power"
    ,xlab = "Global Active Power (kilowatts)"
    ,col = "red"
    )
dev.off()