getPowerConsumptionSampleData.R

# assignment 1
# read data file
powerConsumption <- read.table("household_power_consumption.txt", 
                               header = TRUE, 
                               sep = ';', 
                               na.strings = "?", 
                               colClasses=c("character","character","numeric","numeric","numeric","numeric","numeric","numeric","numeric"))

# extract just the two days of interest
pwrSampleDays <- powerConsumption[(powerConsumption$Date == "1/2/2007") | (powerConsumption$Date == "2/2/2007"),]

# paste together Date and Time fields to new variable "dateTime" for graphing time series data
pwrSampleDays$dateTime <- paste(pwrSampleDays$Date, pwrSampleDays$Time)
pwrSampleDays$Date <- as.Date(pwrSampleDays$Date, format = "%d/%m/%Y")
pwrSampleDays$dateTime <- strptime(pwrSampleDays$dateTime, format = "%d/%m/%Y %H:%M:%S")

str(pwrSampleDays) # check it looks OK :)

# 'data.frame':  2880 obs. of  10 variables:
#   $ Date                 : Date, format: "2007-02-01" "2007-02-01" "2007-02-01" "2007-02-01" ...
# $ Time                 : chr  "00:00:00" "00:01:00" "00:02:00" "00:03:00" ...
# $ Global_active_power  : num  0.326 0.326 0.324 0.324 0.322 0.32 0.32 0.32 0.32 0.236 ...
# $ Global_reactive_power: num  0.128 0.13 0.132 0.134 0.13 0.126 0.126 0.126 0.128 0 ...
# $ Voltage              : num  243 243 244 244 243 ...
# $ Global_intensity     : num  1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1 ...
# $ Sub_metering_1       : num  0 0 0 0 0 0 0 0 0 0 ...
# $ Sub_metering_2       : num  0 0 0 0 0 0 0 0 0 0 ...
# $ Sub_metering_3       : num  0 0 0 0 0 0 0 0 0 0 ...
# $ dateTime             : POSIXlt, format: "2007-02-01 00:00:00" "2007-02-01 00:01:00" "2007-02-01 00:02:00" "2007-02-01 00:03:00" ...