Introduction

This assignment #1 submission for Coursera.org course 'Exploratory Data Analysis' uses data from the UC Irvine Machine Learning Repository, a popular repository for machine learning datasets. In particular, the "Individual household electric power consumption Data Set" is used

• Dataset: Electric power consumption [20Mb]

• Description: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.

The following descriptions of the 9 variables in the dataset are taken from the UCI web site:

1. Date: Date in format dd/mm/yyyy
2. Time: time in format hh:mm:ss
3. Global_active_power: household global minute-averaged active power (in kilowatt)
4. Global_reactive_power: household global minute-averaged reactive power (in kilowatt)
5. Voltage: minute-averaged voltage (in volt)
6. Global_intensity: household global minute-averaged current intensity (in ampere)
7. Sub_metering_1: energy sub-metering No. 1 (in watt-hour of active energy). It corresponds to the kitchen, containing mainly a dishwasher, an oven and a microwave (hot plates are not electric but gas powered).
8. Sub_metering_2: energy sub-metering No. 2 (in watt-hour of active energy). It corresponds to the laundry room, containing a washing-machine, a tumble-drier, a refrigerator and a light.
9. Sub_metering_3: energy sub-metering No. 3 (in watt-hour of active energy). It corresponds to an electric water-heater and an air-conditioner.

CodeBook

The data transformation applied on all the four R scripts are almost identical and listed out here:

1. Reading the Household power consumption dataset file from the zipped file with Headers
2. Renaming variable names to improve readability of code
3. Create a subset data.frame retaining observations only for two dates i.e. 2007-02-01 and 2007-02-02
4. Created a new variable to hold the timestamp (date and time) together for the plots
5. Opening the graphic device
6. Generating the plot(s) and appending graphics to it as required with appropriate parameters
7. Closing the graphic device