rdpeng/ExData_Plotting1

This assignment uses data from the UC Irvine Machine Learning Repository, a popular repository for machine learning datasets. In particular, we will be using the "Individual household electric power consumption Data Set" which I have made available on the course web site: 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: Date: Date in format dd/mm/yyyy Time: time in format hh:mm:ss Globalactivepower: household global minute-averaged active power (in kilowatt) Globalreactivepower: household global minute-averaged reactive power (in kilowatt) Voltage: minute-averaged voltage (in volt) Globalintensity: household global minute-averaged current intensity (in ampere) Submetering1: 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…