snsergio/eda

Exploratory Data Analysis repository

Coursera EDA Project 1

Exploratory Data Analysis

Introduction

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:

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:

• Date: Date in format dd/mm/yyyy
• Time: time in format hh:mm:ss
• Global_active_power: household global minute-averaged active power (in kilowatt)
• Global_reactive_power: household global minute-averaged reactive power (in kilowatt)
• Voltage: minute-averaged voltage (in volt)
• Global_intensity: household global minute-averaged current intensity (in ampere)
• 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).
• 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.
• 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.

Code to generate the required graphics on Project1 assumes the original household_power_consumption.txt file is available at "WORKING DIRECTORY" and the output .png file will be written at the same directory (Working Directory).

Code and output files are:

• input file: household_power_consumption.txt
• code: plot1.R output file: plot1.png
• code: plot2.R output file: plot2.png
• code: plot3.R output file: plot3.png
• code: plot4.R output file: plot4.png