Skip to content

Latest commit

 

History

History
79 lines (51 loc) · 3.11 KB

README.md

File metadata and controls

79 lines (51 loc) · 3.11 KB

You are reading the README.md file in the plotting GitHub repository associated with Russ Robbins. This repository stores the files that plot electricity consumption. Please see below.

Example - Plotting using Base R

This example uses data from the UC Irvine Machine Learning Repository. The data set is the "Individual household electric power consumption" data set.

Data

  • 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.

  • The dataset has 2,075,259 rows and 9 columns.

  • I used data from the dates 2007-02-01 and 2007-02-02.

Plotting

Goal: Examine how household energy usage varies over a 2-day period in February, 2007.

Initially, I forked and cloned the following GitHub repository: https://github.com/rdpeng/ExData_Plotting1

For each plot I

  • Constructed the plot and saved it to a PNG file with a width of 480 pixels and a height of 480 pixels.

  • Named each of the plot files as plot1.png, plot2.png, etc.

  • Created a separate R code file (plot1.R, plot2.R, etc.) that constructs the corresponding plot, i.e. code in plot1.R constructs the plot1.png plot.

  • Added the PNG file and R code file to your git repository

##Results

Plot 1

Plot 2

Plot 3

Plot 4