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Exploratory Data Analysis Project 1

The plotx.R files require the power_consumption_data.txt file to be in the working directory.

It reads in the entire contents of the file, so you will need more than ~350MB of free RAM.

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 files that generate each plot will first read in the data, convert the date and time column into an R date-time value, and then overwrite the date column with this. After the date is converted, the data either side of 2007-02-01 - 2007-02-02 is cut off. After this, the plots are generated.

No special plotting libraries are required, only native R plotting functions are used.

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Plotting Assignment 1 for Exploratory Data Analysis

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