Introduction

This exercise uses data from the UC Irvine Machine Learning Repository, a popular repository for machine learningdatasets. In particular, we will be using the “Individual household electric power consumption Data Set”.

## 'data.frame':    2075259 obs. of  9 variables:
##  $ Date                 : Factor w/ 1442 levels "1/1/2007","1/1/2008",..: 342 342 342 342 342 342 342 342 342 342 ...
##  $ Time                 : Factor w/ 1440 levels "00:00:00","00:01:00",..: 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 ...
##  $ Global_active_power  : num  4.22 5.36 5.37 5.39 3.67 ...
##  $ Global_reactive_power: num  0.418 0.436 0.498 0.502 0.528 0.522 0.52 0.52 0.51 0.51 ...
##  $ Voltage              : num  235 234 233 234 236 ...
##  $ Global_intensity     : num  18.4 23 23 23 15.8 15 15.8 15.8 15.8 15.8 ...
##  $ Sub_metering_1       : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sub_metering_2       : num  1 1 2 1 1 2 1 1 1 2 ...
##  $ Sub_metering_3       : num  17 16 17 17 17 17 17 17 17 16 ...

## [1] "Date"

## 'data.frame':    2075259 obs. of  9 variables:
##  $ Date                 : Date, format: "2006-12-16" "2006-12-16" ...
##  $ Time                 : Factor w/ 1440 levels "00:00:00","00:01:00",..: 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 ...
##  $ Global_active_power  : num  4.22 5.36 5.37 5.39 3.67 ...
##  $ Global_reactive_power: num  0.418 0.436 0.498 0.502 0.528 0.522 0.52 0.52 0.51 0.51 ...
##  $ Voltage              : num  235 234 233 234 236 ...
##  $ Global_intensity     : num  18.4 23 23 23 15.8 15 15.8 15.8 15.8 15.8 ...
##  $ Sub_metering_1       : num  0 0 0 0 0 0 0 0 0 0 ...
##  $ Sub_metering_2       : num  1 1 2 1 1 2 1 1 1 2 ...
##  $ Sub_metering_3       : num  17 16 17 17 17 17 17 17 17 16 ...

Exercise

mieu

December 1, 2015

Introduction

Plot1