R1 - Revision history

GethinWilliams: /* Packages */

2014-12-10T17:06:03Z

Packages

2014-12-10T17:03:49Z

Packages

2014-11-04T14:42:03Z

Standard Graphics: A taster

2014-11-03T16:28:27Z

Standard Graphics: A taster

2014-11-03T16:24:35Z

2014-03-07T12:15:13Z

Protected "R1" ([edit=sysop] (indefinite) [move=sysop] (indefinite))

2014-03-07T12:14:29Z

Unprotected "R1"

2014-03-07T12:11:02Z

Changed protection level for "R1" ([edit=sysop] (indefinite) [move=sysop] (indefinite))

2014-03-07T12:10:06Z

Changed protection level for "R1" ([edit=autoconfirmed] (indefinite) [move=autoconfirmed] (indefinite))

2014-03-03T12:08:54Z

Suggested Exercises

@@ Line 314: / Line 314: @@
 > library(googleVis)
 </source>
 =Reading Data from File=

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 Listed at http://cran.r-project.org/
-Let's install the '''multicore''' package, that will give us access to functions within R which will run on the multiple processors which we often find in our computers these days:
+Let's install the '''GoogleVis''' package, that provides an interface between R and Google Charts.  Google Charts offer interactive charts which can be embedded into web pages. The best known of these charts is probably the Motion Chart, popularised by Hans Rosling in his TED talks.  (See http://cran.r-project.org/web/packages/googleVis/vignettes/googleVis.pdf for more information on this package.)
 <source>
-> install.packages("multicore")
+> install.packages("googleVis")
 </source>
@@ Line 312: / Line 312: @@
 <source>
-> library(multicore)
+> library(googleVis)
 </source>

@@ Line 181: / Line 181: @@
 </gallery>
-There are many more example plots--complete with the R code required to create the plots (at the bottom of the page, after the comments)--on the following web page:
+There are many more example plots--complete with the R code required to create the plots (at the bottom of the page, after the comments)--on the following web pages:
-* http://gallery.r-enthusiasts.com/thumbs.php
+* http://www.sr.bham.ac.uk/~ajrs/R/r-gallery.html
 =Loops=

@@ Line 143: / Line 143: @@
 <source>
 > uk.electricty.sources.2011 <- c(41,29,18,5,4,2,1)
-> names(uk.electricty.sources.2011) <- ("Gas", "Coal", "Nuclear", "Hydro & other", "Wind", "Imports", "Oil")
+> names(uk.electricty.sources.2011) <- c("Gas", "Coal", "Nuclear", "Hydro & other", "Wind", "Imports", "Oil")
 > pie(uk.electricty.sources.2011, main="UK Electricty Generating Mix, 2011", col=rainbow(7))
 </source>

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 If you would prefer to noodle about with some real-world data, you could take a look at:
-* http://www.ukpublicspending.co.uk
+* http://www.theguardian.com/news/datablog/2010/oct/18/historic-government-spending-area#data
 =Writing Faster R Code=

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