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- 1. A Survey of R Graphics<br />June 18 2009<br />R Users<br />Group of LA<br />Michael E. Driscoll<br />Principal, Dataspora<br />mike@dataspora.com<br />
- 2. “The sexy job in the next ten years will be statisticians…”<br />- Hal Varian<br />
- 3.
- 4. Hypothesis<br />(from Jessica Hagy’s thisisindexed.com)<br />
- 5. Munge & Model<br />gdp <- read.csv('gdp.csv')hours <- read.csv('hours.csv')gdp.hours <- merge(hours,gdp)gdp.hours$freetime <- 4380 - gdp.hours$hoursattach(gdp.hours)plot(freetime ~ gdp)m <- lm(freetime ~ gdp,data=gdp.hours)abline(m,col=3,lw=2)pm <- loess(freetime ~ gdp)lines(spline(gdp,fitted(pm)))<br />
- 6. Visualization<br />library(ggplot2)<br />qplot(gdp,freetime,<br />data=gdp.hours,<br />geom=c("point",<br /> "smooth"),<br />span=1)<br />
- 7. basic graphics<br />
- 8. R’s Two Graphics Systems<br />
- 9. plot() graphs objects<br />plot(freetime ~ gdp, <br /> data=gdp.hours)<br />model <- lm(freetime ~ gdp,<br /> data=gdp.hours)<br />abline(model) <br />
- 10. plot() graphs objects<br />abline(model,<br />col="red",<br />lwd=3)<br />
- 11. par sets graphical parameters<br />par(pch=20, <br />cex=5,<br />col="#5050a0BB")<br />RGB hex<br />alpha blending!<br />plot(freetime ~ gdp, data=gdp.hours)<br />help(par)<br />
- 12. par sets graphical parameters<br />parameters<br />for par()<br />pch<br />col<br />adj<br />srt<br />pt.cex<br />graphing functions<br />points()<br />text()<br />xlab()<br />legend()<br />
- 13. Paneling Graphics<br />By setting one parameter in particular, mfrow, we can partition the graphics display to give us a multiple framework in which to panel our plots, rowwise.<br />par(mfrow= c( nrow, ncol))<br />Number of rows<br />Number of columns<br />
- 14. Paneling Graphics<br />par(mfrow=c(2,2))<br />hist(D$wg, main='Histogram',xlab='Weight Gain', ylab ='Frequency', col=heat.colors(14))<br />boxplot(wg.7a$wg, wg.8a$wg, wg.9a$wg, wg.10a$wg, wg.11a$wg, wg.12p$wg, main='Weight Gain', ylab='Weight Gain (lbs)',<br />xlab='Shift', names = c('7am','8am','9am','10am','11am','12pm'))<br />plot(D$metmin,D$wg,main='Met Minutes vs. Weight Gain', xlab='Mets (min)',ylab='Weight Gain (lbs)',pch=2)<br />plot(t1,D2$Intel,type="l",main='Closing Stock Prices',xlab='Time',ylab='Price $')<br />lines(t1,D2$DELL,lty=2)<br />
- 15. Paneling Graphics<br />
- 16. Working with Graphics Devices<br />Starting up a new graphic X11 window<br />x11()<br />To write graphics to a file, open a device, write to it, close.<br />pdf(“mygraphic.pdf”,width=7,height=7) <br />plot(x)<br />dev.off()<br />In Linux, the package “Cairo “ is recommended for a device that renders high-quality vector and raster images (alpha blending!). The command would read Cairo(“mygraphic.pdf”, …<br />Common gotcha: under non-interactive sessions, you should explicitly invoke a print command to send a plot object to an open device. For example <br /> print(plot(x))<br />
- 17. library(ggplot2)<br />
- 18. ggplot2 =grammar of graphics<br />
- 19. ggplot2 =grammar ofgraphics<br />
- 20. Visualizing 50,000 Diamonds with ggplot2<br />
- 21. qplot(carat, price, data = diamonds)<br />
- 22. qplot(log(carat), log(price), data = diamonds)<br />qplot(carat, price, log=“xy”, data = diamonds)<br />OR<br />
- 23. qplot(log(carat), log(price), data = diamonds, <br />alpha = I(1/20))<br />
- 24. qplot(log(carat), log(price), data = diamonds, <br />alpha = I(1/20), colour=color)<br />
- 25. Achieving small multiples with “facets”<br />qplot(log(carat), log(price), data = diamonds, alpha=I(1/20)) + facet_grid(. ~ color)<br />
- 26. old<br />new<br />qplot(color, price/carat, <br />data = diamonds, alpha = I(1/20), geom=“jitter”)<br />qplot(color, price/carat, <br />data = diamonds,<br />geom=“boxplot”)<br />
- 27.
- 28. library(lattice)<br />
- 29. lattice = trellis<br />(source: http://lmdvr.r-forge.r-project.org )<br />
- 30. visualizing six dimensions<br />of MLB pitches with lattice<br />
- 31. xyplot(x ~ y, data=pitch)<br />
- 32. xyplot(x ~ y, groups=type, data=pitch)<br />
- 33. xyplot(x ~ y | type, data=pitch)<br />
- 34. xyplot(x ~ y | type, data=pitch,<br />fill.color = pitch$color,<br />panel = function(x,y, fill.color, …, subscripts) {<br /> fill <- fill.color[subscripts]<br />panel.xyplot(x,y, fill= fill, …) })<br />
- 35. xyplot(x ~ y | type, data=pitch,<br />fill.color = pitch$color,<br />panel = function(x,y, fill.color, …, subscripts) {<br /> fill <- fill.color[subscripts]<br />panel.xyplot(x, y, fill= fill, …) })<br />
- 36. A Story of Two Pitchers<br />Hamels<br />Webb<br />
- 37. list of latticefunctions<br />densityplot(~ speed | type, data=pitch)<br />
- 38. plotting big data<br />
- 39. xyplotwith 1m points = Bad Idea Jeans<br />xyplot(log(price)~log(carat),data=diamonds)<br />
- 40. efficient plotting with hexbinplot<br />hexbinplot(log(price)~log(carat),data=diamonds,xbins=40)<br />
- 41. 100<br />thousand <br />gene measures<br />
- 42. efficient plotting with geneplotter<br />
- 43. beautiful colors with Colorspace<br />library(“Colorspace”)<br />red <- LAB(50,64,64)<br />blue <- LAB(50,-48,-48)<br />mixcolor(10, red, blue)<br />
- 44. R-->web<br />
- 45. LinuxApacheMySQLR<br />http://labs.dataspora.com/gameday<br />
- 46.
- 47.
- 48. Configuring rapache<br />Hello world script<br />setContentType("text/html")<br />png("/var/www/hello.png")<br />plot(sample(100,100),col=1:8,pch=19)<br />dev.off()<br />cat("<html>")<br />cat("<body>")<br />cat("<h1>hello world</h1>")<br />cat('<imgsrc="../hello.png"')<br />cat("</body>")<br />cat("</html>")<br />
- 49. Data Visualization References<br />ggplot2: Elegant Graphics for Data Analysis<br />by Hadley Wickham<br />http://had.co.nz/ggplot2<br />Lattice: Multivariate Data Visualization with R<br />by DeepayanSarkar<br />http://lmdvr.r-forge.r-project.org/<br />

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