1、G G P L O T 2G A L L E R Yggplot2 gallery109Contentsgeom_abline3geom_area10geom_bar10geom_bin2d25geom_blank27geom_boxplot29geom_contour45geom_crossbar45geom_density45geom_density2d46geom_dotplot46geom_errorbar58geom_errorbarh63geom_freqpoly65geom_hex68geom_histogram68geom_hline96geom_jitter100geom_l

2、ine106geom_linerange121geom_map126geom_path128geom_point145geom_pointrangegeom_polygon15159geom_quantile161geom_raster161geom_rect165geom_ribbon65geom_rug171geom_segment174geom_smooth179geom_step181geom_text185geom_tile196geom_violin206geom_vline220geom_abline# Name: geom_abline# Title: Line specifi

3、ed by slope and intercept. # Aliases: geom_abline# * Examplesp - qplot(wt, mpg, data = mtcars) # Fixed slopes and interceptsp + geom_abline() # Cant see it - outside the range of thedata3530mpg252015102345wt p + geom_abline(intercept = 20)3530mpg252015102345wtp + geom_abline(intercept = 37, slope =

4、-5)wt-5.344#37.285# Calculate slope and intercept of line of best fitcoef(lm(mpg wt, data = mtcars)# (Intercept)3530mpg252015102345wt p + geom_abline(intercept = 10, colour = red, size = 2)3530mpg252015102345wt# See ?stat_smooth for fitting smooth models to data p + stat_smooth(method=lm, se=FALSE)3

5、53025mpg2015102345wt# Slopes and intercepts as datap - ggplot(mtcars, aes(x = wt, y=mpg), . cyl) + geom_point() df - data.frame(a=rnorm(10, 25), b=rnorm(10, 0)p + geom_abline(aes(intercept=a, slope=b), data=df)3530mpg252015102345wt# Slopes and intercepts from linear modellibrary(plyr)coefs - ddply(m

6、tcars, .(cyl), function(df) m - lm(mpg wt, data=df)data.frame(a = coef(m)1, b = coef(m)2)str(coefs)# data.frame: 3 obs. of3 variables: #$ cyl: num4 6 8#$ a: num39.6 28.4 23.9#$ b: num-5.65 -2.78 -2.19p + geom_abline(data=coefs, aes(intercept=a, slope=b)3530mpg252015102345wt# Its actually a bit easie

7、r to do this with stat_smooth p + geom_smooth(aes(group=cyl), method=lm)3530mpg252015102345wt p + geom_smooth(aes(group=cyl), method=lm, fullrange=TRUE)30mpg201002345wt# With coordinate transformsp + geom_abline(intercept = 37, slope = -5) + coord_flip()5wt432101520253035mpg5243 p + geom_abline(inte

8、rcept = 37, slope = -5) + coord_polar() 302520mpg15wtgeom_area# Name: geom_area# Title: Area plot.# Aliases: geom_area # * Examples# see geom_ribbongeom_bar# Name: geom_bar# Title: Bars, rectangles with bases on x-axis # Aliases: geom_bar# * Examples # No test:# Generate datac - ggplot(mtcars, aes(f

9、actor(cyl) c + geom_bar()count1050468factor(cyl) c + geom_bar(width=.5)count1050468factor(cyl) c + geom_bar() + coord_flip()8factor(cyl)640510count c + geom_bar(fill=white, colour=darkgreen)count1050468factor(cyl)# Use qplotqplot(factor(cyl), data=mtcars, geom=bar)count1050468factor(cyl) qplot(facto

10、r(cyl), data=mtcars, geom=bar, fill=factor(cyl)10factor(cyl)count46850468factor(cyl)# Stacked bar chartsqplot(factor(cyl), data=mtcars, geom=bar, fill=factor(vs)10countfactor(vs)0150468factor(cyl) qplot(factor(cyl), data=mtcars, geom=bar, fill=factor(gear)10factor(gear)count34550468factor(cyl)# Stac

11、ked bar charts are easy in ggplot2, but not effective visually,# particularly when there are many different things being stackedggplot(diamonds, aes(clarity, fill=cut) + geom_bar()10000count5000cutFair GoodVery Good Premium Ideal0I1SI2SI1VS2VS1VVS2 VVS1IFclarity ggplot(diamonds, aes(color, fill=cut)

12、 + geom_bar() + coord_flip()JIHcutcolorGFair GoodVery Good Premium IdealFED0300060009000count# Faceting is a good alternative:ggplot(diamonds, aes(clarity) + geom_bar() +facet_wrap( cut)FairGoodVery GoodPremiumIdeal50004000300020001000count0500040003000200010000I1 SI2 SI1VS2VS1VVSV2VS1IFI1 SI2 SI1VS

13、2VS1VVSV2VS1IFclarity# If the x axis is ordered, using a line instead of bars is # possibility:ggplot(diamonds, aes(clarity) +geom_freqpoly(aes(group = cut, colour = cut)another50004000count3000200010000I1SI2SI1VS2VS1VVS2 VVS1IFclaritycutFair GoodVery Good Premium Ideal# Dodged bar chartsggplot(diam

14、onds, aes(clarity, fill=cut) + geom_bar(position=dodge)50004000count30002000cutFair GoodVery Good Premium Ideal10000I1SI2SI1VS2VS1VVS2 VVS1IFclarity# compare withggplot(diamonds, aes(cut, fill=cut) + geom_bar() +facet_grid(. clarity)IFVS1VVS2VVS1VS2SI1SI2I150004000count30002000cutFair GoodVery Good

15、Premium Ideal10000VFGaeiProryoredGmIodioeudamVFGlaeiProryoredGmIodioeudamVFGlaePiroryoredGmIodioeudamVFGlaeiProryoredGmIodioeudamVFGlaeiProryoredGmIodioeudamFVGlaePiorryoredGmIodioeudamVFGlaePiorryoredGmIodioeudamVFGlaeiProryoredGmIodioeudamlcut# But again, probably better to use frequency polygons

16、instead:ggplot(diamonds, aes(clarity, colour=cut) +geom_freqpoly(aes(group = cut)50004000count3000200010000I1SI2SI1VS2VS1VVS2 VVS1IFclaritycutFair GoodVery Good Premium Ideal# Often we dont want the height of the bar to represent the # count of observations, but the sum of some other variable. # For

17、 example, the following plot shows the number of diamonds # of each colourqplot(color, data=diamonds, geom=bar)9000count600030000DEFGHIJcolor# If, however, we want to see the total number of carats in # we need to weight by the carat variableeach colourqplot(color, data=diamonds, geom=bar, weight=ca

18、rat, ylab=carat)7500carat500025000DEFGHIJcolor# A bar chart used to display meansmeanprice - tapply(diamonds$price, diamonds$cut, mean)cut - factor(levels(diamonds$cut), levels = levels(diamonds$cut) qplot(cut, meanprice)46004400meanprice4200400038003600FairGoodVery GoodPremiumIdealcut qplot(cut, me

19、anprice, geom=bar, stat=identity)4000meanprice3000200010000FairGoodVery GoodPremiumIdealcut qplot(cut, meanprice, geom=bar, stat=identity, fill = I(grey50)4000meanprice3000200010000FairGoodVery GoodPremiumIdealcut# Another stacked bar chart examplek - ggplot(mpg, aes(manufacturer, fill=class) k + ge

20、om_bar()30class2seater compactcount20midsizeminivan pickup subcompact suv100audcihevrodleotdgefordhondhayundajieelapnd rovlinercomlnercunryissapnontiascubartuoyvootlakswagenmanufacturer# Use scales to change aesthetics defaults k + geom_bar() + scale_fill_brewer()30class2seater compactcount20midsize

21、minivan pickup subcompact suv100audcihevrodleotdgefordhondhayundajieelapnd rovlinecr omlnercunryissapnontiascubartuoyvootlakswagenmanufacturerk + geom_bar() + scale_fill_grey()30class2seater compactcount20midsizeminivan pickup subcompact suv100audcihevrodleotdgefordhondhayundajieelapnd rovlinecr oml

22、nercunryissapnontiascubartuoyvootlakswagenmanufacturer# To change plot order of class varible # use factor() to change order of levelsmpg$class - factor(mpg$class, levels = c(midsize,minivan,suv, compact, 2seater, subcompact, pickup) m - ggplot(mpg, aes(manufacturer, fill=class)m + geom_bar()30class

23、midsize minivancount20suvcompact 2seater subcompact pickup100audcihevrodleotdgefordhondhayundajieelapnd rovliencr omlnercunryissapnontiascubartuoyvootlakswagenmanufacturer # End(No test)geom_bin2d# Name: geom_bin2d# Title: Add heatmap of 2d bin counts. # Aliases: geom_bin2d# * Examplesd - ggplot(dia

24、monds, aes(x = x, y = y) + xlim(4,10) + ylim(4,10) d + geom_bin2d()108count50004000y3000200010006446810x d + geom_bin2d(binwidth = c(0.1, 0.1)108county200010006446810x # See ?stat_bin2d for more examplesgeom_blank# Name: geom_blank# Title: Blank, draws nothing. # Aliases: geom_blank# * Examplesqplot

25、(length, rating, data = movies, geom = blank)10.07.5rating5.02.5010002000300040005000length# Nothing to see here!# Take the following scatter plota - ggplot(mtcars, aes(x = wt, y = mpg), . cyl) + geom_point() # Add to that some lines with geom_abline()df - data.frame(a = rnorm(10, 25), b = rnorm(10,

26、 0)a + geom_abline(aes(intercept = a, slope = b), data = df)3530mpg252015102345wt# Suppose you then wanted to remove the geom_point layer # If you just remove geom_point, you will get an error b - ggplot(mtcars, aes(x = wt, y = mpg)# Not run: b + geom_abline(aes(intercept = a, slope = b),# Switching

27、 to geom_blank() gets the desired plotc - ggplot(mtcars, aes(x = wt, y = mpg) + geom_blank() c + geom_abline(aes(intercept = a, slope = b), data = df)data = df)3530mpg252015102345wtgeom_boxplot# Name: geom_boxplot# Title: Box and whiskers plot. # Aliases: geom_boxplot# * Examples # No test:p - ggplo

28、t(mtcars, aes(factor(cyl), mpg) p + geom_boxplot()3530mpg25201510468factor(cyl) qplot(factor(cyl), mpg, data = mtcars, geom = boxplot)3530mpg25201510468factor(cyl) p + geom_boxplot() + geom_jitter()3530mpg25201510468factor(cyl) p + geom_boxplot() + coord_flip()8factor(cyl)64101520253035mpgqplot(fact

29、or(cyl), mpg, data = mtcars, geom = boxplot) +coord_flip()8factor(cyl)64101520253035mpgp + geom_boxplot(notch = TRUE)# Warning:notch went outside hinges.Try setting notch=FALSE. # Warning:notch went outside hinges.Try setting notch=FALSE.3530mpg25201510468factor(cyl)p + geom_boxplot(notch = TRUE, no

30、tchwidth = .3)# Warning:notch went outside hinges.Try setting notch=FALSE. # Warning:notch went outside hinges.Try setting notch=FALSE.3530mpg25201510468factor(cyl) p + geom_boxplot(outlier.colour = green, outlier.size = 3)3530mpg25201510468factor(cyl)# Add aesthetic mappings# Note that boxplots are

31、 automatically dodged when any aesthetic is # a factorp + geom_boxplot(aes(fill = cyl)353025cyl8mpg7652041510468factor(cyl) p + geom_boxplot(aes(fill = factor(cyl)353025factor(cyl)mpg468201510468factor(cyl) p + geom_boxplot(aes(fill = factor(vs)353025mpgfactor(vs)01201510468factor(cyl) p + geom_boxp

32、lot(aes(fill = factor(am)353025factor(am)mpg01201510468factor(cyl)# Set aesthetics to fixed valuep + geom_boxplot(fill = grey80, colour = #3366FF)3530mpg25201510468factor(cyl)qplot(factor(cyl), mpg, data = mtcars, geom = boxplot,colour = I(#3366FF)3530mpg25201510468factor(cyl)# Scales vs. coordinate

33、 transforms -# Scale transformations occur before the boxplot statistics # Coordinate transformations occur afterwards. Observe the # number of outliers.library(plyr) # to access round_anym - ggplot(movies, aes(y = votes, x = rating, group = round_any(rating, 0.5)m + geom_boxplot()# Warning: positio

34、n_dodge requires constant width: output may be incorrectare computed. effect on the150000votes1000005000002.55.07.510.0ratingm + geom_boxplot() + scale_y_log10()# Warning:position_dodge requires constant width:output may be incorrectvotes100001002.55.07.510.0ratingm + geom_boxplot() + coord_trans(y

35、= log10)# Warning:position_dodge requires constant width:output may be incorrect1200008000040000votes2.55.07.5ratingm + geom_boxplot() + scale_y_log10() + coord_trans(y = log10)# Warning:position_dodge requires constant width:output may be incorrect10000votes1002.55.07.5rating# Boxplots with continu

36、ous x:# Use the group aesthetic to group observations in boxplotsqplot(year, budget, data = movies, geom = boxplot)# Warning:Removed 53573 rows containing non-finite values (stat_boxplot).2.0e+081.5e+08budget1.0e+085.0e+070.0e+001925195019752000yearqplot(year, budget, data = movies, geom = boxplot, group = round_any(year, 10, floor)# Warning:Removed 53573 rows containing non-finite values (stat_boxplot).# Warning:position_dodge requires constant width:outputmay be incorrect2.0e+081.5e+08budget1.0e+085.0e+070.0e+00190019251950197