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Search found 65 results on 3 pages for 'ggplot'.

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• How do I draw an arrow on a histogram drawn using ggplot2?

  - by jon

  Here is dataset: set.seed(123) myd <- data.frame (class = rep(1:4, each = 100), yvar = rnorm(400, 50,30)) require(ggplot2) m <- ggplot(myd, aes(x = yvar)) p <- m + geom_histogram(colour = "grey40", fill = "grey40", binwidth = 10) + facet_wrap(~class) + theme_bw( ) p + opts(panel.margin=unit(0 ,"lines")) I want to add labels to bars which each subject class fall into and produce something like the post-powerpoint processed graph. Is there way to do this within R ? ...... Edit: we can think of different pointer such as dot or error bar, if arrow is not impossible Let's say the following is subjects to be labelled: class name yvar 2 subject4 104.0 3 subject3 8.5 3 subject1 80.0 4 subject2 40.0 4 subject1 115.0 classd <- data.frame (class = c(2,3,3,4,4), name = c ("subject4", "subject3", "subject1", "subject2", "subject1"), yvar = c(104.0, 8.5,80.0,40.0, 115.0))

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• plot only x and y axis (no box) in ggplot2

  - by Tyler Rinker

  The convention of some journals is to show only the x and y axis in a plot not a box around the entire plot area. How can I achieve this in ggplot2? I tried theme_minimal_cb_L from HERE but it seems to erase the entire box around the plot (does not leave the x and y axis) as seen here: Here's the code I'm using: dat <- structure(list(x = c(0.7, 0.75, 0.8, 0.85, 0.9, 0.95, 1, 1.05, 1.1, 1.15, 1.2, 1.25, 1.3), y1 = c(34, 30, 26, 23, 21, 19, 17, 16, 15, 13, 12, 12, 11), y2 = c(45, 39, 34, 31, 28, 25, 23, 21, 19, 17, 16, 15, 14)), .Names = c("x", "y1", "y2"), row.names = c(NA, -13L), class = "data.frame") library(reshape2); library(ggplot2) dat2 <- melt(dat, id='x') theme_minimal_cb_L <- function (base_size = 12, base_family = "", ...){ modifyList (theme_minimal (base_size = base_size, base_family = base_family), list (axis.line = element_line (colour = "black"))) } ggplot(data=dat2, aes(x=x, y=value, color=variable)) + geom_point(size=3) + geom_line(size=.5) + theme_minimal_cb_L()

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• geom_rect and NULL

  - by csgillespie

  I've been looking at the geom_rect example in section 5.10 of the ggplot2 book and don't understand the purpose of the NULL's in the aes function. For example, using the mpg data: g = ggplot(data=mpg, aes(x=displ, y=hwy)) + geom_point() #Produces a plot with a transparent filled region g + geom_rect(aes(NULL, NULL), alpha=0.1,xmin=5, xmax=7, ymin=10, ymax=45, fill="blue") #Solid filled region (v0.9) or nothing in v0.8 g + geom_rect(alpha=0.1,xmin=5, xmax=7, ymin=10, ymax=45, fill="blue") My understanding is that the NULL's are resetting the x & y mapping, but I don't see why this should affect the transparency.

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• two line label with expression

  - by metasequoia

  I'd like to write an axis label over two lines with an expression() statement. However, plotmath and expression won't allow this (e.g. subscript appear on the far right). I found this discussion circa 2005 of a similar issue but the work around that they offer doesn't translate to my application in ggplot2. A recent question addressed a a different permutation of multi-line expression statements, but again the work around provided doesn't apply here. Example: p <- ggplot(mtcars,aes(x=wt,y=mpg))+ geom_point()+ xlab(expression(paste("A long string of text goes here just for the purpose \n of illustrating my point Weight "[reported]))) try(ggsave(plot=p,filename=<some file>,height=4,width=6)) yields an image where subscript "reported" is kicked out to the right when I'd like it to sit next to the previous word.

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• ggplot2 add legend for each geom_point manually

  - by user1162769

  I created a plot using 2 separate data sets so that I could create different errorbars. The first data set has error bars that go down only whereas the second data set has error bars that go up only. This prevents unnecessary overlap in the plot. I also used a compound shape for one of the groups. I want to create a legend based on these shapes (not a colour), but I can't seem to figure it out. Here is the plot code. p<-ggplot() p + geom_point(data=df.figure.1a, aes(x=Hour, y=Mean), shape=5, size=4) + geom_point(data=df.figure.1a, aes(x=Hour, y=Mean), shape=18, size=3) + geom_errorbar(data=df.figure.1a, aes(x=Hour, y=Mean, ymin = Mean - SD, ymax = Mean), size=0.7, width = 0.4) + geom_point(data=df.figure.1b, aes(x=Hour, y=Mean), shape=17, size=4) + geom_errorbar(data=df.figure.1b, aes(x=Hour, y=Mean, ymin = Mean, ymax = Mean + SD), size=0.7, width = 0.4)

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• how to create a plot with customized points in R?

  - by kloop

  I know I can create a plot with line and dots using the type = "o" argument in the plot command. I would like some more control over this -- I want to be able to draw the "o" as full dots, with black border and fill-in color of my choice, of customized size and of a different color than the line. Same for the line, I want to make it thicker, and of my choice of color. How would I go on about doing that? What I found until now is just a plain plot(y, type= "o") which is too poor for my needs. I am not interested in using ggplot, but instead use the internal plot library of R. Any help appreciated.

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• R ggplot2: Arrange facet_grid by non-facet column (and labels using non-facet column)

  - by tommy-o-dell

  I have a couple of questions regarding facetting in ggplot2... Let's say I have a query that returns data that looks like this: (note that it's ordered by Rank asc, Alarm asc and two Alarms have a Rank of 3 because their Totals = 1798 for Week 4, and Rank is set according to Total for Week 4) Rank Week Alarm Total 1 1 BELTWEIGHER HIGH HIGH 1000 1 2 BELTWEIGHER HIGH HIGH 1050 1 3 BELTWEIGHER HIGH HIGH 900 1 4 BELTWEIGHER HIGH HIGH 1800 2 1 MICROWAVE LHS 200 2 2 MICROWAVE LHS 1200 2 3 MICROWAVE LHS 400 2 4 MICROWAVE LHS 1799 3 1 HI PRESS FILTER 2 CLOG SW 1250 3 2 HI PRESS FILTER 2 CLOG SW 1640 3 3 HI PRESS FILTER 2 CLOG SW 1000 3 4 HI PRESS FILTER 2 CLOG SW 1798 3 1 LOW PRESS FILTER 2 CLOG SW 800 3 2 LOW PRESS FILTER 2 CLOG SW 1200 3 3 LOW PRESS FILTER 2 CLOG SW 800 3 4 LOW PRESS FILTER 2 CLOG SW 1798 (duplication code below) Rank = c(rep(1,4),rep(2,4),rep(3,8)) Week = c(rep(1:4,4)) Total = c( 1000,1050,900,1800, 200,1200,400,1799, 1250,1640,1000,1798, 800,1200,800,1798) Alarm = c(rep("BELTWEIGHER HIGH HIGH",4), rep("MICROWAVE LHS",4), rep("HI PRESS FILTER 2 CLOG SW",4), rep("LOW PRESS FILTER 2 CLOG SW",4)) spark <- data.frame(Rank, Week, Alarm, Total) Now when I do this... s <- ggplot(spark, aes(Week, Total)) + opts( panel.background = theme_rect(size = 1, colour = "lightgray"), panel.grid.major = theme_blank(), panel.grid.minor = theme_blank(), axis.line = theme_blank(), axis.text.x = theme_blank(), axis.text.y = theme_blank(), axis.title.x = theme_blank(), axis.title.y = theme_blank(), axis.ticks = theme_blank(), strip.background = theme_blank(), strip.text.y = theme_text(size = 7, colour = "red", angle = 0) ) s + facet_grid(Alarm ~ .) + geom_line() I get this.... Notice that it's facetted according to Alarm and that the facets are arranged alphabetically. Two Questions: How can I can I keep it facetted by alarm but displayed in the correct order? (Rank asc, Alarm asc). Also, how can I keep it facetted by alarm but show labels from Rank instead of Alarm? Note that I can't just facet on Rank because ggplot2 would see only 3 facets to plot where there are really 4 different alarms. Thanks kindly for the help! Tommy

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• How can a data ellipse be superimposed on a ggplot2 scatterplot?

  - by Radu

  Hi, I have an R function which produces 95% confidence ellipses for scatterplots. The output looks like this, having a default of 50 points for each ellipse (50 rows): [,1] [,2] [1,] 0.097733810 0.044957994 [2,] 0.084433494 0.050337990 [3,] 0.069746783 0.054891438 I would like to superimpose a number of such ellipses for each level of a factor called 'site' on a ggplot2 scatterplot, produced from this command: > plat1 <- ggplot(mapping=aes(shape=site, size=geom), shape=factor(site)); plat1 + geom_point(aes(x=PC1.1,y=PC2.1)) This is run on a dataset, called dflat which looks like this: site geom PC1.1 PC2.1 PC3.1 PC1.2 PC2.2 1 Buhlen 1259.5649 -0.0387975838 -0.022889782 0.01355317 0.008705276 0.02441577 2 Buhlen 653.6607 -0.0009398704 -0.013076251 0.02898955 -0.001345149 0.03133990 The result is fine, but when I try to add the ellipse (let's say for this one site, called "Buhlen"): > plat1 + geom_point(aes(x=PC1.1,y=PC2.1)) + geom_path(data=subset(dflat, site="Buhlen"),mapping=aes(x=ELLI(PC1.1,PC2.1)[,1],y=ELLI(PC1.1,PC2.1)[,2])) I get an error message: "Error in data.frame(x = c(0.0977338099339815, 0.0844334944904515, 0.0697467834016782, : arguments imply differing number of rows: 50, 211 I've managed to fix this in the past, but I cannot remember how. It seems that geom_path is relying on the same points rather than plotting new ones. Any help would be appreciated.

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• jitter if multiple outliers in ggplot2 boxplot

  - by Andreas

  I am trying to find a suitable display to illustrate various properties within and across school classes. For each class there is only 15-30 data points (pupils). Right now i am leaning towards a whisker-less boxplot, showing only 1.,2. and 3. quartile + datapoints more then e.g. 1 population SD +/- the sample median. This I can do. However - I need to show this graph to some teachers, in order to gauge what they like most. I'd like to compare my graph with a normal boxplot. But the normal boxplot looks the same if there is only one outlier, or e.g. 5 outliers at the same value. In this case this would be a deal-breaker. e.g. test <-structure(list(value = c(3, 5, 3, 3, 6, 4, 5, 4, 6, 4, 6, 4, 4, 6, 5, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 5, 6, 6, 4, 3, 5, 4, 6, 5, 6, 4, 5, 5, 3, 4, 4, 6, 4, 4, 5, 5, 3, 4, 5, 8, 8, 8, 8, 9, 6, 6, 7, 6, 9), places = structure(c(1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L), .Label = c("a", "b"), class = "factor")), .Names = c("value", "places"), row.names = c(NA, -60L), class = "data.frame") ggplot(test, aes(x=places,y=value))+geom_boxplot() Here there are two outliers at ("a",9) - but only one "dot" shown. So my question: How to jitter the outliers. And - what kind of display would you suggest for this kind of data?

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• What's the best way to annotate this ggplot2 plot? [R]

  - by Matt Parker

  Here's a plot: library(ggplot2) ggplot(mtcars, aes(x = factor(cyl), y = hp, group = factor(am), color = factor(am))) + stat_smooth(fun.data = "mean_cl_boot", geom = "pointrange") + stat_smooth(fun.data = "mean_cl_boot", geom = "line") + geom_hline(yintercept = 130, color = "red") + annotate("text", label = "130 hp", x = .22, y = 135, size = 4) I've been experimenting with labeling the geom_hline in a few different ways, each of which does something I want but has a problem that the other methods don't have. annotate(), used above, is nice - the text is resizeable, black, and easy to position. But it can only be placed within the plot itself, not outside the plot like the axis labels. It also makes an "a" appear in the legend, which I can't dismiss with legend = FALSE. legend = FALSE works with geom_text, but I can't get geom_text to just be black - it seems to be getting tangled up in the line colorings. grid.text lets me put the text anywhere I want, but I can't seem to resize it. I can definitely accept the text being inside of the plot area, but I'd like to keep the legend clean. I feel like I'm missing something simple, but I'm just fried. Thanks in advance for your consideration.

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• geom_ribbon doesn't work - Error in eval(expr, envir, enclos) : object 'variable' not found

  - by Marciszka

  I try to add a geom_ribbon object to my ggplot2 plot. In my data frame, I have an NA values that (I guess) may cause a problem. This is a reproducible example of data drame I have: base <- c(1:10, rep(NA, 10)) output1 <- c(rep(NA, 9), 10 - 0:10) output2 <- c(rep(NA, 9), 10 + 0:10) xaxis <- 1:20 df <- data.frame(xaxis, base, output1, output2) df xaxis base output1 output2 1 1 1 NA NA 2 2 2 NA NA 3 3 3 NA NA 4 4 4 NA NA 5 5 5 NA NA 6 6 6 NA NA 7 7 7 NA NA 8 8 8 NA NA 9 9 9 NA NA 10 10 10 10 10 11 11 NA 9 11 12 12 NA 8 12 13 13 NA 7 13 14 14 NA 6 14 15 15 NA 5 15 16 16 NA 4 16 17 17 NA 3 17 18 18 NA 2 18 19 19 NA 1 19 20 20 NA 0 20 And my attempt to plot a ggplot2 object with a geom_ribbon: dfm <- melt(df, id=1) ggplot(dfm, aes(x = xaxis, y = value, colour = variable)) + geom_line(aes(group=variable)) + geom_ribbon(data=df, aes(group = 1, ymin=output1, ymax=output2)) And, eventually, I got an error I cannot deal with: Error in eval(expr, envir, enclos) : object 'variable' not found Thank ypu in advance for any suggestions.

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• Transform only one axis to log10 scale with ggplot2

  - by daroczig

  I have the following problem: I would like to visualize a discrete and a continuous variable on a boxplot in which the latter has a few extreme high values. This makes the boxplot meaningless (the points and even the "body" of the chart is too small), that is why I would like to show this on a log10 scale. I am aware that I could leave out the extreme values from the visualization, but I am not intended to. Let's see a simple example with diamonds data: m <- ggplot(diamonds, aes(y = price, x = color)) The problem is not serious here, but I hope you could imagine why I would like to see the values at a log10 scale. Let's try it: m + geom_boxplot() + coord_trans(y = "log10") As you can see the y axis is log10 scaled and looks fine but there is a problem with the x axis, which makes the plot very strange. The problem do not occur with scale_log, but this is not an option for me, as I cannot use a custom formatter this way. E.g.: m + geom_boxplot() + scale_y_log10() My question: does anyone know a solution to plot the boxplot with log10 scale on y axis which labels could be freely formatted with a formatter function like in this thread? Editing the question to help answerers based on answers and comments: What I am really after: one log10 transformed axis (y) with not scientific labels. I would like to label it like dollar (formatter=dollar) or any custom format. If I try @hadley's suggestion I get the following warnings: > m + geom_boxplot() + scale_y_log10(formatter=dollar) Warning messages: 1: In max(x) : no non-missing arguments to max; returning -Inf 2: In max(x) : no non-missing arguments to max; returning -Inf 3: In max(x) : no non-missing arguments to max; returning -Inf With an unchanged y axis labels:

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• How to better create stacked bar graphs with multiple variables from ggplot2?

  - by deoksu

  I often have to make stacked barplots to compare variables, and because I do all my stats in R, I prefer to do all my graphics in R with ggplot2. I would like to learn how to do two things: First, I would like to be able to add proper percentage tick marks for each variable rather than tick marks by count. Counts would be confusing, which is why I take out the axis labels completely. Second, there must be a simpler way to reorganize my data to make this happen. It seems like the sort of thing I should be able to do natively in ggplot2 with plyR, but the documentation for plyR is not very clear (and I have read both the ggplot2 book and the online plyR documentation. My best graph looks like this, the code to create it follows: the R code I use to get it is the following: library(epicalc) ### recode the variables to factors ### recode(c(int_newcoun, int_newneigh, int_neweur, int_newusa, int_neweco, int_newit, int_newen, int_newsp, int_newhr, int_newlit, int_newent, int_newrel, int_newhth, int_bapo, int_wopo, int_eupo, int_educ), c(1,2,3,4,5,6,7,8,9, NA), c('Very Interested','Somewhat Interested','Not Very Interested','Not At All interested',NA,NA,NA,NA,NA,NA)) ### Combine recoded variables to a common vector Interest1<-c(int_newcoun, int_newneigh, int_neweur, int_newusa, int_neweco, int_newit, int_newen, int_newsp, int_newhr, int_newlit, int_newent, int_newrel, int_newhth, int_bapo, int_wopo, int_eupo, int_educ) ### Create a second vector to label the first vector by original variable ### a1<-rep("News about Bangladesh", length(int_newcoun)) a2<-rep("Neighboring Countries", length(int_newneigh)) [...] a17<-rep("Education", length(int_educ)) Interest2<-c(a1, a2, a3, a4, a5, a6, a7, a8, a9, a10, a11, a12, a13, a14, a15, a16, a17) ### Create a Weighting vector of the proper length ### Interest.weight<-rep(weight, 17) ### Make and save a new data frame from the three vectors ### Interest.df<-cbind(Interest1, Interest2, Interest.weight) Interest.df<-as.data.frame(Interest.df) write.csv(Interest.df, 'C:\\Documents and Settings\\[name]\\Desktop\\Sweave\\InterestBangladesh.csv') ### Sort the factor levels to display properly ### Interest.df$Interest1<-relevel(Interest$Interest1, ref='Not Very Interested') Interest.df$Interest1<-relevel(Interest$Interest1, ref='Somewhat Interested') Interest.df$Interest1<-relevel(Interest$Interest1, ref='Very Interested') Interest.df$Interest2<-relevel(Interest$Interest2, ref='News about Bangladesh') Interest.df$Interest2<-relevel(Interest$Interest2, ref='Education') [...] Interest.df$Interest2<-relevel(Interest$Interest2, ref='European Politics') detach(Interest) attach(Interest) ### Finally create the graph in ggplot2 ### library(ggplot2) p<-ggplot(Interest, aes(Interest2, ..count..)) p<-p+geom_bar((aes(weight=Interest.weight, fill=Interest1))) p<-p+coord_flip() p<-p+scale_y_continuous("", breaks=NA) p<-p+scale_fill_manual(value = rev(brewer.pal(5, "Purples"))) p update_labels(p, list(fill='', x='', y='')) I'd very much appreciate any tips, tricks or hints. Thanks.

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• subset in geom_point SOMETIMES returns full dataset, instead of none.

  - by Andreas

  I ask the following in the hope that someone might come up with a generic description about the problem.Basically I have no idea whats wrong with my code. When I run the code below, plot nr. 8 turns out wrong. Specifically the subset in geom_point does not work the way it should. (update: With plot nr. 8 the whole dataset is plottet, instead of only the subset). If somebody can tell me what the problem is, I'll update this post. SOdata <- structure(list(id = 10:55, one = c(7L, 8L, 7L, NA, 7L, 8L, 5L, 7L, 7L, 8L, NA, 10L, 8L, NA, NA, NA, NA, 6L, 5L, 6L, 8L, 4L, 7L, 6L, 9L, 7L, 5L, 6L, 7L, 6L, 5L, 8L, 8L, 7L, 7L, 6L, 6L, 8L, 6L, 8L, 8L, 7L, 7L, 5L, 5L, 8L), two = c(7L, NA, 8L, NA, 10L, 10L, 8L, 9L, 4L, 10L, NA, 10L, 9L, NA, NA, NA, NA, 7L, 8L, 9L, 10L, 9L, 8L, 8L, 8L, 8L, 8L, 9L, 10L, 8L, 8L, 8L, 10L, 9L, 10L, 8L, 9L, 10L, 8L, 8L, 7L, 10L, 8L, 9L, 7L, 9L), three = c(7L, 10L, 7L, NA, 10L, 10L, NA, 10L, NA, NA, NA, NA, 10L, NA, NA, 4L, NA, 7L, 7L, 4L, 10L, 10L, 7L, 4L, 7L, NA, 10L, 4L, 7L, 7L, 7L, 10L, 10L, 7L, 10L, 4L, 10L, 10L, 10L, 4L, 10L, 10L, 10L, 10L, 7L, 10L), four = c(7L, 10L, 4L, NA, 10L, 7L, NA, 7L, NA, NA, NA, NA, 10L, NA, NA, 4L, NA, 10L, 10L, 7L, 10L, 10L, 7L, 7L, 7L, NA, 10L, 7L, 4L, 10L, 4L, 7L, 10L, 2L, 10L, 4L, 12L, 4L, 7L, 10L, 10L, 12L, 12L, 4L, 7L, 10L), five = c(7L, NA, 6L, NA, 8L, 8L, 7L, NA, 9L, NA, NA, NA, 9L, NA, NA, NA, NA, 7L, 8L, NA, NA, 7L, 7L, 4L, NA, NA, NA, NA, 5L, 6L, 5L, 7L, 7L, 6L, 9L, NA, 10L, 7L, 8L, 5L, 7L, 10L, 7L, 4L, 5L, 10L), six = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("2010-05-25", "2010-05-27", "2010-06-07"), class = "factor"), seven = c(0.777777777777778, 0.833333333333333, 0.333333333333333, 0.888888888888889, 0.5, 0.888888888888889, 0.777777777777778, 0.722222222222222, 0.277777777777778, 0.611111111111111, 0.722222222222222, 1, 0.888888888888889, 0.722222222222222, 0.555555555555556, NA, 0, 0.666666666666667, 0.666666666666667, 0.833333333333333, 0.833333333333333, 0.833333333333333, 0.833333333333333, 0.722222222222222, 0.833333333333333, 0.888888888888889, 0.666666666666667, 1, 0.777777777777778, 0.722222222222222, 0.5, 0.833333333333333, 0.722222222222222, 0.388888888888889, 0.722222222222222, 1, 0.611111111111111, 0.777777777777778, 0.722222222222222, 0.944444444444444, 0.555555555555556, 0.666666666666667, 0.722222222222222, 0.444444444444444, 0.333333333333333, 0.777777777777778), eight = c(0.666666666666667, 0.333333333333333, 0.833333333333333, 0.666666666666667, 1, 1, 0.833333333333333, 0.166666666666667, 0.833333333333333, 0.833333333333333, 1, 1, 0.666666666666667, 0.666666666666667, 0.333333333333333, 0.5, 0, 0.666666666666667, 0.5, 1, 0.666666666666667, 0.5, 0.666666666666667, 0.666666666666667, 0.666666666666667, 0.333333333333333, 0.333333333333333, 1, 0.666666666666667, 0.833333333333333, 0.666666666666667, 0.666666666666667, 0.5, 0, 0.833333333333333, 1, 0.666666666666667, 0.5, 0.666666666666667, 0.666666666666667, 0.5, 1, 0.833333333333333, 0.666666666666667, 0.833333333333333, 0.666666666666667), nine = c(0.307692307692308, NA, 0.461538461538462, 0.538461538461538, 1, 0.769230769230769, 0.538461538461538, 0.692307692307692, 0, 0.153846153846154, 0.769230769230769, NA, 0.461538461538462, NA, NA, NA, NA, 0, 0.615384615384615, 0.615384615384615, 0.769230769230769, 0.384615384615385, 0.846153846153846, 0.923076923076923, 0.615384615384615, 0.692307692307692, 0.0769230769230769, 0.846153846153846, 0.384615384615385, 0.384615384615385, 0.461538461538462, 0.384615384615385, 0.461538461538462, NA, 0.923076923076923, 0.692307692307692, 0.615384615384615, 0.615384615384615, 0.769230769230769, 0.0769230769230769, 0.230769230769231, 0.692307692307692, 0.769230769230769, 0.230769230769231, 0.769230769230769, 0.615384615384615), ten = c(0.875, 0.625, 0.375, 0.75, 0.75, 0.75, 0.625, 0.875, 1, 0.125, 1, NA, 0.625, 0.75, 0.75, 0.375, NA, 0.625, 0.5, 0.75, 0.875, 0.625, 0.875, 0.75, 0.625, 0.875, 0.5, 0.75, 0, 0.5, 0.875, 1, 0.75, 0.125, 0.5, 0.5, 0.5, 0.625, 0.375, 0.625, 0.625, 0.75, 0.875, 0.375, 0, 0.875), elleven = c(1, 0.8, 0.7, 0.9, 0, 1, 0.9, 0.5, 0, 0.8, 0.8, NA, 0.8, NA, NA, 0.8, NA, 0.4, 0.8, 0.5, 1, 0.4, 0.5, 0.9, 0.8, 1, 0.8, 0.5, 0.3, 0.9, 0.2, 1, 0.8, 0.1, 1, 0.8, 0.5, 0.2, 0.7, 0.8, 1, 0.9, 0.6, 0.8, 0.2, 1), twelve = c(0.666666666666667, NA, 0.133333333333333, 1, 1, 0.8, 0.4, 0.733333333333333, NA, 0.933333333333333, NA, NA, 0.6, 0.533333333333333, NA, 0.533333333333333, NA, 0, 0.6, 0.533333333333333, 0.733333333333333, 0.6, 0.733333333333333, 0.666666666666667, 0.533333333333333, 0.733333333333333, 0.466666666666667, 0.733333333333333, 1, 0.733333333333333, 0.666666666666667, 0.533333333333333, NA, 0.533333333333333, 0.6, 0.866666666666667, 0.466666666666667, 0.533333333333333, 0.333333333333333, 0.6, 0.6, 0.866666666666667, 0.666666666666667, 0.6, 0.6, 0.533333333333333)), .Names = c("id", "one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten", "elleven", "twelve"), class = "data.frame", row.names = c(NA, -46L)) iqr <- function(x, ...) { qs <- quantile(as.numeric(x), c(0.25, 0.5, 0.75), na.rm = T) names(qs) <- c("ymin", "y", "ymax") qs } magic <- function(y, ...) { high <- median(SOdata[[y]], na.rm=T)+1.5*sd(SOdata[[y]],na.rm=T) low <- median(SOdata[[y]], na.rm=T)-1.5*sd(SOdata[[y]],na.rm=T) ggplot(SOdata, aes_string(x="six", y=y))+ stat_summary(fun.data="iqr", geom="crossbar", fill="grey", alpha=0.3)+ geom_point(data = SOdata[SOdata[[y]] > high,], position=position_jitter(w=0.1, h=0),col="green", alpha=0.5)+ geom_point(data = SOdata[SOdata[[y]] < low,], position=position_jitter(w=0.1, h=0),col="red", alpha=0.5)+ stat_summary(fun.y=median, geom="point",shape=18 ,size=4, col="orange") } for (i in names(SOdata)[-c(1,7)]) { p<- magic(i) ggsave(paste("magig_plot_",i,".png",sep=""), plot=p, height=3.5, width=5.5) }

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• What is wrong here (will update): subset in geom_point does not work as expected

  - by Andreas

  I ask the following in the hope that someone might come up with a generic description about the problem.Basically I have no idea whats wrong with my code. When I run the code below, plot nr. 8 turns out wrong. Specifically the subset in geom_point does not work the way it should. If somebody can tell me what the problem is, I'll update this post. SOdata <- structure(list(id = 10:55, one = c(7L, 8L, 7L, NA, 7L, 8L, 5L, 7L, 7L, 8L, NA, 10L, 8L, NA, NA, NA, NA, 6L, 5L, 6L, 8L, 4L, 7L, 6L, 9L, 7L, 5L, 6L, 7L, 6L, 5L, 8L, 8L, 7L, 7L, 6L, 6L, 8L, 6L, 8L, 8L, 7L, 7L, 5L, 5L, 8L), two = c(7L, NA, 8L, NA, 10L, 10L, 8L, 9L, 4L, 10L, NA, 10L, 9L, NA, NA, NA, NA, 7L, 8L, 9L, 10L, 9L, 8L, 8L, 8L, 8L, 8L, 9L, 10L, 8L, 8L, 8L, 10L, 9L, 10L, 8L, 9L, 10L, 8L, 8L, 7L, 10L, 8L, 9L, 7L, 9L), three = c(7L, 10L, 7L, NA, 10L, 10L, NA, 10L, NA, NA, NA, NA, 10L, NA, NA, 4L, NA, 7L, 7L, 4L, 10L, 10L, 7L, 4L, 7L, NA, 10L, 4L, 7L, 7L, 7L, 10L, 10L, 7L, 10L, 4L, 10L, 10L, 10L, 4L, 10L, 10L, 10L, 10L, 7L, 10L), four = c(7L, 10L, 4L, NA, 10L, 7L, NA, 7L, NA, NA, NA, NA, 10L, NA, NA, 4L, NA, 10L, 10L, 7L, 10L, 10L, 7L, 7L, 7L, NA, 10L, 7L, 4L, 10L, 4L, 7L, 10L, 2L, 10L, 4L, 12L, 4L, 7L, 10L, 10L, 12L, 12L, 4L, 7L, 10L), five = c(7L, NA, 6L, NA, 8L, 8L, 7L, NA, 9L, NA, NA, NA, 9L, NA, NA, NA, NA, 7L, 8L, NA, NA, 7L, 7L, 4L, NA, NA, NA, NA, 5L, 6L, 5L, 7L, 7L, 6L, 9L, NA, 10L, 7L, 8L, 5L, 7L, 10L, 7L, 4L, 5L, 10L), six = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("2010-05-25", "2010-05-27", "2010-06-07"), class = "factor"), seven = c(0.777777777777778, 0.833333333333333, 0.333333333333333, 0.888888888888889, 0.5, 0.888888888888889, 0.777777777777778, 0.722222222222222, 0.277777777777778, 0.611111111111111, 0.722222222222222, 1, 0.888888888888889, 0.722222222222222, 0.555555555555556, NA, 0, 0.666666666666667, 0.666666666666667, 0.833333333333333, 0.833333333333333, 0.833333333333333, 0.833333333333333, 0.722222222222222, 0.833333333333333, 0.888888888888889, 0.666666666666667, 1, 0.777777777777778, 0.722222222222222, 0.5, 0.833333333333333, 0.722222222222222, 0.388888888888889, 0.722222222222222, 1, 0.611111111111111, 0.777777777777778, 0.722222222222222, 0.944444444444444, 0.555555555555556, 0.666666666666667, 0.722222222222222, 0.444444444444444, 0.333333333333333, 0.777777777777778), eight = c(0.666666666666667, 0.333333333333333, 0.833333333333333, 0.666666666666667, 1, 1, 0.833333333333333, 0.166666666666667, 0.833333333333333, 0.833333333333333, 1, 1, 0.666666666666667, 0.666666666666667, 0.333333333333333, 0.5, 0, 0.666666666666667, 0.5, 1, 0.666666666666667, 0.5, 0.666666666666667, 0.666666666666667, 0.666666666666667, 0.333333333333333, 0.333333333333333, 1, 0.666666666666667, 0.833333333333333, 0.666666666666667, 0.666666666666667, 0.5, 0, 0.833333333333333, 1, 0.666666666666667, 0.5, 0.666666666666667, 0.666666666666667, 0.5, 1, 0.833333333333333, 0.666666666666667, 0.833333333333333, 0.666666666666667), nine = c(0.307692307692308, NA, 0.461538461538462, 0.538461538461538, 1, 0.769230769230769, 0.538461538461538, 0.692307692307692, 0, 0.153846153846154, 0.769230769230769, NA, 0.461538461538462, NA, NA, NA, NA, 0, 0.615384615384615, 0.615384615384615, 0.769230769230769, 0.384615384615385, 0.846153846153846, 0.923076923076923, 0.615384615384615, 0.692307692307692, 0.0769230769230769, 0.846153846153846, 0.384615384615385, 0.384615384615385, 0.461538461538462, 0.384615384615385, 0.461538461538462, NA, 0.923076923076923, 0.692307692307692, 0.615384615384615, 0.615384615384615, 0.769230769230769, 0.0769230769230769, 0.230769230769231, 0.692307692307692, 0.769230769230769, 0.230769230769231, 0.769230769230769, 0.615384615384615), ten = c(0.875, 0.625, 0.375, 0.75, 0.75, 0.75, 0.625, 0.875, 1, 0.125, 1, NA, 0.625, 0.75, 0.75, 0.375, NA, 0.625, 0.5, 0.75, 0.875, 0.625, 0.875, 0.75, 0.625, 0.875, 0.5, 0.75, 0, 0.5, 0.875, 1, 0.75, 0.125, 0.5, 0.5, 0.5, 0.625, 0.375, 0.625, 0.625, 0.75, 0.875, 0.375, 0, 0.875), elleven = c(1, 0.8, 0.7, 0.9, 0, 1, 0.9, 0.5, 0, 0.8, 0.8, NA, 0.8, NA, NA, 0.8, NA, 0.4, 0.8, 0.5, 1, 0.4, 0.5, 0.9, 0.8, 1, 0.8, 0.5, 0.3, 0.9, 0.2, 1, 0.8, 0.1, 1, 0.8, 0.5, 0.2, 0.7, 0.8, 1, 0.9, 0.6, 0.8, 0.2, 1), twelve = c(0.666666666666667, NA, 0.133333333333333, 1, 1, 0.8, 0.4, 0.733333333333333, NA, 0.933333333333333, NA, NA, 0.6, 0.533333333333333, NA, 0.533333333333333, NA, 0, 0.6, 0.533333333333333, 0.733333333333333, 0.6, 0.733333333333333, 0.666666666666667, 0.533333333333333, 0.733333333333333, 0.466666666666667, 0.733333333333333, 1, 0.733333333333333, 0.666666666666667, 0.533333333333333, NA, 0.533333333333333, 0.6, 0.866666666666667, 0.466666666666667, 0.533333333333333, 0.333333333333333, 0.6, 0.6, 0.866666666666667, 0.666666666666667, 0.6, 0.6, 0.533333333333333)), .Names = c("id", "one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten", "elleven", "twelve"), class = "data.frame", row.names = c(NA, -46L)) iqr <- function(x, ...) { qs <- quantile(as.numeric(x), c(0.25, 0.5, 0.75), na.rm = T) names(qs) <- c("ymin", "y", "ymax") qs } magic <- function(y, ...) { high <- median(SOdata[[y]], na.rm=T)+1.5*sd(SOdata[[y]],na.rm=T) low <- median(SOdata[[y]], na.rm=T)-1.5*sd(SOdata[[y]],na.rm=T) ggplot(SOdata, aes_string(x="six", y=y))+ stat_summary(fun.data="iqr", geom="crossbar", fill="grey", alpha=0.3)+ geom_point(data = SOdata[SOdata[[y]] > high,], position=position_jitter(w=0.1, h=0),col="green", alpha=0.5)+ geom_point(data = SOdata[SOdata[[y]] < low,], position=position_jitter(w=0.1, h=0),col="red", alpha=0.5)+ stat_summary(fun.y=median, geom="point",shape=18 ,size=4, col="orange") } for (i in names(SOdata)[-c(1,7)]) { p<- magic(i) ggsave(paste("magig_plot_",i,".png",sep=""), plot=p, height=3.5, width=5.5) }

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