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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 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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• Can one use polygon() or equivalent in lattice and ggplot2 plots?

  - by Alex Reynolds

  Is it possible to annotate lattice (or ggplot2) figures with elements created with polygon() (or elements created with a similar function) from the graphics library? I'm not too familiar with either library beyond examples of simple graphs posted on the web and printed in Deepayan Sarkar's book. Therefore, while I have code for what I've been doing in R with the graphics library, pointing me to relevant, equivalent functions and usage examples for lattice or ggplot2 specifically would be appreciated. Thanks.

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• R: How to remove outliers from a smoother in ggplot2?

  - by John

  I have the following data set that I am trying to plot with ggplot2, it is a time series of three experiments A1, B1 and C1 and each experiment had three replicates. I am trying to add a stat which detects and removes outliers before returning a smoother (mean and variance?). I have written my own outlier function (not shown) but I expect there is already a function to do this, I just have not found it. I've looked at stat_sum_df("median_hilow", geom = "smooth") from some examples in the ggplot2 book, but I didn't understand the help doc from Hmisc to see if it removes outliers or not. Is there a function to remove outliers like this in ggplot, or where would I amend my code below to add my own function? library (ggplot2) data = data.frame (day = c(1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7,1,3,5,7), od = c( 0.1,1.0,0.5,0.7 ,0.13,0.33,0.54,0.76 ,0.1,0.35,0.54,0.73 ,1.3,1.5,1.75,1.7 ,1.3,1.3,1.0,1.6 ,1.7,1.6,1.75,1.7 ,2.1,2.3,2.5,2.7 ,2.5,2.6,2.6,2.8 ,2.3,2.5,2.8,3.8), series_id = c( "A1", "A1", "A1","A1", "A1", "A1", "A1","A1", "A1", "A1", "A1","A1", "B1", "B1","B1", "B1", "B1", "B1","B1", "B1", "B1", "B1","B1", "B1", "C1","C1", "C1", "C1", "C1","C1", "C1", "C1", "C1","C1", "C1", "C1"), replicate = c( "A1.1","A1.1","A1.1","A1.1", "A1.2","A1.2","A1.2","A1.2", "A1.3","A1.3","A1.3","A1.3", "B1.1","B1.1","B1.1","B1.1", "B1.2","B1.2","B1.2","B1.2", "B1.3","B1.3","B1.3","B1.3", "C1.1","C1.1","C1.1","C1.1", "C1.2","C1.2","C1.2","C1.2", "C1.3","C1.3","C1.3","C1.3")) > data day od series_id replicate 1 1 0.10 A1 A1.1 2 3 1.00 A1 A1.1 3 5 0.50 A1 A1.1 4 7 0.70 A1 A1.1 5 1 0.13 A1 A1.2 6 3 0.33 A1 A1.2 7 5 0.54 A1 A1.2 8 7 0.76 A1 A1.2 9 1 0.10 A1 A1.3 10 3 0.35 A1 A1.3 11 5 0.54 A1 A1.3 12 7 0.73 A1 A1.3 13 1 1.30 B1 B1.1 This is what I have so far and is working nicely, but outliers are not removed: r <- ggplot(data = data, aes(x = day, y = od)) r + geom_point(aes(group = replicate, color = series_id)) + # add points geom_line(aes(group = replicate, color = series_id)) + # add lines geom_smooth(aes(group = series_id)) # add smoother, average of each replicate

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• R: What are the pros and cons of using Lattice versus ggplot2?

  - by Thomas Bratt

  R: What are the pros and cons of using Lattice versus ggplot2?

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• How to add texture to fill colors in ggplot2?

  - by rhh

  I'm currently using scale_brewer for fill and these look beautiful in color (on screen and via color printer) but print relatively uniformly as greys when using a black and white printer. I searched the online ggplot2 documentation but didn't see anything about adding textures to fill colors. Is there an official ggplot2 way to do this or does anyone have a hack that they use? By textures I mean things like diagonal bars, reverse diagonal bars, dot patterns, etc that would differentiate fill colors when printed in black and white. Thanks for thoughts! Robert

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• R: ggplot2, why does my legend show faded colors?

  - by John

  Why is my legend faded in these examples below? Notice how the colours in the legend are not as vivid as the colours in the plot: library(ggplot2) r <- ggplot(data = diamonds, aes(x = carat, y = price, color = cut, group = cut)) r + geom_smooth() #(left) r + geom_smooth(size = 2) #(right)

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• R: ggplot2, can I set the plot title to wrap around and shrink the text to fit the plot?

  - by John

  library(ggplot2) my_title = "This is a really long title of a plot that I want to nicely wrap \n and fit onto the plot without having to manually add the backslash n, but at the moment it does not" r <- ggplot(data = cars, aes(x = speed, y = dist)) r + geom_smooth() + #(left) opts(title = my_title) can I set the plot title to wrap around and shrink the text to fit the plot?

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• R: ggplot2, how to add a number of layers to a plot at once to reduce code

  - by John

  library(ggplot2) This code produces a nice looking plot: qplot(cty, hwy, data = mpg, colour = displ) + scale_y_log2() + labs(x="x axis") + labs(y="y axis") + opts(title = "my title") But I want to setup variables to try and to reduce code repetition: log_scale <- scale_y_log2() xscale <- labs(x="x axis") yscale <- labs(y="y axis") title <- opts(title = "my title") my_scales <- c(log_scale, xscale, yscale, title) # make a variable to hold the scale info changes above So that I can do this and add a bunch of things at the same time: qplot(cty, hwy, data = mpg, colour = displ) + my_scales # add these to your plot. but I get this error: Error in object$class : $ operator is invalid for atomic vectors I realize that the things going into my_scales need to be layers / different types of objects, but I don't see what they should be.

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• How can I manipulate the strip text of facet plots in ggplot2?

  - by briandk

  I'm wondering how I can manipulate the size of strip text in facetted plots. My question is similar to a question on plot titles, but I'm specifically concerned with manipulating not the plot title but the text that appears in facet titles (strip_h). As an example, consider the mpg dataset. library(ggplot2) qplot(hwy, cty, data = mpg) + facet_grid( . ~ manufacturer) The resulting output produces some facet titles that don't fit in the strip. I'm thinking there must be a way to use grid to deal with the strip text. But I'm still a novice and wasn't sure from the grid appendix in Hadley's book how, precisely, to do it. Also, I was afraid if I did it wrong it would break my washing machine, since I believe all technology is connected through The Force :-( Many thanks in advance.

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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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• 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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• 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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• How can I suppress the vertical gridlines in a ggplot2 plot while retaining the x-axis labels?

  - by Tarek

  This is a follow-on from this question, in which I was trying to suppress the vertical gridlines. The solution, as provided by learnr, was to add scale_x_continuous(breaks = NA), but this had the side effect of also suppressing the x-axis labels, as well. I am totally happy to write the labels back in by hand, but it's not clear to me how to figure out where the labels should go. The other option is to suppress all gridlines (using opts( panel.grid.major = theme_blank()) or some such) and then drawing back in just the major horizontal gridlines. Again, the problem here is how to figure out what the breaks are in the plot to supply to geom_hline(). So, essentially, my options are: Suppress vertical gridlines and x-axis labels (using scale_x_continuous(breaks = NA) ) and add the x-axis labels back in. Suppress all gridlines (using opts( panel.grid.major = theme_blank()) ) and add the major horizontal gridlines back in using geom_hline(). Here are the two options: library(ggplot2) data <- data.frame(x = 1:10, y = c(3,5,2,5,6,2,7,6,5,4)) # suppressing vertical gridlines and x-axis labels # need to re-draw x-axis labels ggplot(data, aes(x, y)) + geom_bar(stat = 'identity') + scale_x_continuous(breaks = NA) + opts( panel.grid.major = theme_line(size = 0.5, colour = '#1391FF'), panel.grid.minor = theme_blank(), panel.background = theme_blank(), axis.ticks = theme_blank() ) # suppressing all gridlines # need to re-draw horizontal gridlines, probably with geom_hbar() ggplot(data, aes(x, y)) + geom_bar(stat = 'identity') + scale_x_continuous(breaks = NA) + opts( panel.grid.major = theme_blank(), panel.grid.minor = theme_blank(), panel.background = theme_blank(), axis.ticks = theme_blank() )

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• R: How to update a package and keep it from reverting to the original?

  - by John

  I want to upgrade the package ggplot2: library(ggplot2) packageDescription("ggplot2")["Version"] > 0.8.3 But the current version is 0.8.7. I tried update.packages(), which seemed to work OK. But it still returned older version 0.8.3. So I downloaded and installed the package source from Cran, which says 0.8.7 in the download page. I then install it via the GUI menu in R. It returns ** building package indices ... * DONE (ggplot2) I then run: packageDescription("ggplot2")["Version"] > 0.8.3 And still I have the older version! I don't know why this is not working, what's more I had already come across this problem before and solved it (I can't remember exactly what) but now it has gone back to the older version! What's the easiest way to keep packages like this updated automatically and not have them refer back to older packages?

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• R: ggplot2, how to get the parameters from a plotted linear model smoother?

  - by John

  I have a data.frame with 3 time series in it, shown below. When I plot them with a smoother time series, I want to be able to get the parameters of the linear model that I plot, but I can't see how to do that? > data day od series_id 1 1 0.10 A1 2 3 1.00 A1 3 5 0.50 A1 4 7 0.70 A1 5 1 1.70 B1 6 3 1.60 B1 7 5 1.75 B1 8 7 1.70 B1 9 1 2.10 C1 10 3 2.30 C1 11 5 2.50 C1 12 7 2.70 C1 data = data.frame (day = c(1,3,5,7,1,3,5,7,1,3,5,7), od = c(0.1,1.0,0.5,0.7 ,1.7,1.6,1.75,1.7 ,2.1,2.3,2.5,2.7), series_id = c("A1", "A1", "A1","A1", "B1", "B1","B1", "B1", "C1","C1", "C1", "C1")) r <- ggplot(data = data, aes(x = day, y = od)) r + stat_smooth(aes(group = series_id, color = series_id),method="lm")

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• How do I change the stacking order in a bar chart in ggplot2?

  - by jermdemo

  From the online bar chart guide: qplot(factor(cyl), data=mtcars, geom="bar", fill=factor(gear)) How do I get 5 to sit on the bottom, 4 above that, and 3 on top?

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• How can I make a group bar plot in ggplot2?

  - by maximusyoda

  I have four of these kind of dataframes each with a different name (Apple,Ball,Cat) with different values of frequency but same 4 season names Seasons Frequency DJF 9886 JJA 5408 MAM 12876 SON 6932 And I am trying to make a group bar plot. The graph I'm looking for is like this, where c,d,e,f will be the names - Apple, Ball, Cat. Y-axis will be Frequency Each group will have 4 bars: DJF,JJA,MAM,SON Filled by seasons The number of Frequency written above the bar plot. How can I format the data to make it suitable for ggplot (cbind, melt etc) and use it in ggplot?

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• R ggplot2: possible to customize the continuity of a time scale?

  - by user275455

  Is it possible to have a datetime scale not consider weekends as part of the time continuum? For instance, if I am plotting stock prices over a 2 week period with a line geometry, I do not want to plot a 2 day period of flattness during the weekend. I would like friday to connect with Monday.

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• How can one create a double horizontal axis for a plot in ggplot2?

  - by Alex Holcombe

  I need to show the values on the horizontal axis (aka ordinate, aka x-axis) converted into other units. Hence the need for a second axis.

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• ggplot2 pdf import in Adobe Illustrator missing font AdobePiStd

  - by Sander

  I created several simple ggplot2 plots and saved them to PDF files using the following commands: p <- ggplot(plotobject, aes(x=Pos, y=Pval),res=300) ggsave(plot=p,height=6,width=6,dpi=200, filename="~/example.pdf") If I now open this example.pdf in Adobe Illustrator I get the following error: The font AdobePiStd is missing. Affected text will be displayed using a substitute font. Is there a way in ggplot2 to specify a font (I presume this is for the dots/points) that Adobe will understand or otherwise is there a way to get this font working in Adobe?

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• What is the simplest method to fill the area under a geom_freqpoly line?

  - by mattrepl

  The x-axis is time broken up into time intervals. There is an interval column in the data frame that specifies the time for each row. The column is a factor, where each interval is a different factor level. Plotting a histogram or line using geom_histogram and geom_freqpoly works great, but I'd like to have a line, like that provided by geom_freqpoly, with the area filled. Currently I'm using geom_freqpoly like this: ggplot(quake.data, aes(interval, fill=tweet.type)) + geom_freqpoly(aes(group = tweet.type, colour = tweet.type)) + opts(axis.text.x=theme_text(angle=-60, hjust=0, size = 6)) I would prefer to have a filled area, such as provided by geom_density, but without smoothing the line: UPDATE: The geom_area has been suggested, is there any way to use a ggplot2-generated statistic, such as ..count.., for the geom_area's y-values? Or, does the count aggregation need to occur prior to using ggplot2?

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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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• how to use ggplot conditional on data

  - by Andreas

  I asked this question and it seams ggplot2 currently has a bug with empty data.frames. Therefore I am trying to check if the dataframe is empty, before I make the plot. But what ever I come up with, it gets really ugly, and doesn't work. So I am asking for your help. example data: 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)) And the plot 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) } The problem is that sometimes in the call to geom_point the subset returns an empty dataframe, which sometimes (!) causes ggplot2 to plot all the data instead of none of the data. geom_point(data = SOdata[SOdata[[y]] > high,], position=position_jitter(w=0.1, h=0),col="green", alpha=0.5)+ This is kindda of important to me, and I am really stuck trying to find a solution. Any help that will get me started is much appreciated. Thanks in advance.

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• object of type 'closure' is not subsettable - contradiction?

  - by Alex

  I'm writing a function to produce time series plots of stock prices. However, I'm getting the following error "Error in df[, 7] : object of type 'closure' is not subsettable" Here's an example of the function: plot.prices <- function(df) { require(ggplot2) g <- ggplot(df, aes(x= as.Date(Date, format= "%Y-%m-%d"), y= df[, 7])) + geom_point(size=1) # ... code not shown... g } And example data: spy <- read.csv(file= 'http://ichart.finance.yahoo.com/table.csv?s=SPY&d=11&e=1&f=2012&g=d&a=0&b=29&c=1993&ignore=.csv', header= T) plot.prices(spy) # produces error ggplot(spy, aes(x= as.Date(Date, format= "%Y-%m-%d"), y= spy[, 7])) + geom_point(size=1) ## does not produce error As you can see, the code is identical. I get an error if the call to ggplot() is INSIDE the function but not if the call to ggplot() is OUTSIDE the function. Anyone have any idea why the seeming contradiction?

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