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• Smooth Error in qplot from ggplot2

  - by Jared

  I have some data that I am trying to plot faceted by its Type with a smooth (Loess, LM, whatever) superimposed. Generation code is below: testFrame <- data.frame(Time=sample(20:60,50,replace=T),Dollars=round(runif(50,0,6)),Type=sample(c("First","Second","Third","Fourth"),50,replace=T,prob=c(.33,.01,.33,.33))) I have no problem either making a faceted plot, or plotting the smooth, but I cannnot do both. The first three lines of code below work fine. The fourth line is where I have trouble: qplot(Time,Dollars,data=testFrame,colour=Type) qplot(Time,Dollars,data=testFrame,colour=Type) + geom_smooth() qplot(Time,Dollars,data=testFrame) + facet_wrap(~Type) qplot(Time,Dollars,data=testFrame) + facet_wrap(~Type) + geom_smooth() It gives the following error: Error in [<-.data.frame(*tmp*, var, value = list(NA = NULL)) : missing values are not allowed in subscripted assignments of data frames What am I missing to overlay a smooth in a faceted plot? I could have sworn I had done this before, possibly even with the same data.

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• How to enable `geom_text` to recognize `aes` in QPLOT (R programming)

  - by neversaint

  I have a data that looks like this ensg mirna_hgc time value perc id ENSG00000211521 MIR665 x 89 2.07612456747405 1 ENSG00000207787 MIR98 x 73 1.73010380622837 2 ... ENSG00000207827 MIR30A y 99 21.4532871972318 288 ENSG00000207757 MIR93 y 94 1.73010380622837 289 What I'm trying to do is to create a facet plot with label on top of it. The label can be easily called from the perc column. Using this code: dat.m <- read.delim("http://dpaste.com/1271039/plain/",header=TRUE,sep=" ") qplot(value, data=dat.m,facets=time~.,binwidth=1,main="")+ xlab("Value")+ ylab("Count")+ theme(legend.position="none")+ stat_bin(aes(value,label=sprintf("%.01f",perc)),geom="text") But it gave me this error: Error: geom_text requires the following missing aesthetics: label What I'm trying to do is to generate this plot:

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• How do I plot more than one series using qplot?

  - by celenius

  I'm trying to understand how to have more than one series on a plot, using the following data. Year <- c('1950', '1960', '1970', '1980') Bus <- c(10,20,30,40) Bus.sd <- c(1.1, 2.2, 3.3, 4.4) Car <- c(20, 20, 40, 40) Car.sd <- c(1.1, 2.2, 3.3, 4.4) sample_data = data.frame(Year, Bus, Bus.sd, Car, Car.sd) qplot(Year, Bus, data=sample_data, geom="pointrange", ymin = Bus - Bus.sd/2, ymax = Bus + Bus.sd/2) For example, using the above data, how do I show both sample_data$Bus and sample_data$Car on the same plot in different colors? What I tried doing was: p <- qplot(...) then p <- p + qplot(...) where I replicated the previous line, but this gave me an error. I don't fully understand how AES works. I have studied the ggplot2 examples, but have difficulty understanding the relevant examples here.

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• How can I superimpose modified loess lines on a ggplot2 qplot?

  - by briandk

  Background Right now, I'm creating a multiple-predictor linear model and generating diagnostic plots to assess regression assumptions. (It's for a multiple regression analysis stats class that I'm loving at the moment :-) My textbook (Cohen, Cohen, West, and Aiken 2003) recommends plotting each predictor against the residuals to make sure that: The residuals don't systematically covary with the predictor The residuals are homoscedastic with respect to each predictor in the model On point (2), my textbook has this to say: Some statistical packages allow the analyst to plot lowess fit lines at the mean of the residuals (0-line), 1 standard deviation above the mean, and 1 standard deviation below the mean of the residuals....In the present case {their example}, the two lines {mean + 1sd and mean - 1sd} remain roughly parallel to the lowess {0} line, consistent with the interpretation that the variance of the residuals does not change as a function of X. (p. 131) How can I modify loess lines? I know how to generate a scatterplot with a "0-line,": # First, I'll make a simple linear model and get its diagnostic stats library(ggplot2) data(cars) mod <- fortify(lm(speed ~ dist, data = cars)) attach(mod) str(mod) # Now I want to make sure the residuals are homoscedastic qplot (x = dist, y = .resid, data = mod) + geom_smooth(se = FALSE) # "se = FALSE" Removes the standard error bands But does anyone know how I can use ggplot2 and qplot to generate plots where the 0-line, "mean + 1sd" AND "mean - 1sd" lines would be superimposed? Is that a weird/complex question to be asking?

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• Generate multiple graphics from within an R function

  - by William Doane

  I'd like to spawn several graphics windows from within a function in R using ggplot graphics... testf <- function(a, b) { devAskNewPage(TRUE) qplot(a, b); # grid.newpage(recording = TRUE) dev.new() qplot(a, a+a); # grid.newpage(recording = TRUE) dev.new() qplot(b, b+b); } library(ggplot2) x <- rnorm(50) y <- rnorm(50) testf(x, y) However, neither dev.new() nor grid.newpage() seems to flush the preceding plot. I know that, in R, functions normally only produce the last thing they evaluate, but I'd like to understand the process better and to learn of any possible workarounds. Thoughts?

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• Side-by-side plots with ggplot2 in R

  - by chris_dubois

  I would like to place two plots side by side using the ggplot2 package (ie. do the equivalent of par(mfrow=c(1,2))). For example, I would like to have the following two plots show side-by-side with the same scale. x <- rnorm(100) eps <- rnorm(100,0,.2) qplot(x,3*x+eps) qplot(x,2*x+eps) Do I need to put them in the same data.frame like in this example? qplot(displ, hwy, data=mpg, facets = . ~ year) + geom_smooth() Thanks!

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• program R- in ggplot restrict y to be >0 in LOESS plot

  - by Nate

  Here's my code: qplot(data=sites, x, y, main="Site 349") (p <- qplot(data = sites, x, y, xlab = "", ylab = "")) (p1 <- p + geom_smooth(method = "loess",span=0.5, size = 1.5)) p1 + theme_bw() + opts(title = "Site 349") Some of the LOESS lines and confidence intervals go below zero, but I would like to restrict the graphics to 0 and positive numbers (because negative do not make sense). How can I do this?

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• ggplot: showing % instead of counts in charts of categorical variables

  - by wishihadabettername

  I'm plotting a categorical variable and instead of showing the counts for each category value, I'm looking for a way to get ggplot to display the percentage of values in that category. Of course, it is possible to create another variable with the calculated percentage and plot that one, but I have to do it several dozens of times and I hope to achieve that in one command. I was experimenting with something like qplot (mydataf) + stat_bin(aes(n=nrow(mydataf), y=..count../n)) + scale_y_continuous(formatter="percent") but I must be using it incorrectly, as I got errors. To easily reproduce the setup, here's a simplified example: mydata <- c ("aa", "bb", null, "bb", "cc", "aa", "aa", "aa", "ee", null, "cc"); mydataf <- factor(mydata); qplot (mydataf); #this shows the count, I'm looking to see % displayed. In the real case I'll probably use ggplot instead of qplot, but the right way to use stat_bin still eludes me. Thank you. UPDATE: I've also tried these four approaches: ggplot(mydataf, aes(y = (..count..)/sum(..count..))) + scale_y_continuous(formatter = 'percent'); ggplot(mydataf, aes(y = (..count..)/sum(..count..))) + scale_y_continuous(formatter = 'percent') + geom_bar(); ggplot(mydataf, aes(x = levels(mydataf), y = (..count..)/sum(..count..))) + scale_y_continuous(formatter = 'percent'); ggplot(mydataf, aes(x = levels(mydataf), y = (..count..)/sum(..count..))) + scale_y_continuous(formatter = 'percent') + geom_bar(); but all 4 give: Error: ggplot2 doesn't know how to deal with data of class factor The same error appears for the simple case of ggplot (data=mydataf, aes(levels(mydataf))) + geom_bar() so it's clearly something about how ggplot interacts with a single vector. I'm scratching my head, googling for that error gives a single result.

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• Error when trying to create a faceted plot in ggplot2

  - by John Horton

  I am trying to make a faceted plot in ggplot2 of the coefficients on the regressors from two linear models with the same predictors. The data frame I constructed is this: r.together> reg coef se y 1 (Intercept) 5.068608671 0.6990873 Labels 2 goodTRUE 0.310575129 0.5228815 Labels 3 indiaTRUE -1.196868662 0.5192330 Labels 4 moneyTRUE -0.586451273 0.6011257 Labels 5 maleTRUE -0.157618168 0.5332040 Labels 6 (Intercept) 4.225580743 0.6010509 Bonus 7 goodTRUE 1.272760149 0.4524954 Bonus 8 indiaTRUE -0.829588862 0.4492838 Bonus 9 moneyTRUE -0.003571476 0.5175601 Bonus 10 maleTRUE 0.977011737 0.4602726 Bonus The "y" column is a label for the model, reg are the regressors and coef and se are what you would think. I want to plot: g <- qplot(reg, coef, facets=.~y, data = r.together) + coord_flip() But when I try to display the plot, I get: > print(g) Error in names(df) <- output : 'names' attribute [2] must be the same length as the vector [1] What's strange is that qplot(reg, coef, colour=y, data = r.together) + coord_flip() plots as you would expect.

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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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• R scatterplot overplotting color

  - by rgeekay

  So far I have this: qplot(df[[1]], as.numeric(rownames(df)), group=df[[2]], color=df[[2]], ylab="") I want to use different colors for the points in the 2 groups - perhaps a lighter shade for the what's in black now and a darker - say, red for what's in blue. Also, I want to use hexbin kind of thing for group=0 but not for group=1. I'm not able to get the syntax to get this working. In the current plot 0 is in black and 1 is in blue. Added: I worked on it some more, and by using factor and scale_colour_manual, I got the grey color for 0 and red for 1: > palette1 [1] "grey" "red" "blue" "violet" "black" fy=factor(y, labels=c('grey', 'red')) qplot(x, seq(1:length(x)),col=fy, ylab="") + geom_point() + scale_colour_manual(values=palette1) Pending questions are: How to first plot all the grey and then red on top (some of the red is now hidden because the grey is plotted over). How to apply the hexbin logic for group0 i.e. the grey points only and not for the red.

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• How do I increase the number of evaluation points in geom_smooth for ggplot2 in R

  - by Halpo

  I'm creating a plot and adding a basic loess smooth line to it. qplot(Age.GTS2004., X.d18O,data=deepsea, geom=c('point')) + geom_smooth(method="loess",se=T,span=0.01, alpha=.5, fill='light blue',color='navy') The problem is that the line is coming out really choppy. I need more evaluation point for the curve in certain areas. Is there a way to increase the number of evaluation points without having to reconstruct geom_smooth?

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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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• Can ggplot2 work with R's canvas backend

  - by Casbon

  Having installed canvas from here http://www.rforge.net/canvas/files/ I try to plot: > canvas('test.js') > qplot(rnorm(100), geom='histogram') stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this. Error in grid.Call.graphics("L_setviewport", pvp, TRUE) : Non-finite location and/or size for viewport >

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• Annotating axis in ggplot2

  - by mpiktas

  I am looking for the way to annotate axis in ggplot2. The example of the problem can be found here: http://learnr.wordpress.com/2009/09/24/ggplot2-back-to-back-bar-charts. The y axis of the chart (example graph in the link) has an annotation: (million euro). Is there a way to create such types of annotations in ggplot2? Looking at the documentation there is no obvious way, since the ggplot does not explicitly let you put objects outside plotting area. But maybe there is some workaround? One of the possible workarounds I thought about is using scales: data=data.frame(x=1:10,y=1:10) qplot(x=x,y=y,data=data)+scale_y_continuous(breaks=10.1,label="Millions") But then how do I remove the tick? And it seems that since ggplot does not support multiple scales, I will need to grab the output of the scale_y_continuous, when it calculates the scales automaticaly and then add my custom break and label by hand. Maybe there is a better way?

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• Move a legend in ggplot2

  - by Dan Goldstein

  I'm trying to create a ggplot2 plot with the legend beneath the plot. The ggplot2 book says on p 112 "The position and justification of legends are controlled by the theme setting legend.position, and the value can be right, left, top, bottom, none (no legend), or a numeric position". The following code works (since "right" it is the default), and it also works with "none" as the legend position, but "left", "top", "bottom", all fail with "Error in grid.Call.graphics("L_setviewport", pvp, TRUE) : Non-finite location and/or size for viewport" library(ggplot2) (myDat <- data.frame(cbind(VarX=10:1, VarY=runif(10)), Descrip=sample(LETTERS[1:3], 10, replace=TRUE))) qplot(VarX,VarY, data=myDat, shape=Descrip) + opts(legend.position="right") What am I doing wrong? Re-positioning a legend must be incredibly common, so I figure it's me.

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• How to move or position a legend in ggplot2

  - by Dan Goldstein

  I'm trying to create a ggplot2 plot with the legend beneath the plot. The ggplot2 book says on p 112 "The position and justification of legends are controlled by the theme setting legend.position, and the value can be right, left, top, bottom, none (no legend), or a numeric position". The following code works (since "right" it is the default), and it also works with "none" as the legend position, but "left", "top", "bottom", all fail with "Error in grid.Call.graphics("L_setviewport", pvp, TRUE) : Non-finite location and/or size for viewport" library(ggplot2) (myDat <- data.frame(cbind(VarX=10:1, VarY=runif(10)), Descrip=sample(LETTERS[1:3], 10, replace=TRUE))) qplot(VarX,VarY, data=myDat, shape=Descrip) + opts(legend.position="right") What am I doing wrong? Re-positioning a legend must be incredibly common, so I figure it's me.

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• Help understanding how to make a bar chart using ggplot2

  - by celenius

  I'm trying to use the bar_geom function of ggplot2, but I can't understand how to use it. I've made a small sample of my code to show what I am trying to do: library(ggplot2) # sample data sampleData = data.frame( v1=c('a','b','c','d','e', 'f','g', 'h', 'i','j'), v2=c(1:10) ) sampleData$Names = data.frame( Names = paste(sampleData$v1, sampleData$v2, sep="") ) sampleData$Values = c(1:10) # make plot x = sampleData$Values y = sampleData$Names qplot( x, y, data = sampleData, geom="bar" ) I want sampleData$Names to be on the x-axis of my graph, labeling each bar and and sampleData$Values to scale the bar height. I want the y-axis to be specified as a range. I realize that I don't understand how ggplot2 functions as this small example does not work, yet my other example is generating a plot but I cannot specify a y-range as it considers the variables to be categorical.

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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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• missing plot title in ggplot2

  - by Ben Mazzotta

  How can I create a plot title in ggplot2? Am I making a silly syntax error? The ggplot2 docs indicate that labs(title = 'foo') should work, but I can only get the arguments x='foo' and y='foo' to work with labs(). Neither ggtitle() nor title() worked either. Here is an example. x <- rnorm(10,10,1) y <- rnorm(10,20,2) xy.df <- data.frame(x,y) qplot(x,y, data=xy.df, geom='point', color=x*y) + labs(title = "New Plot Title", x='Some Data', y='Some Other Data')

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• Adding trend lines/boxplots (by group) in ggplot2

  - by Tal Galili

  Hi all, I have 40 subjects, of two groups, over 15 weeks, with some measured variable (Y). I wish to have a plot where: x = time, y = T, lines are by subjects and colours by groups. I found it can be done like this: TIME <- paste("week",5:20) ID <- 1:40 GROUP <- sample(c("a","b"),length(ID), replace = T) group.id <- data.frame(GROUP, ID) a <- expand.grid(TIME, ID) colnames(a) <-c("TIME", "ID") group.id.time <- merge(a, group.id) Y <- rnorm(dim(group.id.time)[1], mean = ifelse(group.id.time$GROUP =="a",1,3) ) DATA <- cbind(group.id.time, Y) qplot(data = DATA, x=TIME, y=Y, group=ID, geom = c("line"),colour = GROUP) But now I wish to add to the plot something to show the difference between the two groups (for example, a trend line for each group, with some CI shadelines) - how can it be done? I remember once seeing the ggplot2 can (easily) do this with geom_smooth, but I am missing something about how to make it work. Also, I wondered at maybe having the lines be like a boxplot for each group (with a line for the different quantiles and fences and so on). But I imagine answering the first question would help me resolve the second. Thanks.

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• Return call from ggplot object

  - by aL3xa

  I've been using ggplot2 for a while now, and I can't find a way to get formula from ggplot object. Though I can get basic info with summary(<ggplot_object>), in order to get complete formula, usually I was combing up and down through .Rhistory file. And this becomes frustrating when you experiment with new graphs, especially when code gets a bit lengthy... so searching through history file isn't quite convenient way of doing this... Is there a more efficient way of doing this? Just an illustration: p <- qplot(data = mtcars, x = factor(cyl), geom = "bar", fill = factor(cyl)) + scale_fill_manual(name = "Cylinders", value = c("firebrick3", "gold2", "chartreuse3")) + stat_bin(aes(label = ..count..), vjust = -0.2, geom = "text", position = "identity") + xlab("# of cylinders") + ylab("Frequency") + opts(title = "Barplot: # of cylinders") I can get some basic info with summary: > summary(p) data: mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb [32x11] mapping: fill = factor(cyl), x = factor(cyl) scales: fill faceting: facet_grid(. ~ ., FALSE) ----------------------------------- geom_bar: stat_bin: position_stack: (width = NULL, height = NULL) mapping: label = ..count.. geom_text: vjust = -0.2 stat_bin: width = 0.9, drop = TRUE, right = TRUE position_identity: (width = NULL, height = NULL) But I want to get code I typed in to get the graph. I reckon that I'm missing something essential here... it's seems impossible that there's no way to get call from ggplot object!

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