similar to: change order of plot panels in faceted ggplot/qplot

Hi, I have a data set that I'd like to run logistic regressions on, using ddply to speed up the computation of many models with different combinations of variables. I would like to run regressions on every unique two-variable combination in a portion of my data set, but I can't quite figure out how to do using ddply. The data set looks like this, with "status" as

I'm running into some problems with the spacing of some faceted ggplot plots. I have a number of time series faceted to be one above another, but the scale labels of the y axes all clobber each other at the bottom/top of each. for example, try: qplot(x, y, data = data.frame(x = 1:10, y = 1:10, size = 1:10), facets = size ~ ., size = size) + scale_x_continuous(breaks = 1:10) +

I have a data.frame with ~250 observations (rows) in each of ~50 categories (columns). I would like to perform t.tests on subsets of observations within each column, with the subsets according to index vectors contained in other columns of the data.frame. My data.frame looks something like this: x<-data.frame(matrix(rnorm(200,mean=5,sd=.5),nrow=20)) colnames(x)<-c("site",

Hi, I've tried to figure this out using Intro to R and help(), to no avail - I am new at this. I'm trying to write a script that will read multiple files from a directory and then merge them into a single new data frame. The original data are in a tree-ring specific format, and so I've first used a function (read.rwl) from the dplR package to read each file, translate each into a

Hi, I've run into a difficulty with qplot function (in the ggplot2 package). I can facet histograms even when the faceting variable contains missing values, but only so long as the faceting variable is not a factor. Example: y1 <- rnorm(10) x1 <- c(rep(1,5), rep(2,4), NA) x2 <- factor(c(rep(1,5), rep(2,4), NA)) library(ggplot2) qplot(y1, geom = "histogram", facets =

I have a data frame (attached) that has interpolated EOT errors for each minute before flight landing. It also has the runway and an index for the flight: > > times[1:4,] time error runway flight 1 0 -0.02206235 04R 1 2 1 -0.07961631 04R 1 3 2 -0.13795380 04R 1 4 3 -0.20726073 04R 1 > > sapply(times, class) time error

Hi, I have a qplot like the one in the minimal example below, except I also have faceting like this: qplot(jitter(Goodall),jitter(Better.adapt),colour=Second.adapt,facets=~Pol,data=d1) and with the real data I get quite a lot of overplotting, so I would like to add an alpha channel. In addition, I would like to be able to control which colors are used for each value of Second.adapt (which

Hi there, I am having a little problem with combining three scale_manual commands in a facet plot. I am not able to combine the three different characteristics, instead ending up with three different descriptions next to the graph for the same geom. I would like to see two separate labels (not three); one describing lines 1-7 and the other 8-14. For each of the treatments (A-B) I want a

Hi List, I am running R 2.8.0 on a Windows XP machine, running ggplot2 version 0.8.1 I want to label the bars in a faceted grid barplot. Reproducible R code is given below: #### reproducible facet barplot ##### library(ggplot2) # Dataset from which to create the barplot ml <- rep(1:10,2) vals <- rnorm(20,mean = 10, sd=1) type <- c(rep("MAPE",10),rep("AIC",10))

Look at the bottom of the message for my question #here is a little function that I wrote USGS <- function(input="discharge", days=7){ library(chron) library(gsubfn) #021973269 is the Waynesboro Gauge on the Savannah River Proper (SRS) #02102908 is the Flat Creek Gauge (ftbrfcms) #02133500 is the Drowning Creek (ftbrbmcm) #02341800 is the Upatoi Creek Near Columbus (ftbn) #02342500 is

I get the following error when I run qplot() qplot(grade, read,data = hhm.long.m, geom = c("point", "smooth")) Error in smooth.construct.cr.smooth.spec(object, data, knots) : x has insufficient unique values to support 10 knots: reduce k. I am not sure how to tackle this problem. When I take a subsample (< 1000) than I am able to run that function but with my sample

Hello I simply want to plot two variables against one 'year' variable in qplot. Is any way of doing this without reshaping data in long format and using facet function afterwards? Thank you Denis

I have the following Data structure $ step45 : Factor w/ 2 levels $ obserror : num 6.2 6.2 5.6 6.6 6.6 ... $ Mon : num 2.2 2.0 1.0 3.2 2.0 ... $ inc.comp : num 4 5 2 5 5 5 5 5 4 4 ... all I wanted to do is plotting Mon against obserror, the colors should be by step45 and the size of the symbol should be according to inc.comp so I did this:

I'd like to generate a boxplot that has BOTH the overall distribution of a continuous variable (say age), and then a boxplot for each level of a stratifying variable (e.g. site). Does anyone have prototype code for this? Thanks, -- View this message in context: http://www.nabble.com/GGPLOT-QPLOT-Boxplot-with-summary-tp20095591p20095591.html Sent from the R help mailing list archive at

Dear List, yes, me again trying to work with qplot ;-) I would like to make several single plots within a loop, like this (simplified and so on...): trials <- c("A","B","C") mycolours <- ("wheat","darkolivegreen","lightgreen",

r <-(structure(list(TSS = c(2.8, 8.4, 11, 1.3, 4.2, 2, 3.4, 14, 8.2, 3.1, 1.4, 0.9, 0.5, 6.1, 9.2, 0.6, 1, 11, 2.4, 1.2, 1.3, 1.3, 0, 1.8, 8, 11, 11, 8.5, 8.5, 1.8, 13, 4.4, 1.4, 2.1, 0.5, 25, 25, 9.3, 6.1, 1.6, 1.5, 19, 19, 24, 9.6, 1.8, 1.4, 1), GPP = c(1.213695235, 3.817313822, 1.267930498, 10.45692825, 3.268295623, 3.505286001, 4.468225245, 0.915653726, 1.635617261, 3.726133898,

Hello, I have a ggplot that has the looks of the plot that I want, but it doesn't have the right layout. The data is an ordered melted dataframe: - ID - type (to use for a faced grid) - time - type - time - value (POSIXct) - pos (to use for a faced grid, this is an index to split the plot) The goal of the plot is to create a time line for each ID (different points of time). The ID's

Hi, I would like to plot a bunch of tree ring width data (time series) using ggplots, but I'm having trouble figuring out how to do it. My data is in a data.frame, with years as rownames and a distinct tree ring series in each column. So, something like this: rwl<-matrix(rnorm(800), nrow = 100) colnames(rwl) <- paste('V', 1:8, sep = '')

Hello all, I've been using the following qplot command: qplot(pixX,pixY, data=som, geom="tile", fill=rgb) + scale_fill_identity() + opts(aspect.ratio = .75) + facet_grid(unitX ~ unitY) Now I would like to convert it into the explicit ggplot grammar, so I can remove the extras: axes, labels, background, borders, facet labels, and extra white-space around the plot. (If anyone has

I'm having problems with this example, it is posted with reproduceable code below, both with the normal 0-6 scale and the desired 3-6 scale (with bars removed). How can I get the graph to have the desired 3-6 scale without removing the bars. Thanks! #Data