similar to: "continuous" boxplot?

I have a data frame with data similar to this: NameA GrpA NameB GrpB Dist A Alpha B Alpha 0.2 A Alpha C Beta 0.2 A Alpha D Beta 0.4 B Alpha C Beta 0.2 B Alpha D Beta 0.1 C Beta D Beta 0.3 Dist is a distance measure between two entities. The table displays all to all distances, but the

I have managed to create a data frame like this: > tsus_same_mean[1:10,] PID Grp Dist PercAln PercId 1 12638 Acidobacteria 0.000000000 1.0000000 1.0000000 2 87 Actinobacteria 0.000000000 0.9700000 0.9700000 3 92 Actinobacteria 0.008902000 1.0000000 0.9910000 4 94 Actinobacteria 0.000000000 1.0000000 1.0000000 5 189 Actinobacteria 0.005876733

Sorry about this one being long, and I apologise beforehand if there is something obvious here that I have missed. I am new to creating my own functions in R, and I am uncertain of how they work. I have a data set that I have read into a data frame: > gctable[1:5,] refseq geometry X60_origin X60_terminus length kingdom 1 NC_009484 cir 1790000 773000 3389227 Bacteria 2

Hi! First, pardon me if this is a faq. I think I should be using some sort of apply, but I am not managing to figure those out. I have a data frame similar to this: > d <- data.frame(x = LETTERS[1:5], y = rnorm(5), z = rnorm(5)) > d x y z 1 A 0.1605464 -0.2719820 2 B -0.9258660 1.2623117 3 C -0.3602656 1.5470351 4 D 1.2621797 1.2996500 5 E 0.6021728 0.5027095

I have a function that creates a list based on some clustered data: mix <- function(Y, pid) { hc = gethc(Y,pid) maxheight = max(hc$height) noingrp = processhc(hc) one = noingrp$one two = noingrp$two twoisone = "one" if (two != 1) twoisone = "more" out = list(pid = pid,one = noingrp$one, two = noingrp$two, diff = maxheight, noseqs = length(hc$labels), twogrp = twoisone)

Hello. I have a distance matrix with lots of distances that I use hclust to organise. I then plot the results using the plot method of hclust. However, the plot itself takes around 20 mins to make due to there being ~700 things in the matrix that I have distances for. I thus would like to dump this to some graphics format which will let me examine this further. I tried dumping it to postscript:

I have a data frame that looks like this: > gctablechromonly[1:5,] refseq geometry gccontent X60_origin X60_terminus length kingdom 1 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 2 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 3 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 4 NC_009484 cir 0.6799

I am using the code example from the R graph gallery to look at a cloud plot: require(lattice) data(iris) print(cloud(Sepal.Length ~ Petal.Length * Petal.Width, data = iris, groups = Species, screen = list(z = 20, x = -70), perspective = FALSE, key = list(title = "Iris Data", x = .15, y=.85, corner = c(0,1), border = TRUE,

I would like to put three figures next to each other in a figure. I have been reading the introduction to R, section 12 several times now, and I still can't make heads or tails out of it. Lets say that I have three dataframes a, b, c, and I want to plot a$V1, b$V1 and c$V1 in separate plots simply using plot(), how do I put them next to each other? I am sorry if this is a FAQ, but I cannot

I am trying to create some graphs with R and it seems to be able to do what I need. However, I have so far not been able to find any sort of explanation of how the graphics system works. I am for instance trying to create a multiple figure, and I seem to have to call plot.new() before every new plot command, I have however not found any explanation of what this actually does. ?plot.new does give

I am new to R, and I couldn't find the answers to my question in a faq. This could however be because I didn't know what to look for...:) I have three classes of data, data for bacteria, archaea and eukaryotes. I wish to display these in a histogram where all of the values are used to calculate each column. But, I want each column split in three, where the size of each coloured area

I have read and reread the boxplot and the boxplot stats page, and I still cannot understand how and what boxplot shows. I realize that this might be due to me not knowing enough statistics, but anyway... First, how does boxplot determine the size of the box? And is the line inside the box the mean or the median (or something completely different?) And how does it determine how long out the

I am sorry if this is a faq or tutorial somewhere, but I am unable to solve this one. What I am looking for is a count of how many different categories(numbers in this case) that appears for a given factor. Example: > l <- c("Yes", "No", "Perhaps") > x <- factor( sample(l, 10, replace=T), levels=l ) > m <- c(1:5) > y <- factor( sample(m, 10,

Hi! I have a dataset that looks like this: 0.0 14 0.0 3 0.9 12 0.73 15 0.78 2 1.0 15 0.3 2 0.32 8 ...and so on. I.e. a value between 0 and 1, and a number I would like to plot this in a histogram-like manner. I would like to have a set of bins, each 0.1 wide, and plot the sum of values in column 2 that falls within each bin. I.e, in this case I would like the first bin, 0.0, to have the

I have some code as shown below. Basically, I would like three boxplots to be set next to each other with no ylabels on the two "inner" plots, and I want the same x axis range on all three. However, it seems like boxplot does not respect the xlim setting. I've tried the various ways I thought would work (par, boxplot(...xlim=)) but none of them seem to work. I then tried plot.window,

I have a function like this: changedir <- function(dataframe) { dir <- dataframe$dir gc_content <- dataframe$gc_content d <- ifelse(dir == "-", gc_content <- -gc_content,gc_content <- gc_content) return(d) } The goal of this function is to be able to input a data frame like this: > lala dir gc_content 1 + 0.5 2 - 0.5 3 +

I am trying to make horizontal violin plots. I have tried both vioplot and simple.violinplot, but both of them seem to not be willing to take the horizontal option. Is this correct, or am I just bungling it somehow? For instance, for vioplot (from the example shown, with the horizontal modification): > vioplot(bimodal,uniform,normal, horizontal=TRUE) Error in median(data) : need numeric data

Hello list:) I have lots of values which I would like to get a histogram outline out of. An example of what I am talking about: testdata = runif(100) bbb = seq(0,1, by = 0.01) hist(testdata, breaks = bbb) I would like to get the outline of the resulting histogram. Now, I think that I can do this using the stepfun function. However, I am uncertain of how to get to the data the stepfun function

I have a problem regarding the colors assigned to the lines in the key to an xy plot. I specify the plot like this: xyplot(numbers~sqrt(breaks)|moltype+disttype, groups = type, data = alldata, layout = c(3,2), type = "l" , lwd = 2, col = c("gray", "skyblue"), key = simpleKey(levels(alldata$type), points = FALSE, lines = TRUE, columns = 2, lwd = 2,

Hi! I have a set of 49 pairwise comparisons that I have done. From this I would like to plot either histograms or the density plots of the values I get. Now, I can plot one histogram per comparison, but I have problems getting the output I want. When plotting like I normally would do: histogram(~percid | orgA_orgB, data = alldata) I get the histograms next to eachother in a boxlike shape.