similar to: using the stepfun to plot histogram outline.

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)

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,

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 two vectors x and y, which I would like to plot against each other. I am also displaying other data in this plot. However, I have about 1 million points to plot, and just plotting them x againt y is not very informative. What I'd like to do is to do sort of a continuous box plot. My x values goes from -1 to 1 and my y values from 0 to 1, so I?d like to plot the median and quantiles,

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 know this is fairly basic, but I must have somehow missed it in the manuals. I have two vectors, often of unequal length. I would like to compare them for identity. Order of elements do not matter, but they should contain the same. I.e: I want this kind of comparison: > if (1==1) show("yes") else show("blah") [1] "yes" > if (1==2) show("yes") else

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

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

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

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.

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

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 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,

I am calculating some values that I am inserting into a data frame. From what I have read, creating the dataframe ahead of time is more efficient, since rbind (so far the only solution I have found to appending to a data frame) is not very fast. What I am doing is the following: # create data frame goframe = data.frame(goA = character(10), goB = character(10), value = numeric(10)) goframe[1,] =

I have a data frame containing columns which are factors. I use this to make boxplots for the data, with one box per factor. I would now like to get at the data in the data frame which corresponds to the outliers. I have so far found the $out, which gives "the values of any data points which lie beyond the extremes of the whiskers", but I haven't found anything which will let me get

I have lots of data that I need to display, and I think hexbin would be good for it. However, I cannot load one of the requried packages associated with the hexbin package: > library(hexbin) Loading required package: colorspace Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'colorspace' methods for export not found: [, coords, plot

First I just want to say thanks for all the help I've had from the list so far..) I now have what I think is a clustering problem. I have lots of objects which I have measured a dissimilarity between. Now, this list only has one entry per pair, so it is not symmetrical. Example input: NameA NameB Dist 189_1C2 189_1C1 0 189_1C3 189_1C1 0.017 189_1C3 189_1C2 0.017 189_1C4 189_1C1 0

Hello list! I have a set of data like this: > alldata[1:5,] breaks numbers disttype moltype type 1 0.0000000 6598 Gapped Distances 5S Between species 2 0.4066667 0 Gapped Distances 5S Between species 3 0.8133333 5228 Gapped Distances 5S Between species 4 1.2200000 0 Gapped Distances 5S Between species 5 1.6266667 9702 Gapped

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 +