similar to: producing histogram-like plot

Displaying 20 results from an estimated 1000 matches similar to: "producing histogram-like plot"

2010 Nov 10
1
plotting histograms/density plots in a triangular layout?
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.
2008 Feb 18
3
tabulation on dataframe question
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
2007 Oct 01
3
"continuous" boxplot?
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,
2009 Apr 15
1
performing function on data frame
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
2008 May 21
1
problems with data frames, factors and lists
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)
2008 Feb 26
1
combine vector and data frame on field?
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
2007 Sep 19
2
function on factors - how best to proceed
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
2008 Mar 10
1
hclust graphics - plotting many points
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:
2007 Oct 11
1
creating summary functions for data frame
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
2008 Jun 21
2
using the stepfun to plot histogram outline.
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
2008 Aug 05
1
xyplot key issue - line colors
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$type), points = FALSE, lines = TRUE, columns = 2, lwd = 2,
2008 Jun 05
5
vector comparison
I know this is fairly basic, but I must have somehow missed it in the manuals. I have two vectors, often of unequal length. I would like to compare them for identity. Order of elements do not matter, but they should contain the same. I.e: I want this kind of comparison: > if (1==1) show("yes") else show("blah") [1] "yes" > if (1==2) show("yes") else
2008 Apr 22
2
cloud plot has white(transparent?) background
I am using the code example from the R graph gallery to look at a cloud plot: require(lattice) data(iris) print(cloud(Sepal.Length ~ Petal.Length * Petal.Width, data = iris, groups = Species, screen = list(z = 20, x = -70), perspective = FALSE, key = list(title = "Iris Data", x = .15, y=.85, corner = c(0,1), border = TRUE,
2005 Sep 23
2
multi-class histogram?
I am new to R, and I couldn't find the answers to my question in a faq. This could however be because I didn't know what to look for...:) I have three classes of data, data for bacteria, archaea and eukaryotes. I wish to display these in a histogram where all of the values are used to calculate each column. But, I want each column split in three, where the size of each coloured area
2008 Jan 22
2
contingency table on data frame
I am sorry if this is a faq or tutorial somewhere, but I am unable to solve this one. What I am looking for is a count of how many different categories(numbers in this case) that appears for a given factor. Example: > l <- c("Yes", "No", "Perhaps") > x <- factor( sample(l, 10, replace=T), levels=l ) > m <- c(1:5) > y <- factor( sample(m, 10,
2007 Sep 25
5
Am I misunderstanding the ifelse construction?
I have a function like this: changedir <- function(dataframe) { dir <- dataframe$dir gc_content <- dataframe$gc_content d <- ifelse(dir == "-", gc_content <- -gc_content,gc_content <- gc_content) return(d) } The goal of this function is to be able to input a data frame like this: > lala dir gc_content 1 + 0.5 2 - 0.5 3 +
2005 Sep 27
5
graphics guide?
I am trying to create some graphs with R and it seems to be able to do what I need. However, I have so far not been able to find any sort of explanation of how the graphics system works. I am for instance trying to create a multiple figure, and I seem to have to call plot.new() before every new plot command, I have however not found any explanation of what this actually does. ?plot.new does give
2005 Sep 23
2
multifigure question
I would like to put three figures next to each other in a figure. I have been reading the introduction to R, section 12 several times now, and I still can't make heads or tails out of it. Lets say that I have three dataframes a, b, c, and I want to plot a$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
2005 Oct 04
6
boxplot statistics
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
2009 Aug 12
1
inserting into data frame gives "invalid factor level, NAs generated"
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,] =