similar to: table with values as dots in increasing sizes

Hello dear subscribed Users, this is my first post, so please forgive me for any inconveniences. The following problem: I have a dataframe containing a factor column. For each column i would like to compare means as parted by the factor. Using the normal t.test function I have already achieved my goal. But i think, that for my original data, a permutational t.test would be better suited.

Dear List, I often have to merge two or more data frames containing unique row names but with some columns (names) common to the two data frames and some columns not common. This toy example will explain the kind of setup I am talking about: mat1 <- as.data.frame(matrix(rnorm(20), nrow = 5)) mat2 <- as.data.frame(matrix(rnorm(20), nrow = 4)) rownames(mat1) <- paste("site",

Hi, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

Dear all, maybe somebody can provide some help for this problem: Example: I've got the following dataframe "data": grid.id<-c(1:4) lat<-c(10,12,13,15) species1<-c(0,0,0,1) species2<-c(1,1,0,0) species3<-c(1,1,1,1) data<-data.frame(cbind(grid.id,lat,species1,species2,species3)) How can I, out of "data" make a new dataframe, where the cells of value

Hello. Does anyone know of an existing function that takes a list in the form of: Plot1 Species1 Abundance1 Plot1 Species2 Abundance2 Plot2 Species1 Abundance1 Plot2 Species3 Abundance3 . . . PlotN SpeciesN AbundanceN and translates into a matrix in the form of Species1 Species2.... SpeciesN Plot1 Abundance1 Abundance2... AbundanceN Plot2 Abundance1

Hi, I'm needing some help finding a function to read a large text file into an array in R. The data are essentially presence / absence / na data for many species and come as a grid with each species name (after two spaces) at the beginning of the matrix defining the map for that species. An excerpt could therefore be: SPECIES1 999001099 900110109 011101000 901100101 110100019 901110019

Hei, i am trying to plot the means of two variables (d13C and d15N), by 2 grouping factors (Species and Year) that i obtained by the function tapply. I would like to plot with different colours according to the Year and show the "Species" as data labels. My data looks like this: Species d13C d13N Year "Species1" 14,4 11.5 2009 "Species2"

Dear all, I have 4 sites and want to determine how different they are from each other. For this I have decided to use R though it seems a bit daunting to learn. I have read data in from a CSV the structure is : Species1 Species2 Species3 Site1 4 4 7 Site2 3 1 0 Site3 0 99 6 Site4 75 3 33 There are many more species than shown above this is just an example. Here are the

Hello, I've some problem with the ggplot2. Here's a small example: --8<-- library(ggplot2) molten <- data.frame(date=c('01','01','01','01', '02','02','02','02'), channel=c('red','red','blue','blue',

I have two vectors min 0.2, 0.3, 0.6, 0.1 max 0.4,0.5,0.7,0.4 Is there a way to combine these two vector so that the values will be taken from the vectors alternating so that I will get a new minmaxminmaxminmax-vector? minmax 0.2,0.4,0.3,0.5,0.6,0.7,0.1,0.4 Any help is much appreciated -- View this message in context:

I am trying to use the "cast" function from the reshape package, where the formula is not passed in directly, but as the result of the as.formula() function. Using reshape v. 0.7.2 I am able to properly melt() by data with: > molten <- melt(x, id=1:2) then I can properly cast with this: > cast(molten, days ~ variable) but if I try > cast(molten,

Dear R Users, I'm trying to use the 'cast' function in the 'reshape' package to convert column-format data to gridded-format data. A sample of my dataset is as follows: head(finalframe) Latitude Longitude Temperature OrigLat p-value Blaney 1 -90 -38.75 NA -87.75 17.10167 NA 2 -90 135.75 NA -87.75 17.10167 NA 3 -90 80.25

I'm working on a package to produce graphic displays of 2- and 3-way tables and need some help/advice on how to simplify the specification of a complex argument that gives the drawing details for each cell of the table. Prototypes of two functions, 'tableplot' and 'cellgram' are given below. The essential idea is that for a given table ('values'), the cells can be be

I am attempting to join several dataframes that summarize sampling effort for different samples into one large data.frame/table. I have looked at the merge command, but have not been clever enough to figure out how to get it to do what I want. A simplified example of what I am trying to do: The dataframes I have look like this (they were generated using the table command) species1.effort

Dear list members, I have a data.frame so shaped: Sector Quadrants Plot Sic Time Species1 Species2 Species3 .. Species-n 1 1 1 1 5 0 0 1 . 0 2 1 1 1 12 1 1 1 . 0 3 1 1 1 34 0 1 0 . 0 4 1 1 1 23 1 1 0 . 0 5 2 1 1 22 1 1 1 . 1 6 2 1 1 10 1 1 1 . 1 7 2 1 1 2 1 0 0 . 0 8 2 1 1 2 0 0 1 . 0 9 3 1 1 12 0 0 0 . 1 . . . . . . . . . .

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 = '')

I have a file that reads like this: Species,Year,Julian_day Alnus_glutinosa, 1873, 123 Sorbus_aucuparia, 1873, 122 ....(more species...) Alnus_glutinosa, 1874, 134 Sorbus_aucuparia, 1874, 143 ....(more species and years) Is there a way to plot this as julian day over years so that each species get a different color? Also is it possible to convert this data into the format: Alnus_glutinosa,

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Hi, I'm doing cross-correlation correlograms with the ncf package. I have four study sites ; four correlograms. I'd like to get the same y scale for the four of them... only, using "ylim=c(-1,1)" does not change the y scale never and I don't know why. I tried with plot() too. Is there another option to change the ylim in plots ? Example with only one correlog (all work

If I have a data frame where a species occupies several rows with different phases such as (both col's ar factors): species,phase Populus tremula,1 Populus tremula,2 Populus tremula,3 Calluna vulgaris,1 Calluna vulgaris,2 Betula alba,1 Betula alba,2 Betula alba,3 Primula veris,1 Primula veris,2 and another df where each species only have one row: species,growth_form Populus tremula,tree Acer