similar to: Very new - beginners questions

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

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

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

I was just thinking of a way to present data and if it is possible in R. I have a data frame that looks as follows (this is just mockup data). df location,"species1","species2","species3","species4","species5" "loc1",0.44,0.28,0.37,-0.24,0.41 "loc2",0.54,0.62,0.34,0.52,0.71 "loc3",-0.33,0.75,-0.34,0.48,0.61 location

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",

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"

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.

Hi R users Does anyone out there have a better/quicker way of adding a factor column to a data frame based on levels of another factor? I have a (large) data frame consisting of records for individual plants, each represented by a unique ID number. The species of each plant is indicated in the column "species", which is a factor column with many different levels (species). There are

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

Dear all, I am trying to extract rows from a data.frame based on the rowSums != 0. I want to preserve rownames in the first column in the subset. Does anyone know how to extract all species that don't have rowSums equal to zero? Here it is: # dataset x <- data.frame( species=c("sp.1","sp.2","sp.3","sp.4"), site1=c(2,3,0,0), site2=c(0,0,0,0),

Dear R-experts, I have a table with following collumns: State, SamplePlot, Species and BodySize. I sampled bird species at 34 SamplePlots and 5 States (regions) monthly during two years. On each bird record I measured bodysize and identified the species. So I have many records of each species (about 150 species) at each SamplePlot and each Region (State). Now I would like bootstrap

Hello, How can I randomly sample individuals within a sites from a site (row) X species abundance (column) data frame or matrix? As an example, the matrix "abund2" made below. ##### (sorry, Im a newbie and this is the only way I know to get an example on here) abund1 <- c(150, 300, 0, 360, 150, 300, 0, 240, 150, 0, 60, 0, 150, 0, 540, 0, 0, 300, 0, 240, 300, 300,

Hello all, here's a real-world example: I'm measuring a quantity (d) at five sites (site1 thru site5) on a silicon wafer. There is a clear site-dependence of the measured value. To find out if this is a measurement artifact I measured the wafer four times: twice in the normal position (posN), and twice rotated by 180 degrees (posR). My data looks like this (full, self-contained code at

Hello, Suppose I have a matrix a where a= sp1 sp2 sp3 sp4 sp5 sp6 site1 1 0 1 1 0 1 site2 1 0 1 1 0 1 site3 1 1 1 1 1 1 site4 0 1 1 1 0 1 site5 0 0 1 0 0 1 site6 0 0 1 0 1 0 And I want to pack that matrix so that the upper left corner contains most of the ones and the bottom right corner contains most of the zeros so that matrix b is b= sp3 sp6 sp4 sp1 sp2 sp5 site1 1 1 1 1 0 0 site2

Hi R user, Would you mind to help me on how I can change a value in a specific column and row in a big table? but the column of the table is a factor (not numeric). Here is an example. I want to change dat[4:5,3]<-"20" but it generated NA> do you have any suggestions for me? dat<-structure(list(Sites = structure(1:5, .Label = c("Site1", "Site2",

Hello R list, I have a list of data frames, in the form (dump output for an example list follows message): $site1 year data 1 2000 0.03685042 2 2001 0.02583885 6 2005 0.02480015 7 2006 0.03458745 $site2 year data 1 2002 4.071134e-03 2 2003 -4.513524e-08 3 2004 8.336272e-08 4 2005 2.270803e-08 5 2006 1.263597e-02 6 2007 NaN I would like to plot each

Dear all, I would like to multiply two matrixes with the different dimension column by column. Let make an example: If I have two matrixes "X" and "Y"as follow: X<- matrix(1:12, nrow=4, ncol=3, dimnames=list(c("A","B","C","D"), c("stage1","stage2","stage3"))) Y<- matrix(1:28, nrow=4, ncol=7,

The simplest would be to convert precip to character and then back to a factor if you really want it to be a factor. This will also remove the levels that no longer exist. str(dat) # 'data.frame': 5 obs. of 3 variables: # $ Sites : Factor w/ 5 levels "Site1","Site2",..: 1 2 3 4 5 # $ temp : num 14 15 12 12.5 17 # $ precip: Factor w/ 5 levels