similar to: merge two matrices

Dear R-help members I would be grateful if anyone could help me with the following problem: I would like to combine two matrices (Schmitt_15 and Schmitt_16, they are attached) which have a species presence/absence x sampling plot structure. The aim would be to have in the end only one matrix which shows all existing species and their presence/absence on all the different plots. To do this I

Hi R user,I am struggling to figure out on how I can calculate the average from the two tables in R. Any one can help me? really your help would be grateful- I am spending so much time to figure it out. It should not be so hard, I think. I have very big data but I have created a hypothetical data for simplification. for example I have : table 1 table 1: species occurance data

R Experts, I would like to create a series of variables without having to assign a separate line of code for each new variable. My dataframe (DF) contains two groups of linked variables (ESP1:ESP9) and (ECRL1:ECRL9). Within ESP1:ESP9 are abbreviated species codes (full dataframe contains 26 codes). ECRL1 represents the number of species x in variable ESP1 harvested, and so on through ESP9 and

Hi Keep your messages in the list, you increase your chance to get some answer. I changed your data to groupedData object (see below), but I did not find any problem in it. plot(wlg) gives reasonable picture and I am not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

Hi Hadley et all, I am struggling with reshape2 and melt works and melt_check (filtered151) seems fine My cast command was acast (filtered151, Time ~ Species ~ Number) > melt_check (filtered151) Using time, Species as id variables $id [1] "time" "Species" $measure [1] "Number" When I execute cast the data matrix is in the correct order but the data

I have a list of scientific names in a data set. I would like to split the names into genus, species and subspecies. Not all names include a subspecies. Could someone show me how to do this? My example code is: a <- matrix(c('genusA speciesA', 10, 'genusB speciesAA', 20, 'genusC speciesAAA subspeciesA', 15,

Merry Xmas to all, I am writing a function and curiously this runs sometimes on one data set and fails on another and i cannot figure out why. Any help much appreciated. If i run the code below with data <- iris[ ,1:4] The code runs fine, but if i run on a large dataset i get the following error (showing data structures as matrix is large) > str(cluster.data) num [1:9985, 1:811] 0 0 0 0

Hi All, I have a large data set with many columns of data. One of these columns is a species identifier and the remainder are variables such as temperature or mass. Currently I am carrying out a single regression on subsets of the data set, e.g. separated data sets with only the data from one species at a time. I have been searching for a thread that will help me to understand how best to repeat

Hello, *Error in tx %*% comb : non-conformable arguments* Suggestions greatly appreciated. I am a beginner and this is my first time posting. I would like to get the summary for indicator species analysis, using package indicspecies with multipatt. I am getting errors, I believe, do to my data organization. After reorganizing and reorganizing, nothing has helped. > data<-

Hello everybody! I’m trying to define the optimal number of surveys to detect the highest number of species within a monitoring season/session. To do this I want to run all the possible combinations between a set of samples and to calculate the total number of species for each combination of 2, 3, 4 …n samples events, so that at the end I will be able to define which is the lowest number of

Hi, I'm analyzing a large number of large simulation datasets, and I've isolated one of the bottlenecks. Any help in speeding it up would be appreciated. `dat` is a dataframe of samples from a regular grid. The first two columns are the spatial coordinates of the samples, the remaining 20 columns are the abundances of species in each cell. I need to calculate the species richness in

Hi Ansely, As Jim points out we really need some sample data to go with the code. Have a look at ?dput which is the best way to supply sample data here or have a look at http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html for some general suggestions on asking questions here---including discussions of using

Hi all, I have the following data and I have a histogram for mms like ggplot(hist,aes(x=hist$mms))+ geom_histogram(binwidth=1,fill="white",color="black")and then I want to fill the color of histogram by probable=1 and probable=0, could anyone help me in this? My data: structure(list(probable = c(1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 1L,

Hi everyone, I am trying to generate a conditional dummy variable ?X" with the following rules set X=1 if Y is =1, two years prior to the NA. [0,0,NA]. For example, if the pattern for Y is 0,0,NA then the X variable is =0 for all the two years prior to the NA. If the pattern for Y is 0,1,NA or 1,0,NA then the X =1 . To be clear, if 1,1,NA then the X=1 that first specific year, it

Hello- I have a dataset which basically looks like this: Location Sex Date Time Verbal Self harm Violence_objects Violence A 1 1-4-2007 1800 3 0 1 3 A 1 1-4-2007 1230 2 1 2 4 D 2 2-4-2007 1100 0

Hi Faradj, What a problem! I think I have worked it out, but only because the result is the one you said you wanted. # the sample data frame is named fkdf Y2Xby3<-function(x) { nrows<-dim(x)[1] X<-rep(0,nrows) for(i in 1:(nrows-2)) { if(!is.na(x$Y[i])) { if(x$Y[i] == 1 && any(is.na(x$Y[(i+1):(i+2)]))) X[i]<-1 if(i > 1) { if(X[i-1] == 1) X[i]<-0 } }

Hi, I am doing canonical discriminant analysis using candisc function from the candisc package. My input is a table of species distribution (columns = abundance of each species in each sample) in samples that are split by categories (rows), and I want to know whether each category is associated with a particular set of species and their abundances. I have 20 rows (samples) split into 6

Dear Jim, wow! It worked! Thanks a lot. I did as you suggested and it worked well with the real data. Although it gave me this error: Error in if (!is.na(x$Y[i])) { : argument is of length zero. For some reason the X1 produced less observations than it is in the data. But it's not a big deal - I identified those cases and simply deleted from the data (it was countries that only appeared

All - I have a large data frame that looks like ID p1 p2 p3...p20 Lat1 Lat2 Lat3...Lat20 Long1 Long2 Long3...Long20 1 0 0 1 0 NA NA 29.xx NA NA NA -89.xx NA 2 1 0 0 1 27.xx NA NA 29.00 -88.00 NA NA -89.xx 3 0 0 0 0 NA

Hello I have a table describing butterfly range traits. It is composed of three columns as below Species name range size (X) latitude of range midpoint (Y) There are 11 kinds of butterflies. Each has its range size, and the latitude of each range midpoint ranges from 9 to 19. I would like to have the average range size of every degree of latitude. For example, the average range