search for: species3

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 "1" in the species columns ("species1" to "species3") are replaced by the respective "lat" v...

...ome 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 SPECIES2 999000099 900110119 011101100 901010101 110000019 900000019 SPECIES3 999001099 900100109 011100010 901100100 110100019 901110019 where 9 is actually na, 0 is absence and 1 presence. The final array I want to create should have dimensions that are the x and y coordinates and the number of species (known in advance). (In this example dim = c(9,6,3)). It would be sort...

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 Abundance2... AbundanceN . . . PlotN AbundanceN AbundanceN... AbundanceN This is a...

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 is a factor while all the species are numerical vectors. I would like to present this as a table (or something...

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 questions. How do I read one row of data so as to load site2 into a variable called site2? Once I plot a graph using ordiplot how do I extract i...

...t able to do this with perm.t.test() from deducer. Have fun with this trivial undergraduate problem. Code: c(rep("A", 5), rep("B", 5))->Faktor matrix(rnorm(100, mean=20, sd=4), nrow=10, ncol=10)->M colnames(M) <- c("species1","species2", "species3","species4","species5","species6","species7","species8","species9", "species10") ###Conventional T-Test to test for differences of each species per factor lapply( M, function(x) t.test(x~ Faktor) ) ###Trying it...

...r "Species1" 14,4 11.5 2009 "Species2" ... ... .... >Nmean<-tapply(d15N,list(Year,Species),mean) >Cmean<-tapply(d13C,list(Year,Species),mean) ##works fine, returns something like this Species1 Species2 Species3 2009 20.3 13.4 13,5 2011 NA 23.5 14.5 2012 11.3 NA 23.4 >plot(Cmean,Nmean,col=c("green","red","blue"),....) #works fine, gives a plot with data points coloure...

...tes? in traditional vegetation analyses while ?traits? here correspond to ?species? in such analyses. My data looks like this: Trait1 Trait2 Trait3 Trait4 Trait5 Trait? Species1 228.44 16.56 1.66 13.22 1 short Species2 150.55 28.07 0.41 0.60 1 mid Species3 NA 25.89 NA 0.55 0 large Species4 147.70 17.65 0.42 1.12 NA large Species? 132.68 NA 1.28 2.75 0 short Because the traits have different variable types, different measurement scales, and also missing values for some species, I have calculated...

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 . . . . . . . . . . 16 4 1...

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",