Hi see inline
> > Hello, > > I've got a small dataset on box turtle shell measurements that I would > like to perform a detrended correspondence analysis on. I thought that it > would be interesting to examine the morphometrics for each species in the > area of overlap and in areas where neither species occurs. > > I've taken a look at the dune and dune.env datasets in vegan. Using the > str() command gives me > > > str(dune) > 'data.frame': 20 obs. of 30 variables: > $ Belper: num 3 0 2 0 0 0 0 2 0 0 ... > $ Empnig: num 0 0 0 0 0 0 0 0 0 0 ... > $ Junbuf: num 0 3 0 0 0 0 0 0 0 0 ... > $ Junart: num 0 0 0 3 0 0 4 0 0 3 ... > ... > > However, when I try looking directly at the data frame using the edit > command I see that there is a column called "row.names" to the left of "Belper". > > Likewise, when I use the str() command on dune.env I get > > > str(dune.env) > 'data.frame': 20 obs. of 5 variables: > $ A1 : num 3.5 6 4.2 5.7 4.3 2.8 4.2 6.3 4 11.5 ... > $ Moisture : Ord.factor w/ 4 levels "1"<"2"<"4"<"5": 1 4 2 4 1 1 4 1 2 4 ... > $ Management: Factor w/ 4 levels "BF","HF","NM",..: 1 4 4 4 2 4 2 2 3 3 ... > $ Use : Ord.factor w/ 3 levels "Hayfield"<"Haypastu"<..: 2 2 2 3 2 > 2 3 1 1 2 ... > $ Manure : Ord.factor w/ 5 levels "0"<"1"<"2"<"3"<..: 3 4 5 4 3 5 4 3 1 1 ... > > but using the edit() command shows a column named "row.names". No. This is not a column but it is what it says row.names > str(rosin) 'data.frame': 10 obs. of 5 variables: $ pytel: int 1 2 3 4 5 6 7 8 9 10 $ rstr : num 1.022 0.981 0.992 1.01 0.976 ... $ gama : num 1.4 1.44 1.41 1.43 1.39 ... $ cas : int 0 3 6 9 12 15 18 21 24 27 $ typ : chr "anatas" "anatas" "anatas" "anatas" > head(rosin) pytel rstr gama cas typ 1 1 1.0216621 1.397885 0 anatas 2 2 0.9809663 1.442439 3 anatas 3 3 0.9916211 1.411767 6 anatas ^^ these are row names > > I assume that the the "row.names" column is used to link the two files together. If you are in doubt, recommended way is to consult documentation. ?row.names All data frames have a row names attribute, a character vector of length the number of rows with no duplicates nor missing values. > > My turtle data is saved as a *.csv, and I've added a column called > "row.names", so that it looks like this > > row.names,CL,CCL,CW,CCW,CH,CCH > 1,104.4,131.8,89.887,137.4,43.391,89.7 > 2,108.79,135.9,87.78,118.1,50.72,71.2 > 3,114.12,126.1,89.33,132.8,142.39,78.3 > 4,102.87,128.2,84.2,125,45.42,72.4 > 5,84.6,104.8,72.61,111.8,41.1,57.3 > > I've called this file "turtles_dca.csv". I've also created a file called > "turtles_dca_env.csv" that looks like this > > row.names,Species,Sex,Distribution,Concatenated,Species_overlap > 1,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap > 2,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap > 3,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap > 4,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap > 5,Terrapene_ornata,Female,overlap,TO_F_Overlap,TO_Overlap > > However, when I read the data into R using this command > > turtles.env = read.csv("turtles_dca_env.csv", header = TRUE) > > > and then using the str() command I get > > > > str(turtles) > 'data.frame': 67 obs. of 7 variables: > $ row.names: int 1 2 3 4 5 6 7 8 9 10 ... > $ CL : num 104.4 108.8 114.1 102.9 84.6 ... > $ CCL : num 132 136 126 128 105 ... > $ CW : num 89.9 87.8 89.3 84.2 72.6 ... > $ CCW : num 137 118 133 125 112 ... > $ CH : num 43.4 50.7 142.4 45.4 41.1 ... > $ CCH : num 89.7 71.2 78.3 72.4 57.3 73.4 67 57 68.8 68 ... > > When I run decorana() on this dataset, it appears that the column > "row.names" is included in the analysis, which isn't what I'm looking for. Then why you added this column to your data? > > If I go ahead and delete the column "row.names" from my data frames (i.e. > removing it from turtles and turtles.env), I don't believe that the > analysis is performed correctly. The two species differ significantly in > most of their measurements, but the ordihull() and ordispider() commands > show them overlapping almost completely. > > I think that I'm missing something pretty basic about inputting and > formatting this data for this analysis. Can anyone offer a suggestion on > where I'm going astray? I can send a copy of the data if anyone wants to look at it. I am not familiar with functions you use. However you probably want to link those 2 files together. If they both are in the same order you can just do turtles.complet <- cbind(turtles, turtles.env) Or if they are in different order you need to find some common column(s) and ?merge those two files. Regards Petr > > Best wishes, > Chris > University of Central Oklahoma > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.