similar to: Print the content of several columns in only one

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

Dear R-friends, Unfortunately the tables that I "past" on last email gone with bad visual structure. So I send it again. Sorry to do this so confuse. Miltinho ==== Table1 - Bird records State,SampleSite,Species,Bodysize SaoPaulo,Site1,Spp01,4.39 SaoPaulo,Site1,Spp04,4.05 SaoPaulo,Site1,Spp01,2.75 SaoPaulo,Site1,Spp02,8.18 SaoPaulo,Site1,Spp02,0.80

Hello, I'd like to transpose data to create an analysis-friendly dataframe. See below for an example, I was unable to use t(x) and I couldn't find a function with options like PROC TRANSPOSE in SAS. The ideal solution handles variable quantities of SITE - but beggars can't be choosers. :-) Thank you in advance, Mike ## INPUT DATA USER_ID<-c(1,1,1,2,2,2,3,3,4) SITE

Hi, I have seen http://www.tinc-vpn.org/pipermail/tinc-devel/2010-October/000473.html and so tried out for myself to see if multicast would work in tinc using routing mode. I'm using tinc 1.0.19. My test involved sending a ping out on 224.1.1.1 (as 224.0.0.0/24 is a special case), and while I could see the traffic reaching the other tinc daemons, it never seemed to go out to the local

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

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

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

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),

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 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

Hello. I want to test a multi-site setup w/ replication to a central DC only. In a test scenario I have set up a central samba4 DC (sernet-samba 4.1.12-9). For provisioning I have used the --site=central, so no Default-First-Site-Name has been created on provisioning, just 'central'. In AD Site & Services I have unchecked the "Bridge all site links" in "Inter-Site

Dear all, how can I, with R, transform a presence-absence (0/1) matrix of species occurrences into a presence-only table (3 columns) with the names of the species (1st column), the lat information of the sites (2nd column) and the lon information of the sites (3rd column), as given in the below example? Thanks a lot for your help! Christian my dataframe: site lat lon spec1 spec2 spec3 spec4

Hi: I'm having some difficulty properly subscripting a function to remove complete NA rows from a R array object. Could someone please suggest how best to script this out? Data structure: X is an array with 3 dimensions (replicates, Species, Sites) replicates: 1 to 6 but ragged...not all sites equal ,,Site1 Sp1 Sp2 Sp3... Sp50 1 5 4 3 2 2 3 0 0 1 3 NA NA NA NA 4 NA NA NA NA 5 NA

I'm running dovecot 2.2.5 and would like to completely turn off all automatic adding of mount points. So var/lib/dovecot/mounts would be empty essentially. Is this possible? Somehow dovecot always adds a mount point that does not exist and was removed a long time ago. I've dove: doveadm mount add '/my custom path/*' ignore but it still will add mount points in the

Thanks for everyone's input so far, it is greatly appreciated. But I've got one last task I could use some advice on Here are the first few lines of my data set: site,time_local,time_utc,reef_type_code,sensor_type,sensor_depth_m,temperature_c 06,2006-04-09 10:20:00,2006-04-09 20:20:00,BAK,sb39, 2, 29.63 06,2006-04-09 10:40:00,2006-04-09 20:40:00,BAK,sb39, 2, 29.56 06,2006-04-09

I want to gain thousands of random sampling data by randomizing the presence-absence data. Meantime, one important limition is that the row and column sums must be fixed. For example, the data "tst" is following: site1 site2 site3 site4 site5 site6 site7 site8 1 0 0 0 1 1 0 0 0 1 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0

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",

Hi everyone, I am working with the dbFD function of the FD package, and there's something funny happening with the value of sing.sp in the output. Basically, I have a species-function matrix and a community matrix. One site in particular has 6 species, 4 of which have identical functional coding. I thus expect nbsp = 6 and sing.sp = 2 for this site. However, nbsp = sing.sp = 6. This