similar to: data transformation

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

dear R-friends, i`ve got a large dataset of vegetation-samples with about 500 variables(=species) in the following format: 1 spec1 1 spec23 1 spec54 1 spec63 2 spec1 2 spec2 2 spec253 2 spec300 2 spec423 3 spec20 3 spec88 3 spec121 3 spec200 3 spec450 . . this means: sample 1 (grassland) with the species (=spec) 1, 23, 54, 63 is it possible to get a following data-structure for further

Hi R-helpers, I have a dataframe (called data) with trees in rows (n=100) and insect species (n=10) in columns. My tree IDs are in a column called TREE and each species has a column labeled SPEC1, SPEC2, SPEC3, etc... I wish to randomize the values in my dataframe such that row and column totals are held constant, i.e. in my randomized data each tree will have the same number of individual

I would like to export a dataframe to a .csv using: >write.csv(dataframe,"dataframe.csv") but I need to add four "header" lines to the csv that are not part of the dataframe (which itself has a line of column headers). The difficulty (for me, at least!) lies in the requirement that certain elements of the header (X, Y and the number of "Q"s - please see example

Dear all, how can I, with R, transform a presence-only table (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)) into a presence-absence (0/1) matrix of species occurrences across sites, as given in the below example? Thanks a lot for your help! Christian My initial table: species lat lon sp1 10 10

Hello, I would like to reshape a dataframe into an array. This is kind a similar task as Excel performs with a Pivot table. To illustrate it: LOC <- factor(c(1,2,2,3,1,1)) SPEC1 <- c(0,0,23,0,12,11) SPEC2 <- c(1,2,0,0,0,4) df <- data.frame(LOC,SPEC1,SPEC2) # original dataframe a <-

While using DTrace to track down a problem recently, we came across an unexpected restriction: the compiler will not permit different speculations to be committed in the same instance of a probe identifier. For instance, consider the following useless D script: #!/usr/sbin/dtrace -s #pragma D option nspec=2 BEGIN { spec1 = speculation(); spec2 = speculation(); } END {

Hi, Can anyone pls help me in plotting the following data? The data-set contains company name, specification-1, specification-2. The graph would basically plot company name with specification-1 on x-axis, & specification-2 on y-axis. Simply put - company name should get classified into one of the four quardrants created by specification 1 & specification2. Thanks.

I am really a beginner of PRI ISDN board, I am wondering if there is a "quick start" chan_dahdi.conf configuration I could use. I tried to install two "FreePBX" boxes follow the instructions from "http://www.cadvision.com/blanchas/Asterisk/DahdiT1trunk.html" connected them between PRIs, It worked. And now if I refer the FreePBX "chan_dahdi.conf" it looks

Hi, I wonder if anyone can help me with specifying a right model for my analysis. I am a beginner to lme methods and though have spent already many hours studying from various books an on-line helps, I was unfortunately not able to find a solution to my problem on my own. Data structure: I studied escape behavior of three species of a prey to a predator. The prey specimens (many) were in a

Hello, # Full disclosure. I am not sure if my problem is a bug(s) in the code, or a fundamental misunderstanding on my part about what I am trying to do with these statistics. I am not familiar with maximum likelihood tests. # I currently have two vectors Aequipecten<-c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,

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

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

On Tue, 20 Feb 2018 14:10:16 +0500 "denis.shigapov" <denis.shigapov at stroylandiya.ru> wrote: It seems that the problem starts here: Could not find machine account in secrets database Yet near the top there is: Setting up secrets.ldb It seems that either 'secrets.ldb' doesn't contain the required info or 'vas.lah' doesn't have the required permissions

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

On Tue, 20 Feb 2018 17:34:00 +0500 "denis.shigapov" <denis.shigapov at stroylandiya.ru> wrote: > Not join(( > samba-tool domain join example.ru DC -Uvas.lah --password=password > --realm=EXAMPLE.RU --site=SITE2 -d 4 'example.ru' is your dns domain name, you should be using your netbios domain name 'EXAMPLE' Who is 'vas.lah' ? does the user have

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