similar to: reshape dataframe to array (pivot table)

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 {

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

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, I used to use reshape and moved to reshape2 (R 2.15.1). Now I tried some of my older scripts and was surprised that my cast function wasn't working like before. What I did/want to do: 1) Melt a dataframe based on a vector specifying column names as measure.vars. Thats working so far: dfm <- melt(df, measure.vars=n, variable_name = "species", na.rm = FALSE) 2) Recast the

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

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 R-users, I have a data set like this (first ten rows): id patient_id date code class eala ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564262 1562 6.4.2006 12:00 5555 1 NA ID1564264 1365 14.2.2006 14:35 5555 1 50 ID1564265 1342 7.4.2006 14:30 2222 2 50 ID1564266 1648 7.4.200614:30 2222 2 50 ID1564267 1263 10.2.2006 15:45 2222 2 10 ID1564267 1263 10.2.200615:45 3333 3 10 ID1564269 5646

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

I am working with some survival data with missing values. I am using the mice package to do multiple imputation. I have found code in this thread which handles pooling of the MI results: https://stat.ethz.ch/pipermail/r-help/2007-May/132180.html Now I would like to plot a survival curve using the pooled results. Here is a reproducible example: require(survival) require(mice) set.seed(2) dt

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

Hi, I'd like to merge mutliple dataframes from a list of dataframes by some common columns. The approach for simply merging 2 dataframes is working with: merge(df1,df2,by=c("col1","col2","col3"),all=TRUE) For mutliple dataframes in a list I try to use the merge_all command from the package reshape. The documentation states that the command takes a list of

R-helpers: I have a dataset that has 168 subjects and 12 variables. Some of the variables have missing data and I want to use the multiple imputation capabilities of the "mice" package to address the missing data. Given that mice only supports linear models and generalized linear models (via the lm.mids and glm.mids functions) and that I need to fit Cox models, I followed the previous

I read in a CSV file with Data <- read.csv(file="FileName.csv",head=TRUE,sep=",") the file containts strings in the 2nd and 3rd columns and each has about 1000 rows. I need to either loop through the strings there looking for strings that would trigger other logic or remove those rows and put them in another array and loop through them in the new array. I can't seem

Hi, I just started with writing functions in R and so some questions popped up. I provide some values as argument to my function such as: function(a,b,c){} Now i want that the function first checks if the arguments are valid for the function. E.g argument "a" has to be a number in the range 0-1. How can that easily done? So far I have: a <- as.numeric(a) if(0 <= a &&

Hello, I want to use a for loop for repeadely calculating a maxent model (package dismo, function maxent()) which creates an object of the class maxent (S4). I want to collect all the resulting object in a list. I tried to simplify my for loop to explain what I want. There are two problems/questions: 1) How can I create the new variables in the loop (using paste) and assign the objects 2) How

Hi, I have a 1-column dataframe with rownames and I want to sort it based on the single column. The typical procedure that is recommended in diverse posts is to use order in the index. But that "destroys" my dataframe structure. Probabaly it is a very simple solution. Here is a short reproducable example: x <- c(1,3,51,2,34,44,12,33,2,8) df <- data.frame(x) rownames(df) <-

Hello, I am wondering about the X11() graphic device on Windows. I try to plot a raster image but nothing gets displayed. I found some pages where it is mentioned that x11() not always supports raster rendering. Is there any add on for x11, any update or any R-package which solves that displaying problem in Windows? What I try to test it is an example from the package {raster}: library(raster)

Hello, I am wondering about the X11() graphic device on Windows. I try to plot a raster image but nothing gets displayed. I found some pages where it is mentioned that x11() not always supports raster rendering. Is there any add on for x11, any update or any R-package which solves that displaying problem in Windows? What I try to test it is an example from the package {raster}: library(raster)