similar to: melt on OSX ignores na.rm=T

I have a data frame that is the result of a cast (reshape) operation. I deleted the variable column and tried to melt the resulting data frame. Depending on which method I use to delete the column I get different error messages when melting: > head(tinfos) vpn group trial_no item relation trial_type rt variable # 1 102 2 1 4351 diag1 distractor 8471 fix_d 27

Hi, I have a data frame and want to merge adjacent rows if some condition is met. There's an obvious solution using a loop but it is prohibitively slow because my data frame is large. Is there an efficient canonical solution for that? > head(d) rt dur tid mood roi x 55 5523 200 4 subj 9 5 56 5523 52 4 subj 7 31 57 5523 209 4 subj 4 9 58 5523 188 4 subj 4 7

Dear list! > gregexpr("a+(b+)", "abcdaabbc") [[1]] [1] 1 5 attr(,"match.length") [1] 2 4 What I want is the offsets of the matches for the group (b+), i.e. 2 and 7, not the offsets of the complete matches. Is there a way in R to get that? I know about gsubgn and strapply, but they only give me the strings matched by groups not their offsets. I could write

I'd like do a simple xyplot with customized order of panels and try to understand how to use index.cond for that. Several attempts didn't deliver the correct results. Now, I noticed the following: > p <- xyplot(dur~roi|trial, data) > p$index.cond [[1]] [1] 1 2 3 4 5 6 7 8 9 10 These numbers are "valid indexing vector for the integer vector

Hi list! I have a large matrix which I'd like to partition into blocks and for each block I'd like to compute the mean. Following a example where each letter marks a block of the partition: a a a d g g a a a d g g a a a d g g b b b e h h b b b e h h c c c f i i I'm only interested in the resulting matrix of means. How can this be done efficiently?

Hi list! An operation that I often need is splicing two vectors: > splice(1:3, 4:6) [1] 1 4 2 5 3 6 For numeric vectors I use this hack: splice <- function(x, y) { xy <- cbind(x, y) xy <- t(xy) dim(xy) <- length(x) * 2 return(xy) } So far, so good (?). But I also need splicing for factors and I tried this: splice <- function(x, y) { xy <-

Hi list, I have a function that detects saccadic eye movements in a time series of eye positions sampled at a rate of 250Hz. This function needs three vectors: x-coordinate, y-coordinate, trial-id. This information is usually contained in a data frame that also has some other fields. The names of the fields are not standardized. > head(eyemovements) time x y trial 51

Hello, I need to convert dataframe from: ID T0 T1 T2 A 1 2 3 B 4 5 6 C 7 8 9 to: ID Variable Value A T0 1 A T1 2 A T2 3 B T0 4 B T1 5 B T2 6 C T0 7 C T1 8 C T2 9 i tried to use melt cast but it gives me all the time not exactly what I need. Thank

## Can someone suggest a simpler expression than either of these, with the goal ## of taking a long matrix into a wide one with exactly one of the factors converted to ## columns and all the rest retained as factors. I want something that generalizes beyond ## the three factors illustrated here. ## Rich meltTest <- data.frame(A=rep(c("B","C"), each=12),

Dear list, I'm looking for an inverse function of melt(which is in package reshape).Namely, I had a data frame like this (Table1) YEAR VAR1 VAR2 VAR3 1995 7 3 45 1996 5 6 32 1997 6 10 15 I transformed my data by using the melt function and my data was reshaped in the following format: (Table2) YEAR variable

Hi, I have installed R on my computer with windows 7 . I also installed reshape software, but I am not being able to work with melt cast commands . I have chjecked the commands.It is not working. Thankyou, Deepika [[alternative HTML version deleted]]

Hello, I am finding that the melt function from the reshape library causes errors when applied to a data.frame that contains numeric and character columns. For example, melt(id.vars="ID",data.frame(ID=1:3,date=c("a","b","c"),value=c(1,4,5))) ID variable value 1 1 date a 2 2 date b 3 3 date c 4 1 value <NA> 5 2

Hi list, I'm using the package XML to create a simple XML document. Unfortunately constructing the XML tree is extremely slow. My code (see below) adds only about 100 nodes per second on an Intel i5 machine. There's clearly something wrong but I don't see what. Here's a sample of the XML document: <?xml version="1.0" encoding="utf-8"?>

I have a data frame called s3. This data frame has a column called saccade which has two levels 1 and -1. > head(s3$saccade, 100) [1] NA NA NA NA -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 [26] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 [51] 1 1 1 1 1 1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 [76] -1 -1 -1 -1 -1

Esteemed UseRs, This must be embarrassingly trivial to achieve with e.g., melt() and cast(): deduplicating records ("pw.X" in example) for a given set of responses ("cond.Y" in example). Hopefully the runnable example shows clearly what i have and what i'm trying to convert it to. But i'm just not getting it, ?cast that is! So i'd really appreciate some ones

This is my first excursion into using reshape2 and I want to ensure that the melt() function call is syntactically correct. The unmodifed data frame is organized this way: head(tds.anal) site sampdate param quant 1 UDS-O 2006-12-06 TDS 10800 4 STC-FS 1996-06-14 Cond 280 7 UDS-O 2007-10-04 Mg 1620 9 UDS-O 2007-10-04 SO4 7580 19 JCM-10B 2007-06-21 Ca 79 20

Dear R Users, I'm trying to use the reshape package to 'melt' my gridded data into column format. I've done this before on individual files, but this time I'm trying to do it on a directory of files (with variable file names) - therefore I have to also use the 'assign' command. I have come up against a couple of problems however and am therefore seeking advice... >

I have a dataset that is based on crop output for a single crop *sugarcane*...but each observation is further subdivided into 3 kinds of sugarcane i have read the file and have also used melt it to sort it on the basis of *crop group* using melt(sugarcane, m=c("Crop_group")) -> canefile this is how it has cast the data variable value 1 Crop_group Sugarcane

Dear all, I have a grid of 720 columns by 360 rows of global population density values, and hope to convert this to column format using the 'melt' command in the 'reshape' package. I'm not receiving any errors as such, but when the code has finished running, my output looks like this: > head(PopDens.long) Latitude Longitude PopDensity 1 -84.75 V1 0 2

I'm sorry everyone for the inconvenience of spamming the R-help... Here's the complete post: Hi everyone, > > Since it's quite a while that I used the reshape package, I now feel kind > of rusty. > > I have a data.frame like this: > > > > id Sample.Name Marker Allele.1 > Allele.2 sample_id species