similar to: need help on melt/cast

Hello, I have a data x with normal (or very close to normal) distribution, I can plot a density distribution with density(x,...). My question is is there any way to calculate an area under this distribution (=probability) for particular range of x values, let's say for x from 0 to 2? I was not able to find any kind of simple procedure to do this. Thanks in advance for your help, Evgeny.

## 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),

Hello, I'm trying to produce some plots in ggplot2 to use them on the dark-blue gradient background. I am wondering if there is already any theme/set of options that I can use to change the color scheme and add transparency. Thank you very much, Evgeny. [[alternative HTML version deleted]]

Hi the list. Is there a bug in mmlcr package ? The following code does not compile: mmlcrTest <- function(dataW){ dataL <- reshape(dataW,idvar="id",timevar="T",varying=list("T0","T1","T2"),direction="long",v.names="score") resultR <- mmlcr(outer= ~ 1 | id, components = list(list(formula =

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]]

I'm in the middle of my own little intellectual exercise comparing dcast() and reshape() and have successfully stumped myself. I want to melt() a data frame, then dcast() it into a new form. After doing so, I want to duplicate the process using reshape(). So far, I can do the melt and cast require(reshape2) Raw <- data.frame(site = c(1, 1, 1, 1, 2, 2, 2, 2), id =

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

List, I want to reshape my data, but I'm not sure how to do it... it might be a simple task, but don't know which package does this. "occ.data" (see below) is how my original data are arranged, and I know that with melt() I can reshape it like "y" (see below). However, I just want to build a matrix like the "y" matrix, but with only 2 dimensions. Something

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

Hi there, I am trying to reorganized my data sets so that it is easy for MARK to read it. Basically I have the encounter histories of 1837 butterflies The data looks like this the first 4 columns are the occasions and the last two code for male and female > t1 t2 t3 t4 M F > 1 0 0 0 1 0 male capture on time1 but not seen on time 2, 3 > and 4 > 1 0 0 0

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

I would appreciate some advice on the following task. I have some data that currently looks like this: t1 <- data.frame(id=c(1,1,2,2), aspect=c("A","B","A","B"), score=c(10,9,11,12)) I'd like it to look like this: id A B 1 10 9 2 11 12 reshape() looks like a good candidate for this job but I'm not really sure about the roles of

Hi, I'm trying to melt() some data for subsequent cast()ing and am encoutering errors. The overall process requires a couple of casts()s and melt()s. ########Start Session 1########## ## I have the data in a (fully) melted format and can cast it fine... > norm1[1:10,] Pool SNP Sample.Name variable value 1 1 rs1045485 CA0092 Height.1 0.003488853 2 1 rs1045485

Hi all, I have played a bit with the "reshape" package and function along with "melt" and "cast", but I feel I still don't have a good handle on how to use them efficiently. Below I have included a application of "reshape" that is rather clunky and I'm hoping someone can offer advice on how to use reshape (or melt/cast) more efficiently. #For this

Dear R helpers, I have a data.frame as given below - dat1 = data.frame(date = as.Date(c("3/30/12","3/29/12","3/28/12","3/27/12","3/26/12", "3/23/12","3/22/12","3/21/12","3/20/12", "3/30/12","3/29/12","3/28/12","3/27/12",

Hi R Forum I am a newbie to R and I have been amazed by what I can get my team to accomplish just by implementing Scripting routines of R in all my team's areas of interest.. Recently i have been trying to adopt R scripting routine for some analysis with longitudanal data.. I am presenting my R script below that I have tried to make to automate data analysis for longitudanal data by employing

I am trying to reshape a data set. Could someone please help me with the reshape, cast, and melt functions? I am new to R and I have tried reading up on how to use the reshape package, but I am very confused. Here is an example of what I am trying to do: subject coder score time [1,] 1 1 20 5 [2,] 1 2 30 4 [3,] 2 3 10 10 [4,] 2 2

Greetings all, I am having difficulty transposing, reshaping, flipping (not sure which) a data frame which is read from a DBF file. I have tried using t(), reshape() and other approaches without success. Can anyone please suggest an way (elegant or not) of flipping this data around ? The initial data is like propsum (defined below), and I want it to look like tpropsum once reformed. >

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 list, I run R on Linux and OSX. On both systems I use R version 2.9.2 (2009-08-24) and reshape version: 0.8.2 (2008-11-04). When I do a melt with na.rm=T on a data frame I get different results on these systems: library(reshape) x <- read.table(textConnection("char trial wn p E10I13D0 4 r E10I13D0 4 a E10I13D0 4 c E10I13D0 4 t E10I13D0 4 i E10I13D0 4 c E10I13D0 4 e E10I13D0