search for: laply

Given a variable aa in the workspace, some of its attributes are: > typeof(aa) [1] "list" > mode(aa) [1] "list" > length(aa) [1] 2 How do I retrieve the maximum indices, in this case 2,3,4? The variable itself is: > aa [[1]] [[1]][[1]] [[1]][[1]][[1]] [1] 37531.52 [[1]][[1]][[2]] [1] 62787.32 [[1]][[1]][[3]] [1] 5503.184 [[1]][[1]][[4]] [1] 33832.8

...l using source(). At any rate, when I read it into the session using source I get errors and I can't find documentation on what's wrong (or tell from the feedback). Hoping you can help! /Implementing Our Sentiment Scoring Algorithm To score each tweet, our score.sentiment() function uses laply() to iterate through the input text. It strips punctuation and control characters from each line using R?s regular expression-powered substitution function, gsub() and uses match() against each word list to find matches:/ score.sentiment = function(sentences, pos.words, neg.words, .progress=?none?...

Hi all, I have read posts of heat map creation but I am one step prior -- Here is what I am trying to do and wonder if you have any tips? We are trying to map sequence reads from tumors to viral genomes. Example input file : 111 abc 111 sdf 111 xyz 1079 abc 1079 xyz 1079 xyz 5576 abc 5576 sdf 5576 sdf How may xyz's are there for 1079 and 111? How many abc's, etc?

...are named according to the type of object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply which works in a similar way to mapply * r*ply which works in a similar way to replicate You can find out more at http://had.co.nz/plyr/, including a 20 page introductory guide, http://had.co.nz/...

...are named according to the type of object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply which works in a similar way to mapply * r*ply which works in a similar way to replicate You can find out more at http://had.co.nz/plyr/, including a 20 page introductory guide, http://had.co.nz/...

Hi   I have four groups   y1=c(1.214,1.180,1.199) y2=c(1.614,1.710,1.867,1.479) y3=c(1.361,1.270,1.375,1.299) y4=c(1.459,1.335) Is there a function that can give me the length for each, like the made up example below?   >function(length(y1:y2) [1] 3 4 4 2 [[alternative HTML version deleted]]

I have a list of data frames like the following: set.seed(123) a<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) b<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) L<- list(a,b) All data frames in the list have the same dimensions. I need to calculate the sample means for x and y. The real data are lists of several thousand quite large dataframes, so I need

Dear all, I have a question regarding the possibility of parallel computation in plyr version 1.7. The help files of the following functions mention the argument '.parallel': ddply, aaply, llply, daply, adply, dlply, alply, ldply, laply However, the help files of the following functions do not mention this argument: ?d_ply, ?aply, ?lply Is it because parallel computation is not supported for these latter functions? Or is it just because the documentation was not updated for these functions after adding the parallel computation fe...

Hey all, I have a list of matrices. I'd like to calculate the median across all those matrices for each element. What I'd like to end up with is a matrix containing the median of all [1,1] [1,2] etc. elements across all matrices. Is there a concise way of doing that? Thanks!

. HI there, I'd like to show demonstrate how the chi-squared distribution works, so I've come up with a sample data frame of two categorical variables y<-data.frame(gender=sample(c('Male', 'Female'), size=100000, replace=TRUE, c(0.5, 0.5)), tea=sample(c('Yes', 'No'), size=100000, replace=TRUE, c(0.5, 0.5))) And I'd like to create a list of 100

I realize this should be simple, but even after reading over the several help pages several times, I still cannot decide between the myriad "apply" functions to address it. I simply want to apply a function to all the rows (or columns) of the same index from two (or more) identically sized arrays (or data frames). For example: > a=matrix(1:50,nrow=10) >

Hello together, this is ma first post, so please aplogize me if post this in the wrong section. I have problem concerning ma two matrizes. After a regressione and so on, I got two matrizes Matrixres contains the results of ma calculation. Matrixr contains my detiene, which where Aldo used for the regression. Please ser the following code: #Datei einlesen residual =

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >