similar to: transposing a column table

I am doing cluster analysis on 8768 respondents on 5 lifestyle variables and am having difficulty constructing a dissimilarity matrix which I will use for PAM.  I always get an error:  “cannot allocate  vector of size 293.3 Mb” even if I have already increased my memory to its limit of 4000.  I did it on 2GB , 32-bit OS .  I tried ff and filehash and I still get the same error.  Can you please

Dear R user, Can you please help me. How do I convert part of a cluster analysis output under the heading “Clustering vector” as shown below, showing the clusters to which each respondent belongs to:      [1] 1 1 2 2 1 2 1 2 1 1 2 2 1 2 2 2 2 1 1 1 1 2 2 1 2 2 1 2 2 2 2 2 2 2 2 1 2   [38] 2 1 1 2 2 2 2 2 1 2 1 2 2 2 2 1 2 1 2 2 1 2 2 2 2 2 2 1 2 1 2 2 2 1 1 2 2   [75] 2 1 2 2 2 2 2 2 2 1 1 2

I am running a latent class regression with 3 nominal and 2 ordinal variables using depmixS4 but the available response models do not include one for ordinal response.  How do I go about this?   Penny [[alternative HTML version deleted]]

I did cluster validity using internal and stability measures on 8768 items but I get an error message: “ the number of items to be clustered is larger than maxitems.”  I increased my maxitems to 9000 and still got the same error message.  I partitioned the data into subsections of 600 and was able to get results but it doesn’t make sense to interpret the 15 validity results based on subsections of

On 10/25/2017 12:33 PM, Robert Arkiletian wrote: > here is a python solution > #!/usr/bin/python > #python 2 (did not check if it works) > f=open('yourfilename') > D={} > for line in f: > email,num = line.split() > if email in D: > D[email] = D[email] + num > else: > D[email] = num > f.close() > for key in D: >

On Wed, Oct 25, 2017 at 9:59 AM, Robert Arkiletian <robark at gmail.com> wrote: > On Wed, Oct 25, 2017 at 9:41 AM, Mark Haney <mark.haney at neonova.net> wrote: >> On 10/25/2017 12:33 PM, Robert Arkiletian wrote: >>> >>> here is a python solution >>> #!/usr/bin/python >>> #python 2 (did not check if it works) >>>

Hello there, I have a problem with replication between two domain controllers, dc1 and dc2. Distribution: Debian 8.5 Samba-Distribution: sernet-samba 4.3.11-14 The replication on dc2 working fine without any failures. But the synchronization on dc1 gives the failure "WERR_BAD_NETPATH". Because the message "BAD_NETPATH" I checked the DNS-resolution:

Hello, This must be simple... Thanks a lot - Christoph # Imagine you have a list, e.g: K <- list(1:10, 2:11, 9:18) K # Transforming to dataframe... KK <- as.data.frame(K) # ... one obtaines the list elements as column. KK # But I need the list elements as rows # How can I achieve this? Is there a simple way to transpose data.frames?

I HAVE A VERY BIG DATA OF 67 COLMS AND 25000 ROWS AND WOULD LIKE TO TRANSPOSE IT THE R HELP WAS NOT ENOUGH INFORMATION BECOUSE I AM NOT A PROGRAMMER AND FIRST TIME R USER. SO CAN YOU GIVE SOME HINTS OF CODING, AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC AA TT GG GG CC TO AA AA AA AA AA TT TT TT TT TT GG GG GG GG GG GG GG GG GG GG CC CC CC CC CC [[alternative HTML

I am currently trying to transpose some large panel data set ie transposing multiple rows in into a single column. instead the transpose functionality transposes all rows into columns. my sample data set looks like below: ACCT_NUM ACCOUNT_NAME TRAN_AMT DATE EMPLOYER 101913 GK 7489 30-Apr-10 PENSION 101913 GK 7489 30-May-10 PENSION 101913

Hi, I'm an R beginner and I'm struggling with what should be a rudimentary task. My data is along these lines: ID name1 name2 name3 name4 Class 0 1 0 2 Var1 A B C A Var2 B C C A Var3 C A B A etc. I'm using the following: foo <- data.frame(t(read.table("file", header=FALSE))) but of course now it's not using ID, Class, etc. as column names. As you can imagine,

Hi R, Can I transpose a data frame by a particular group variable? For example: d=data.frame(group=c(1,1,2,2,2),val=c(6,4,6,3,5)) And my output should be: data.frame(group=c(1,2),v1=c(6,6),v2=c(4,3),v3=c(NA,5)) Many thanks, Shubha This e-mail may contain confidential and/or privileged i...{{dropped:13}}

x <- read.table("LittleGarvin.csv", sep=",", header=TRUE) y <- t(x) str(y) chr [1:193, 1:288] "oligocha" "0" " 0" " 0" " 0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:193] "X" "upwd1201" "upwd0502" "upwd0702" ... ..$ : NULL x is a data frame with

Hello, I have a matrix that is a product of tapply on a larger data set. Let's assume it looks like this: X<-matrix(c(10,20,30,40,50,60),2,3) dimnames(X)<-list(c("1","2"),c("1","2","3")) (X) 1 2 3 1 10 30 50 2 20 40 60 Is there an efficient way of transforming this matrix into the following matrix: rows columns entries 1

Dear list, We have a number of files containing similarly structured data: file1: A B C 1 2 3 4 5 6 file2: A B C 7 8 9 10 11 12 ... etc My part of R receives all these data as an array: 1,2,3... 12 together with info about dimensions (row,col,fileN) . ( Converting the data into 3D cannot simply done by: array(x, c(2,3,2)) because breaks the structure (e.g. 1,3,5 is type mismatch)

Hello, everyone! I have a very simple task - I have a data frame (see MyData below) and I need to stack the data (see result below). I wrote the syntax below - it's very basic and it does what I need. But I am sure what I am trying to do is a very typical task and there must be a much shorter/more elegant way of doing it. Any advice? Thank you very much!

Hi. I have repeated measures data of the form where each observation is a trial, and trials are grouped by subject, and variables encode whatever level of a factor was present during that trial, and the dependent variable is response time (RT). I want to transpose the data to a form suitable for MANOVA such that there is one observation per subject and RT is recoded across many

Hi, I'm new to R and I have a file with many rows of values. Each row contains a title and values for a contingency table e.g. row 1= title 8 0 37796 47 which is a table called 'title' with values 8 0 37796 47 I would like to know how I can import this using R and for each row calculate a p value using the fisher test. Using each p value I will do multiple a correction. I am

I have trying to figure this out all day so hopefully the answer isn't too obvious. I am able to view a graph in the viewer window. However, I need to export graph outside of the viewer window. Here is the script I am using: > png("Compare.png") > plot(compare$DepthSLI, compare$DischargeSLI, col="blue", xlab = "Average Water Depth (cm)", ylab =

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