similar to: Reshape Columns

Hi, I am trying to use the nls() function to closely approximate a vector of values, colC and I'm running into trouble. I am not sure how if I am asking the program to do what I think its doing, because the same minimization in Excel's Solver does not run into problems. If anyone can tell me what is going wrong, and why I'm getting a singular convergence(7) error, please tell me. I

Dear all, I have a problem with the "subset()" function. I spent all day yesterday with a collegue to solve it and we did not find a satisfying solution (even in the archived mails), so I ask for your help. Let's say (for a simple example) a matrix mat: R> mat cola colb colc [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 My goal is to select the lines of the matrix on the basis of the

Hi, I have two dataframes: The first, df1, contains some missing data: cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 The second, df2, contains the following: cola colb colc cold cole 1 1.4 0.8 0.02 1.6 0.6 I'm wanting all missing data in df1$cola to be replaced by the value of df2$cola.

Hello all! I am currently trying to sort a data frame in a particular way, but I am having some difficulties with this. Specifically I want to sort the below dataset in such a way that there is only one line per ProteinID and if there are multiple GeneID or GeneName entries for a single proteinID, that they be concatenated with a comma separating them. The way I have done it earlier worked fine

Why does this sapply code change df3 but not df1? Thanks df1 <- read.table(text=" cola colb colc cold cole 1 NA 5 9 NA 17 2 NA 6 NA 14 NA 3 3 NA 11 15 19 4 4 8 12 NA 20 ", header=TRUE) df2 <-df1*2 df1 df2 df3 <-sapply(names(df1),function(x) {df1[[x]]<- df2[[x]]}) df1 df3 [[alternative HTML version deleted]]

Hi, I am making my way down the learning curve of R, and find it a great language with so many helpful users! Below is an example of what I'm trying to do, but can't quite figure out the right path to go down. Here's what I have: Main is a time series of data with columns Cola and Colb Cola Colb 1 1 1 2 1

Hello every body, I am quite a new user of R so I beg your pardon for this naive question and the lake of syntax with wich I ask it: I have a data frames like this: cola colb 1 c 1 i 1 i 1 c 2 i 2 c 2 c 2 i 2 i ... 10000 I would like ,for each level of cola and for x in colb: -if colb[x]=="i" and colb[x-1] does not exist (first row in dataframes), then replace colb[x] by

Dear R users, First of all sorry for this question, surely quite naive. (I searched on the R site but was unable to find by myself). I have a table, called infile : 1 2 3 4 5 6 7 8 9 I would like to read it and ignore the rows with 1st element > 3 I do it now with a for loop, and it's ok, but I was expecting something simpler, like : intable = read.table(infile); newtable =

Greetings all, I am getting an error message that is stifling me. Any ideas? > ## Define Directories ## > load_from <- "/home/mcc/Dropbox/abrodsky/kegg_combine_data/" > save_to <- "/home/mcc/Dropbox/abrodsky/ttest_results/" > > ############################### > ## Define Columns To Compare ## > compareA <- "log_b_rich" > compareB

Hi, May be this helps: funcName<- function(df1, x){ ?whatCol=df1[[x]] ?print("Got it") ?print(whatCol) ?} ? funcName(df,"ColA") #[1] "Got it" #[1] 1 2 3 4 5 ? funcName(df,"ColB") #[1] "Got it" #[1] A B C D E #Levels: A B C D E A.K. >I am trying to extract the 2nd column from a dataframe using a function called funcName. Note this is an

Greetings all, I am curious to know if either of these two sets of code is more efficient? Example1: ## t-test ## colA <- temp [ , j ] colB <- temp [ , k ] ttr <- t.test ( colA, colB, var.equal=TRUE) tt_pvalue [ i ] <- ttr$p.value or Example2: tt_pvalue [ i ] <- t.test ( temp[ , j ], temp[ , k ], var.equal=TRUE) ------------- I have three loops, i, j, k. One to test the all of

Hello All, I need to create a three-way interaction plot and I was wondering if anyone could recommend a package I could use to design these plots. Thank you! ________________________________ PHRI DISCLAIMER This information is directed in confidence solely to the person named above and may not otherwise be distributed, copied or disclosed. Therefore, this information should be considered

Gracias, Carlos. Habia pensado en algo similar usando sapply(): sapply(seq(1, ncol(vtmp), by = 2), function(i) c(rbind(as.character(vtmp[, i]), as.character(vtmp[, i+1])))) Dependiendo de la dimension de los datos, quizas mapply() sea mas eficiente que sapply(). Saludos cordiales, Jorge.- 2015-02-25 1:01 GMT+11:00 Carlos Ortega <cof en qualityexcellence.es>: > Hola, > > Este

Hi All, I have a question regarding contingency tables. I would like to calculate the mean and standard deviation of a continuous variable from my own dataset based on the percentages of a contingency table I obtained from a scientific article. dataset<- data.frame(cbind(case=rep(0:1,5), x1=c(1:10), x2=c(0:9))) contingency_table<- matrix(c(100, 75, 65, 85, 90, 87), nrow=3, ncol=3) In

Excelente! Ahora corre muy rápido. No conocía ese método, creo que me va a resultar muy útil. Muchas gracias y saludos. Fernando Macedo El 24/02/15 a las 10:51, Jorge I Velez escribió: Fernando, Podrias intentar R> a <- rep('a', 5) R> b <- rep('b', 5) R> a [1] "a" "a" "a" "a" "a" R> b [1] "b"

Dear Group: I have 72 files (.txt). Each file has 2 columns and column 1 is always identical for all 70 files. Each file has 90,799 rows and is standard across all files. I want to create a matrix 40(rows) x 70 columns. I tried : temp = list.files(pattern="*.txt") named.list <- lapply(temp, read.delim) library(data.table) files.matrix <-rbindlist(named.list) >

Dear R Help: I am trying to sum data from one column in a dataframe based on a value in another. I do not know how to do this easily in R. For example: Col A Col B 1 0 3 0 2 1 2 0 1 0 4 0 1 1 9 1 3 0 5 0 2 1 I would like to cumsum the values in Col A for all rows where Col B is 0, and a value of 1 in Col B will reset

OK, I need help!! I've been searching, but I don't understand the logic of some this dataframe addressing syntax. What is this type of code called? test [["v3"]] [is.na(test[["v2"]])] <-10 #choose column v3 where column v2 is == 4 and replace with 10 and where is it documented? The code below works for what I want to do (find the non-missing value in a row),

Hi, Following previous discussion on this list (http://tolstoy.newcastle.edu.au/R/devel/05/12/3439.html) I have created a package as suggested, and uploaded it to CRAN incoming : data.table.tar.gz. ** Your comments and feedback will be very much appreciated. ** >From help(data.table) : This class really does very little. The only reason for its existence is that the white book specifies

I am trying to read some data off the zillow site. Newbie to xml, html, parsing and the xml package. I've been able to load the web page I'm interested with the following code but I'm not sure of the next step to get the information I'm interested in into R : library(XML) url <- "http://www.zillow.com/homes/511 W Lafayette St, Norristown, PA_rb" doc <-doc <-