similar to: sapply question

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.

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 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

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

Say I want to perform transformations on row subsets of my dataframe. Do I have to break the dataframe into subsets, perform the analysis on each subset, and rbind() them together again? ..or is there another way. Thank you! [[alternative HTML version deleted]]

Hello, I have a general formatting question. I have two columns of data: ColA <- c("m", "m", "m", "m") ColB<- c("d","d","d","d") And I would like to reorder them into a new column that looks like this: ColC<-

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),

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 =

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

colnames(dd) #[1] "col1" "colb" null_vector<- colnames(dd) sapply(null_vector,makeNull,dd) #???? col1 colb #[1,]?? NA??? 4 #[2,]??? 2?? NA #[3,]??? 3??? 2 #[4,]??? 4?? NA #[5,]??? 1??? 4 #[6,]?? NA??? 5 #[7,]??? 1??? 6 A.K. >I am trying to make a column value in a dataframe = NA if there is a 0 or high value in that column. I need to do this process repeatedly, hence

Hi, I am not sure if this is the right place to ask, so please forgive me if it''s not. I have read most of the documentation regarding shorewall, and found it fairly easy to understand. I am in the process of buying a new house, where I will have my own computer room and a new ISP. I would like to use 1 to 1 NAT on the PC''s. I will hopefully be setting my my network as follows:

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

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

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

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"

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

Why does the subset not work in the which() version below? Thank you v1 <- subset(t1, version_1==as.character("100-1") | version_1==as.character("100-2")) a<-c("100-1", "100-2") v1 <- subset(t1, which(a==as.character(version_1)) != 0) [[alternative HTML version deleted]]

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

Dear baseRs, I recently made a mistake when renaming data frame columns, accidentally creating an NA column. I found the following strange behavior when negative indexes are used. Can anyone explain what happens here. No "workarounds" required, just curious. Dieter Version: Windows, R version 2.6.1 (2007-11-26) #----------------------------- df = data.frame(a=0:10,b=10:20) df[,-2]