similar to: skip for loop

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Hi R users, I have a dataframe in the below format xyz 01/03/2007 15.25 USD xyz 01/04/2007 15.32 USD xyz 01/02/2008 23.22 USD abc 01/03/2007 45.2 EUR abc 01/04/2007 45.00 EUR

Hi R, When I use the below to write the text file try=data.frame(rep("a",5), rep("b",5)) write.table(try,"z:\\try.txt",row.names=F,col.names=F,sep="\t") the output contains two columns with quotes! Is there a way to write without quotes? I tried try[,1]=noquote(try[,1]) try[,2]=noquote(try[,2]) Thank you, Regards, Ravi Shankar

Hi R, I have a list > class(pp2) [1] "list" > length(pp2) [1] 1244 It is in the below format RIC Trade.Date Close.Price Currency.Code Convertion.Rate New.Price ABCD.SZ 2008/02/29 15.30 CNY 0.1408 2.154240 ABCD.SZ 2008/01/31 15.27 CNY 0.1392 2.125584 ABCD.SZ 2007/12/31 14.88 CNY 0.1371 2.040048

Hello, I have imported data from Excel using the command cours=read.delim("w:/apprentissage/cours_2.txt") after transforming my initial file with tab delimiters It seemed to work It is 2-dimensionnal. When I type cours[5,5], I get this type of message : "[1] 0,9760942761824 Levels: 0,495628477 0,893728761 0,89640592 0,903398558 ... 3,864414217" And when I want to

Hi, I want to time how long a function takes to execute. Any clues on what to search for to achieve this? Thanks in advance. -- View this message in context: http://r.789695.n4.nabble.com/timing-a-function-tp2126319p2126319.html Sent from the R help mailing list archive at Nabble.com.

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I have a TS of monthly observations. head(data4) 1991(1) 1991(2) 1991(3) 1991(4) 1991(5) 1991(6) 12.00864 11.94203 11.98386 12.01900 12.19226 12.15488 Now I want to make 11 dummy variables indicating months. Therefore I did followings : For Jan : rep(c(rep(0,0), 1, rep(0, 11)), 17) For Feb : rep(c(rep(0,1), 1, rep(0, 10)), 17) ........ and so on But my

Hi. In a data set I have a variable that takes values from 1 to 14. For each subgroup of values of this variable, I would like to obtain some descriptive statistics of other variables present in the data set. I've been trying with a "for" loop but I couldn't get nothing. Could you please suggest me some lines? -- View this message in context:

Dear R users, I'm looking for tools to perform optimization subject to constraints, both linear and non-linear. I don't mind which algorithm may be used, my primary aim is to get something general and easy-to-use to study simples examples. Thanks for helping, Gildas

Dear all, i have 2 lists of data with each of the list contain 14 columns. How am i going to extract column 12 and 13 from each of the list ?? and can i combine my extracted columns to form a single list. Attach with are my data. Your coorperation is highly appreciated. Many thanks Regards, Anisah -------------- next part -------------- An embedded and charset-unspecified

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Hi R users, I am using RMySQL to connect to a database in MySQL. I have 3 questions. 1)When I give the following command dbListTables(con) I get the output stack imbalance in .Call, 142 then 143 stack imbalance in <-, 140 then 141 stack imbalance in {, 138 then 139 stack imbalance in standardGeneric, 126 then 127 stack imbalance in class, 121 then 122 stack imbalance in

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Hi, I am using the CrossTable function from library(gmodels). x=unique(data[,c("L1","L1_Revenues","RIC")]) L1_Classification=CrossTable(x$L1,x$L1_Revenues,exclude = c("NA","","0%","0"),prop.r=FALSE,prop.c=FALSE,prop.t=FALSE,prop.chisq=FA LSE,dnn=c("L1_Classification","Revenue")) What I would like

I'm trying to work out the simplest way to remove the upper and lower quantiles, in this case upper and lower 25% from an array. I can do it in two steps but when I try it in one, it fails. Is there something simple missing from my syntax or are there other simple elegant way to accomplish this? Thanks J > i <-1:20 > i2 <- i[i<quantile(i,.75)] > i3 <-

Hi R, I was using 'as.dendrogram' with the DIST coefficient, where the smaller values of the DIST coefficient, say that the objects are closer to each other, while the larger values of the coefficient say that the objects are far from each other. But now, I have my coefficient as the DICE coefficient(in some sense similar to correlation coefficient), where the larger coefficient

I don't see much in the way of an ability to write reports in R the way you can with SAS. You basically have to write a program with R in a 3G way unlike SAS with it's 4G proc print and proc report. Are there similar R functions and packages? -- View this message in context: http://r.789695.n4.nabble.com/R-reports-tp2330733p2330733.html Sent from the R help mailing list archive at

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