search for: dat1new

Dear all, I think this is an easy task, but I don't know how to do it. Specifically, I have 69 columns with 300.000 rows. In each cell there is a code like "2E3", "4RR", etc. I now have a list that replaces this with values, e.g., old new 2E3 5 4RR 3 etc. The list ist about 1600 rows long, so also to extensive for normal solutions Do you how to do that? It would

HI Elisa, You could use ?cut() vec1<-c(33,18,13,47,30,10,6,21,39,25,40,29,14,16,44,1,41,4,15,20,46,32,38,5,31,12,48,27,36,24,34,2,35,11,42,9,8,7,26,22,43,17,19,28,23,3,49,37,50,45) label1<-unlist(lapply(mapply(c,lapply(seq(0,45,5),function(x) x),lapply(seq(5,50,5),function(x) x),SIMPLIFY=FALSE),function(i) paste(i[1],"<x<=",i[2],sep="")))

HI, You may try this: dat1<- read.table(text=" CustID TripDate Store Bread Butter Milk Eggs 1 2-Jan-12 a 2 0 2 1 1 6-Jan-12 c 0 3 3 0 1 9-Jan-12 a 3 3 0 0 1 31-Mar-13 a 3 0 0 0 2 31-Aug-12 a 0 3 3 0 2 24-Sep-12 a 3 3 0 0 2 25-Sep-12 b 3 0 0 0 ",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<- dat1[,-c(1:3)] res<- lapply(seq_len(ncol(dat2)),function(i)

Hi, May be you can try this: dat1New<-? dat1[!(duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE)),] dat2<-dat1[duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE),] ?lst1<-split(dat2,dat2$gene) dat3<-unsplit(lapply(lst1,function(x) {x1<- sum(apply(x[,6:32],2,function(y) y[1]>=y[2]));x2<- sum(apply(x[...

Hello I have dataframe 101 2008-07 0.2898966 102 2008-08 0.3101667 103 2008-09 0.3730476 104 2008-10 0.2717037 105 2008-11 0.1344286 106 2008-12 0.1375000 107 2009-01 0.1781000 108 2009-02 0.2146667 109 2009-03 0.2808235 110 2009-04 0.4326250 111 2009-05 0.3420741 112 2009-06 0.2675238 113 2009-07 0.2478667 114 2009-08 0.3147000 115 2009-09 0.3437826 116 2009-10 0.2057391 117 2009-11 0.1824737 118

Hello, I'm working with a very large dataset (250,000+ lines in its' current form) that includes presence only data on various species (which is nested within different sites and sampling dates). I need to convert this into a dataset with presence/absence for each species. For example, I would like to expand "My current data" to "Desired data": My current data

I have data X and Y, and I want to predict what the very next point would be based off the model. This is what I have: >model=lm(x~y) I think I want to use the predict function, but I'm not exactly sure what to do. Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Linear-Model-Prediction-tp4637644.html Sent from the R help mailing list archive at Nabble.com.

Dear R Users, Could you please help me on the following issue? I have a real large yearly data set. For each year I have 365 flow values. Some of the flow values are not known and that’s why you will see NA written in those slots. I wanted to know, is there a way that I can estimate those values? I tried approx command but it seems least helpful for the kind of issue I am up against.