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...2 b 2 3 c 1 > class(d3$x) [1] ?factor" > d4<-as.data.frame(table(x),stringsAsFactors=F) > class(d4$x) [1] ?character" # Display the code showing the different stringsAsFactors handling in table and matrix: > as.data.frame.table function (x, row.names = NULL, ..., responseName = "Freq", stringsAsFactors = TRUE, sep = "", base = list(LETTERS)) { ex <- quote(data.frame(do.call("expand.grid", c(dimnames(provideDimnames(x, sep = sep, base = base)), KEEP.OUT.ATTRS = FALSE, stringsAsFactors = stringsAsFactors)), Freq =...

...uestion with 14 possible answers. None of the respondents choose the 13th answer, so when I table() the results, R says: 1 2 3 4 5 6 7 8 9 10 11 12 14 31 52 7 21 40 7 8 2 28 2 2 1 17 13 is missing... anyone knows how to tell table() that there are 14 modalities in the answers? I tried with responseName =c("1","2","3","4","5","6","7","8","9","10","11","12","13","14") but all I have is: error in table.... all the arguments must have the same length thank y...

I suspect that the line in the added variable plot (library car) is a SLR of the residuals, but I can't seem to find this written anywhere. Can someone confirm this? Thanks. Tom [[alternative HTML version deleted]]

...t;), attr=paste("attribute=", seq_len(3), sep="")) set.seed(1) data <- rexp(prod(dim)) arr <- array(data=data, dim=dim, dimnames=dimnames) arr[,2,,] <- arr[,2,,]*10 arr[,4,2,2] <- arr[,4,2,2]*10 z <- abs(sweep(arr, 3, 1)) df <- as.data.frame.table(z, responseName="error") ## box plot bwplot(error ~ methods | attr * groups, data=df, as.table=TRUE, notch=TRUE, scales=list(alternating=c(1,1), tck=c(1,0))) ## with relation="sliced" bwplot(error ~ methods | attr * groups, data=df, as.table=TRUE, notch=TRUE, sc...

...""), methods=c(expression(method==1), expression(alpha=1)), attr=paste("attribute=", seq_len(3), sep="")) data <- rexp(prod(dim)) arr <- array(data=data, dim=dim, dimnames=dimnames) z <- abs(sweep(arr, 3, 1)) df <- as.data.frame.table(z, responseName="error") ## box plot bwplot(error ~ methods | attr * groups, data=df, as.table=TRUE, outer=FALSE, strip=TRUE, notch=TRUE, scales=list(alternating=c(1,1), tck=c(1,0)))

LS, I would really like to know how to count the frequency/occurrence of chachters inside a dataset. I am working with extreemly large datasets of forest inventory data with a large variety of different species inside it. Each row inside the dataframe represents one individual tree and the simplified dataframe looks something like this: num species dbh 1 sp1

LS, I would really like to know how to count the frequency/occurrence of chachters inside a dataset. I am working with extreemly large datasets of forest inventory data with a large variety of different species inside it. Each row inside the dataframe represents one individual tree and the simplified dataframe looks something like this: num species dbh 1 sp1

...actor" >> d4<-as.data.frame(table(x),stringsAsFactors=F) >> class(d4$x) > [1] ?character" > > > # Display the code showing the different stringsAsFactors handling in table and matrix: > >> as.data.frame.table > function (x, row.names = NULL, ..., responseName = "Freq", stringsAsFactors = TRUE, > sep = "", base = list(LETTERS)) > { > ex <- quote(data.frame(do.call("expand.grid", c(dimnames(provideDimnames(x, > sep = sep, base = base)), KEEP.OUT.ATTRS = FALSE, stringsAsFactors = stringsAsFactors))...

...@removed))) if(all(i==0)){ return(list()) } else { if(simplify) x@outlier.removal[seq(along=i)[i==0]] <mailto:x@outlier.removal[seq(along=i)[i==0]]<-NULL> <-NULL tmp <- lapply(x@outlier.removal,getRemovedDf.OAD,x@predictorName,x@responseName) if(descrip){ f <- as.data.frame(descrip[!"history"%in%names(x@descrip)]) return(lapply(tmp,function(x)cbind(f,x))) } else { return(tmp) } } } ) MAN FILE \name{getRemovedDf.OAD} \alias{g...

Hello, Currently it's possible to convert an object of class table to a data frame with as.data.frame.table(), but there's no ready-made function, AFAIK, to do the reverse operation, i.e. conversion of a data frame to a table. Do you think it would be a good idea to add a data.frame method to as.table(), to allow such conversions? The idea is that if `x' is a table and `y <-

I have two dataframes, the first column of each dataframe is a unique id number (the rest of the columns are data variables). I would like to figure out how many times each id number appears in each dataframe. So far I can use: length( match (dataframeA$unique.id[1], dataframeB$unique.id) ) but this only works on each row of dataframe A one-at-a-time. I would like to do this for all of

Hello How to pass from table to data-frame ? Thanks

...8 > 9 10 11 12 14 > 31 52 7 21 40 7 8 2 > 28 2 2 1 17 > > 13 is missing... anyone knows how to tell table() that there are 14 > modalities in the answers? I tried with > > responseName > =c("1","2","3","4","5","6","7","8","9","10","11","12","13","14") > > but all I have is: > > error in table.... > all the arguments must h...

hi all, I often have a data frame like this example data.frame(sq=c(1,1,1,2,2,3,3,3,3),area=c(1,2,3,1,2,3,1,2,3),habitat=c("garden","garden","pond","field","garden","river","garden","field","field")) for each "sq" I have multiple "habitat"s each with an associated "area". I

Hello, I have an unbalanced panel data set that looks like: ID,YEAR,HEIGHT Tom,2007,65 Tom,2008,66 Mary,2007,45 Mary,2008,50 Harry,2007,62 Harry,2008,62 James,2007,68 Jack,2007,70 Jordan,2008,72 That is, James, Jack, and Jordan are missing a YEAR. Is there any command that will "fill in" the missing YEAR such that the end result will be balanced and look like: ID,YEAR,HEIGHT

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

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...to xtabs() at the end: "The as.data.frame method for objects inheriting from class "table" can be used to convert the array-based representation of a contingency table to a data frame containing the classifying factors and the corresponding entries (the latter as component named by responseName). This is the inverse of xtabs." For example, from ?xtabs, using the ?UCBAdmissions dataset, which is a 3 dimension table: > str(UCBAdmissions) table [1:2, 1:2, 1:6] 512 313 89 19 353 207 17 8 120 205 ... - attr(*, "dimnames")=List of 3 ..$ Admit : chr [1:2] "Admitted...

Hi R -users, i've a table as describe below. I'm reading the numeric value presented in this table to populate a list. #table #============ #X    A    B    C #x1    2    3    4 #x2    5    7    10 #x4    2    3    5 #============ rawData <- read.table("raw_data.txt",header=T, sep="\t") myList=list() counter=0 for (i in c(1:length(rawData$X))) {     print (i)    

Dear R help group, I am teaching myself linear mixed models with missing data since I would like to analyze a stats design with these kind of models. The textbook example is for the procedure "proc MIXED" in SAS, but I would like to know if there is an equivalent in R. This example only includes two time-measurements across subjects (a t-test "with missing values"), but I