similar to: transform

Am 27.08.24 um 11:55 schrieb peter dalgaard: > Yes. A quirk, rather than a bug I'd say. One issue is that the internal logic of transform() relies on > > e <- eval(substitute(list(...)), `_data`, parent.frame()) > tags <- names(e) > > so untagged entries in ... will not be included. ... unless at least one is tagged: R> transform(BOD, 0:5, 1:6) Time

The idea is that one wants to write the line of code below in a general way which works the same whether you specify ix as one column or multiple columns but the naming entirely changes when you do this and BOD[, 1] and transform(BOD, X=..., Y=...) or other hard coding solutions still require writing multiple cases. ix <- 1:2 transform(BOD, X = BOD[ix] * seq(6)) On Tue, Jul 24, 2018 at

Note the inconsistency in the names in these two examples. X.Time in the first case and Time.1 in the second case. > transform(BOD, X = BOD[1:2] * seq(6)) Time demand X.Time X.demand 1 1 8.3 1 8.3 2 2 10.3 4 20.6 3 3 19.0 9 57.0 4 4 16.0 16 64.0 5 5 15.6 25 78.0 6 7 19.8 42 118.8 >

I don't think it has much to do with transform in particular: > BOD <- data.frame(Time = 1:6, demand = runif(6)) > BOD[["X"]] <- BOD[1:2] * seq(6); BOD Time demand X.Time X.demand 1 1 0.8649628 1 0.8649628 2 2 0.5895380 4 1.1790761 3 3 0.6854635 9 2.0563906 4 4 0.4255801 16 1.7023206 5 5 0.5738793 25 2.8693967 6 6 0.9996713

I think you meant to call BOD[,1] From ?transform, the ... arguments are supposed to be vectors, and BOD[1] is still a data.frame (with one column). So I don't think it's surprising transform gets confused by which name to use (X, or Time?), and kind of compromises on the name "Time". It's also in a note in ?transform: "If some of the values are not vectors of the

I would like to add a column to the airquality dataset that contains the date 1950-01-01 in each row. This method does not appear to work: > attach(airquality) > data1 <- transform(airquality,Date=as.Date("1950-01-01")) Error in data.frame(list(Ozone = c(41L, 36L, 12L, 18L, NA, 28L, 23L, 19L, : arguments imply differing number of rows: 153, 1 I can't decipher what

The advantages of SQL are that - it can be used from many languages so if you know SQL you can easily move that part of your code to python, say, and visa versa - it is widely used - it can handle data stored outside of R and possibly otherwise too large for R - some SQL databases support multiple concurrent users - depending on the database it may be used to communicate the data to others - one

Is this not supposed to work? > dput(BOD, file = "/BOD.R") > source("/BOD.R") Error in attributes(.Data) <- c(attributes(.Data), attrib) : row names must be 'character' or 'integer', not 'double' > dput(iris, file = "/iris.R") > source("/iris.R") Error in attributes(.Data) <- c(attributes(.Data), attrib) :

I am just starting to code in R and need some help as I am used to doing this in SAS. I have a dataset that looks like this: Chemical Well1 Well2 Well3 Well4 BOD 13.2 14.2 15.5 14.2 O2 7.8 2.6 3.5 2.4 TURB 10.2 14.6 18.5 17.3 and so on with more chemicals.... I would like to transpose my data so that it looks like this: Chemical WellID Value BOD Well1 13.2 BOD Well2 14.2 BOD Well3 15.5 BOD

Hi All, I'm trying to run nls on the data from the study by Marske (Biochemical Oxygen Demand Interpretation Using Sum of Squares Surface. M.S. thesis, University of Wisconsin, Madison, 1967) and was reported in Bates and Watts (1988). Data is as follows, (stored as mydata) time bod 1 1 0.47 2 2 0.74 3 3 1.17 4 4 1.42 5 5 1.60 6 7 1.84 7 9 2.19 8 11 2.17 I then

The behaviour of within() with list input changes if you delete 2 or more variables, compared to deleting one: l <- list(x=1, y=2, z=3) within(l, { rm(z) }) #$x #[1] 1 # #$y #[1] 2 within(l, { rm(y) rm(z) }) #$x #[1] 1 # #$y #NULL # #$z #NULL When 2 or more variables are deleted, the list entries are instead set to NULL. Is this intended?

My apologies in advance for my thickness but I can't seem to solve the following, seemingly simple, data manipulation problem: I have a data frame that contains multiple factors and multiple continuous response variables, but duplicates of some factor combinations. The duplicates contain bad data, so I would like to eliminate the duplicates. I would like to retain the entire rows

Dear all, Is there a less cumbersome way to rename a column by name (as opposed to index) than -- names( X)[ names[ X] == "bob"]<-"sue" ? A semi-related question: how does one get the index of a column by name, something along the lines of col.index( X, "sue") ? Chip Barnaby --------------------------------------------------------- Chip Barnaby

>>>>> peter dalgaard <pdalgd at gmail.com> >>>>> on Mon, 26 Jun 2017 13:43:28 +0200 writes: > This seems to be due to changes made by Martin Maechler in > 2008. Presumably this fixed something, but it escapes my > memory. Yes: The change set (svn -c46441) also contains the following NEWS entry BUG FIXES o

Hi, all I have a question on mgcv and ns. Now I want to compare the results from glm, gam and ns. Take a simple model y~x for example. glm1 = glm(y~x, data=data1) gam1 = gam(y~s(x), data=data1) ns1 = glm(y~ns(x),data=data1) In order to confirm the result from glm1 is consistent to those from gam1 and ns1, I want to define degree=1 in mgcv and ns. I am wondering if there is somebody can give me

Hi all. 1) If I have a dataframe with variable names as follow: PC1 PC2 ... PCn and I want to pass only some of them to a function, e.g. glm(resp~from PC1 to PC10, PC15, etc.,...) is there a faster way than simply writing each variable name in the formula? 2) Again, I have a dataframe, say ali.df, with tha following variables: ali1, ali2, ...ali78 I want to sum, for example, ali1+al2+ali7+f rom

Hello, When I do: dbWriteTable(con, "r.BOD", cbind(row_names = rownames(BOD), BOD)) ...can I specify the data types such as varchar(12), float, double precision, etc. for each of the fields/columns? If not, what is the best way to create a table with specified field data types (with the RpgSQL package/R)? Regards, Ben [[alternative HTML version deleted]]

Hello Given the following data for a data set called airquality. To identify the nature of the objects from the data set airquality example "Ozone" would it be best to use the command is. like is.character(airquality$Ozone) ....... I tried attributes(airquality$Ozone) but it came up null. Would there be a better way to identify these objects. Thanking you in advance for your

Hi All, I've reproduced the example from Prof. Friedrich Leisch's webpage. When I write sweave("Example-1.Snw") OR sweave("Example-1.Rnw"), (yes, I renamed them). I get the following error: Writing to file example-1.tex Processing code chunks ... 1 : echo term verbatim Error: chunk 1 Error in library(ctest) : there is no package called 'ctest' Also while

Hello, I am running randomForest models on a number of species. I would like to be able to automate the printing of dependence plots for the most important variables in each model, but I am unable to figure out how to enter the variable names into my code. I had originally thought to extract them from the $importance matrix after sorting by metric (e.g. %IncMSE), but the importance matrix is n