similar to: multi-line query

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, Using the RpgSQL package, there must be a way to get the row names into the table automatically. In the example below, I'm trying to get rid of the cbind line, yet have the row names of the data frame populate a column. > bentest = matrix(1:4,2,2) > dimnames(bentest) = list(c('ra','rb'),c('ca','cb')) > bentest ca cb ra 1 3 rb 2 4 >

Hi, I post this message to the general r-help list hoping anyone within a wider range have suggestions: There are three ways to integration R and postgres, especially on 64bit Microsoft windows Platform, 1. via RODBC package, which has 32 bit and 64 bit version for windows 2. via RPostgres interface, which only has 32bit version currently 3. via plr for Greenplum, which only supports a

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

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) :

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

Hello, I have a nasty loop that I have to do 11877 times. The only thing that slows it down really is this merge: xx1 = merge(dt,ua_rd,by.x=1,by.y= 'rt_date',all.x=T) Any ideas on how to speed it up? The output can't change materially (it works), but I'd like it to go faster. I'm looking at getting around the loop (not shown), but I'm trying to speed up the merge first.

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 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

One oddity in transform that I recently noticed. It seems that to include a one-column data frame in the arguments one must name it even though the name is ignored. If the data frame has more than one column then it must also be named but in that case it is not ignored and the names are made up of a combination of that name and the data frame's names. I would have thought that if we did not

Hello, Thanks in advance for any help! How do I pass an unknown number of objects into the "..." (dot dot dot) parameter? Put another way, is there some standard way to pass multiple objects into "..." to "fool" the function into thinking the objects are passed in separately/explicitly with common separation (like "x,y,z" when x, y and z are objects to be

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

Hello, Does anyone know how to get the rounding method used for the axis tick numbers/values in plot()? I'm using mtext() to plot the values used to plot vertical and horizontal lines (using abline()) and I'd like these vertical and horizontal line values to be rounded like the axis tick values are rounded. In other words, I want numbers plotted with mtext() to be rounded in the same

Hello, How do I get the dates of all Fridays between two dates? thanks, Ben [[alternative HTML version deleted]]

Hello, I'd like to understand 'what' is predicting the response for library(mgcv) gam? For example: library(mgcv) fit <- gam(y~s(x),data=as.data.frame(l_yx),family=binomial) xx <- seq(min(l_yx[,2]),max(l_yx[,2]),len=101) plot(xx,predict(fit,data.frame(x=xx),type="response"),type="l") I want to see the generalized function(s) used to predict the response

I would like to write a function that computes Tukey's 1 df for nonadditivity. Here is a simplified version of the function I'd like to write: (m is an object created by lm): tukey.test <- function(m) { m1 <- update(m, ~.+I(predict(m)^2)) summary(m1)$coef } The t-test for the added variable is Tukey's test. This won't work: data(BOD) m1 <- lm(demand~Time,BOD)

Hello, Is there a faster way to do this? Basically, I'd like to NA all values in all_data if there are no 1's in the same column of the other matrix, iu. Put another way, I want to replace values in the all_data columns if values in the same column in iu are all 0. This is pretty slow for me, but works: all_data = matrix(c(1:9),3,3) colnames(all_data) =

Hello, What is the best way to get ranks for a vector of values, limit the range of rank values and create equal count in each group? I call this uniform ranking...uniform count/number in each group. Here is an example using three groups: Say I have values: x = c(3, 2, -3, 1, 0, 5, 10, 30, -1, 4) names(x) = letters[1:10] > x a b c d e f g h i j 3 2 -3 1 0 5 10 30 -1 4 I

I ran a function called BoxCox, taken from the book by Venables and Ripley, for checking the need for power transformation. This function works fine using the version 0.50 of R, but gives an error message with version 0.60. The lm function in version 0.60 is different from that in version 0.50. Is there a bug in the new lm function? Kung-Sik Chan >

Hello, I'm posting this again (with some small edits). I didn't get any replies last time...hoping for some this time. :) Currently I'm only coming up with brute force solutions to this issue (loops). I'm wondering if anyone has a better way to do this. Thank you for your help in advance! The problem: I have endpoints of one x range (x_rng) and an unknown number of s ranges