similar to: Access variables by string

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

Hi Folks, I'm wondering if there's a secret trick to achieve the following. I have some big code for analysis related to a named variable, which will be one of several in the columns of a dataframe, and I would like to be able to choose between a run for just one of these variables, or a run which loops over them all. So, for a single run, I could have the following kind of thing in a

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?

Hi Justin, my class is a visitor pattern and I use accept method to go recursive in suboject in my AST. In locals I store AllocaInst pointer. void *visit(var1_init_decl_c *symbol) { llvm::Type *lType; varNames.clear(); varType = ""; symbol->var1_list->accept(*this); /* get a vector contains variable names */ symbol->spec_init->accept(*this); /* Store in

>>>>> 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

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

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

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

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

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

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, I am trying to produce a 30x30 lattice grid. The 30 variables naturally fall into three groups of ten and I would like to add thicker axis lines around these to highlight this. However, I can only do this separately, so far, and I don't know how to superimpose the grid with the thicker lines (separating the 10x10 groups) onto the overall grid of all 30x30 plots. I enclose a

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

On Fri, Jan 11, 2013 at 8:20 AM, Manuele Conti <manuele.conti at sirius-es.it>wrote: > Hi Justin, > my class is a visitor pattern and I use accept method to go recursive in > suboject in my AST. > In locals I store AllocaInst pointer. > > > void *visit(var1_init_decl_c *symbol) { > llvm::Type *lType; > > varNames.clear(); > varType = "";

Hi all, I am reading books and tutorials about R. I don't understand the following: plot(salary~rank, data=salary) plot(Ozone~date, data=airquality) I don't understand what does "~" here, and how can plot() have a input argument called "data"... I have looked it up in "plot"'s help but I could not find about argument "data". Could you please

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

I could use some help understanding how nls parses the formula argument to a model.frame and estimates the model. I am trying to utilize the functionality of the nls formula argument to modify garchFit() to handle other variables in the mean equation besides just an arma(u,v) specification. My nonlinear model is y<-nls(t~a*sin(w*2*pi/365*id+p)+b*id+int,data=t1,

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

Muy buenas. Quiero hacer un loop en el que en cada iteración se hace un subset con el que se queda con las muestras para la que cierta variable es positiva. Si hago esto, sale bien: df2<-subset(df, subset = var1>0) Pero he probado así (y de no sé cuantas formas más), antes de hacer el for, y no sale: GT<- c("var1","var2", ? ) df2<-subset(df,

Dear R-devel list, I realized that removing a predictor in lm through the "-"'s operator in formula() does not affect the complete cases that are considered. A minimal example is: summary(lm(Wind ~ ., data = airquality)) # 42 observations deleted due to missingness summary(lm(Wind ~ . - Ozone, data = airquality)) # still 42 observations deleted due to missingness, even if only 7