similar to: na.omit leaves cases with NA's intact

I've seen how to replace the NA's in a single column with a data frame *> mydata$ncigs[is.na(mydata$ncigs)]<-0 *But this is just one column... I have thousands of columns (!) that I need to do this, and I can't figure out a way, outside of the dreaded loop, do replace all NA's in an entire data frame (all vars) without naming each var separately. Yikes. I'm racking my

Not sure where to even start on this.... I'm hoping there's some debugging I can do... I have a loop that cycles through several different data sets (same structure, different info), performing randomForest growth and predictions... saving out the predictions for later study... I get about 5 hours in (9%... of the planned iterations.. yikes!) and R just freezes. This happens in

"classwt" in the current version of the randomForest package doesn't work too well. (It's what was in version 3.x of the original Fortran code by Breiman and Cutler, not the one in the new Fortran code.) I'd advise against using it. "sampsize" and "strata" can be use in conjunction. If "strata" is not specified, the class labels will be used.

Sorry for the repost, but I've really been looking, and can't find any syntax direction on this issue... Just browsing the documentation, and searching the list came up short... I have some unbalanced data and was wondering if, in a "0" v "1" classification forest, some combo of these options might yield better predictions when the proportion of one class is low (less

Ok, I know R isn't an optimal environment for looping (or so I've heard) but I have a need to loop through columns of data and create new columns of data based on calculations within rows... I'm sure there's a help file, but I'm not sure what search terms to use to find it! The problem is that these new columns need to have names that I can later access... Like NewVar1,

I have a very large data frame, and I'm doing a conversion of all columns into factors. Takes a while (thanks to folks here though, for making faster!), but am wondering about optimization from a memory perspective... Internally, am I better off assigning into a new data frame, or doing one of these: dataframe<-someoperation(dataframe) It would seem that re-assigning into the same data

I have two xts objects, call them "a" and "b", and am trying to merge them... > class(a) [1] "xts" "zoo" > class(b) [1] "xts" "zoo" > head(a) 2010-04-01 7.6343 2010-04-02 7.6343 2010-04-03 7.5458 2010-04-04 7.4532 2010-04-05 7.4040 2010-04-06 7.3317 > head(b) 2010-04-01 568.80 2010-04-05 571.01 2010-04-06

You can test if the problem is accumulation in memory registers, which is certainly what this sounds like. Just do a loop over a reasonably small number of iterations and store or print the time between each iteration. If memory accumulation it will run optimally for the first few iterations, after which the time will increase noticeably (essentially exponentially, hence ultimately freezes up). If

Hello, all-- I am having some fun playing with the graphing in quantmod-- very nice! I am writing a function to calculate (and hopefully plot) support and resistance lines, but the usual plot call of "abline(h=value)" does not seem to work. Here's my code: require(quantmod) AAPL<-getYahooData("AAPL") candleChart(AAPL,subset="last 3

I have and XTS time series object that has date and time. I started with 1 minute data and used apply.daily(x, sum) to sum the data to one cumulative value. This function works just fine however it leaves a time for the last summed value which looks like this 2006-07-19 14:58:00. I need to just have the date and to remove the time value of 14:58:00 just leaving the date value of 2006-07-19 .

Hi, folks! I'm trying to pull in data using read.csv("my URL goes here"), and it really works fantastically. Amazing to pull in live data right off the internet, into RAM, and get busy... however... occasionally there is a server problem, or the data are not up yet, and instead of pushing through a nice CSV file, the server sends a 404 "Not Found" page... Since the

I know I've done this before, but it's been a while and I can't find quite what I need in the help files or archives. I have a text field in a very large data frame. I'd like to add a column that represents the value from an existing field, from the next record (the data are sorted). I'm trying to represent "what happens tomorrow", so the "today" row would

I have this little data.frame http://dl.dropbox.com/u/102669/nanotna.rdata Two column contains NA, so the best thing to do is use na.locf function (with fromLast = T) But locf function doesn't work because NA in my data.frame are not recognized as real NA. Is there a way to substitute fake NA with real NA? In this case na.locf function should work Thank you

The National Ambulatory and Medical Care Survey is a free data set from the CDC that I'd like to analyze using the "Survey" package in R. Before I dive in, though, it occurred to me that someone may already have gone to the trouble of writing code that will bring in the data and assign the variable names and value labels. This is a big file, so doing it from scratch will take

I have data where where I've taken some measurements three times... twice in rapid succession so I could check test-retest reliability of a piece of equipment, and then a third measurement some time later. Not I'd like to do an analysis where I have two scores... the first being the mean of the first two taken the same day, and the second being the one taken later. I have a lot of

Hi to all, i'm new to R I have an xts object. Can i find: a) how many NA are in my object ? b) eventually where (in which line) they are Thank you

Just giving the survey package a spin... I'm accustomed to stata, and it seems very similar in many respects. One thing is throwing me, however. I've gotten my data in, and specified the design. Looks like the weighting is right (based on published population estimates from these data), but now I'd like to check my "marginal means" for proportions against those that have

Hello, all... I've been playing with the TTR package and quantmod, and I'm loading the Chicago Board of Exchange put/call ratio data via a simple read.csv call... CBOEtotal<-read.csv(file=" http://www.cboe.com/publish/ScheduledTask/MktData/datahouse/totalpc.csv ",skip=1) this gives me a data frame with columns.... > names(CBOEtotal) [1] "Trade_date"

Hello, all. I wanted to use the "survey" package to analyze data from the National Ambulatory Medical Care Survey, and am having some difficulty translating the analysis keywords from one package (Stata) to the other (R). The data were collected using a multistage probability sampling, and there are variables included to identify the sampling units and weights. Documentation from the

I am reading several hundred files. Anywhere from 50k-400k in size. It appears that when I read these files with R 2.15.1 the process will hang or seg fault on the scan() call. This does not happen on R 2.14.1. This is happening on the precise build of Ubuntu. I have included everything, but the issue appears to be when performing the scan in the method parseTickData. Below is the