xts

I have data that was programmed to acquire information every 5 hours which means multiple data points per day. The problem is sometimes the data logger fails or batteries die or whatever and there are missing data or failed attempts. All of my analysis I do is based upon these dates. I need to sort and filter and select everything based on this date/time stamp. As of right now I am going through "long winded" scripts just to select and subset my data. Additionally I have several data loggers (individuals) so I am also batch processing. For instance, I want to subset and use only one data point

I have stock data at the tick level and would like to create a rolling list of all ticks for the previous 10 seconds. The code below works, but takes a very long time for large amounts of data. I'd like to vectorize this process or otherwise make it faster, but I'm not coming up with anything. Any suggestions or nudges in the right direction would be appreciated. library(quantmod) set.seed(150) # Create five minutes of xts example data at .1 second intervals mins <- 5 ticks <- mins * 60 * 10 + 1 times <- xts(runif(seq_len(ticks),1,100), order.by=seq(as.POSIXct("1973-03-17 09:00:00"), as

transform() removes the class "xts" qualifier from my xts object: > class(myxts) [1] "xts" "zoo" > myxts = transform(myxts, ABC = 1) > class(myxts) [1] "zoo" Why is that? There's no xts method for transform , so the zoo method is dispatched. The zoo method explicitly creates a new zoo object. > zoo:::transform.zoo function (`_data`, ...) { if (is.null(dim(coredata(`_data`)))) warning("transform() is only useful for matrix-based zoo series") zoo(transform.data.frame(data.frame(coredata(`_data`)), ...), index(`_data`), attr(`_data`, "frequency")) } <environment: namespace:zoo> You could simply

I'm trying to import the financials statements of all the companies listed on the NYSE whose market cap is in greater than the first quartile of the sample. Here is my code : require(TTR) require(quantmod) data.init="2013/01/01" start.date <- as.numeric(gsub("/", "",data.init)) nyse.symbols <- stockSymbols("NYSE")[,-c(3,5)] nyse.symbols <- na.omit(nyse.symbols[which(nyse.symbols[,"MarketCap"]>0),]) ######## Selection Criteria # Filter 1 : stock mkt cap > 1st quartile --> remove the less liquid stocks mktcap.filter <- quantile(nyse.symbols[,"MarketCap"],0.25) nyse.symbols <- nyse.symbols[which

I'm having trouble adding some text to an plot of time series data in R using xts . I've produced a simple example of the problem. My text() command seems to do nothing, whereas I can add a points to the plot. I've tried to keep the code simple by using defaults where possible require(quantmod) # fetch the data and plot it using default options getSymbols('MKS.L') plot(MKS.L$MKS.L.Close) # try to add text - doesn't appear text(as.Date('2012-01-01'),y=500,"wobble", cex=4) # add a point - this does appear testPos <- xts(600, as.Date('2012-01-01')) points( testPos, pch = 3, cex = 4, col = "red" )

I have 3 xts objects all of whose indicies are 'Date' objects: > a a 1995-01-03 1.76 1995-01-04 1.69 > b b 1995-01-03 1.67 1995-01-04 1.63 > c c 1995-01-03 1.795 1995-01-04 1.690 To verify the indices are the same: > index(a) == index(b) [1] TRUE TRUE > index(a) == index(c) [1] TRUE TRUE Now I'm seeing this odd behaviour: > merge.xts(a,b) a b 1995-01-03 NA 1.67 1995-01-03 1.76 NA 1995-01-04 NA 1.63 1995-01-04 1.69 NA While the following merge works fine: > merge.xts(a,c) a c 1995-01-03 1.76 1.795 1995-01-04 1.69 1.690 I can't figure out what could possibly be going on here. Any idea? Update: >