similar to: time plotting problem

Hello I have a string which contains microseconds, can anyone help on constructing this in to a time object, with the microseconds, that I can take to a ZOO file? Thanks Sean > UK[1,3] [1] "17:09:53.824" > UK[1,1] [1] "2007-12-11 00:00:00" > mydates <- paste( substr(UK[,1], 1, 10), UK[,3]) > mydates[1] [1] "2007-12-11 17:09:53.824" >

I noticed something surprising (in R 2.2.1 on WinXP) According to the documentation, rownames and colnames are character vectors. Assigning a vector of class POSIXct or POSIXlt as rownames or colnames therefore is not strictly according to the rules. In some cases, R performs a reasonable typecast, but in some other cases where the same typecast also would be possible, it does not. Assigning a

I noticed something surprising (in R 2.2.1 on WinXP) According to the documentation, rownames and colnames are character vectors. Assigning a vector of class POSIXct or POSIXlt as rownames or colnames therefore is not strictly according to the rules. In some cases, R performs a reasonable typecast, but in some other cases where the same typecast also would be possible, it does not. Assigning a

Hi all I was wondering whether there has ever been an update on the rownames and colnames behaviour as described by Eric below? I still get the same behaviour, exactly as described by Eric, on my WinXP installation of R-2.3.0. I also posted a message to r-help on Friday but looking through the online archives it seems to have not made it to the list. I would agree with Eric that a consistent

Hello! I have my data frame "mydata" (below) and data frame "reference" - that contains all the dates I would like to be present in the final data frame. I am trying to merge them so that the the result data frame contains all 8 dates in both subgroups (i.e., Group1 should have 8 rows and Group2 too). But when I merge it it's not coming out this way. Any hint would be

Hello, I was wondering, is there a way to plot estimated betas and standard deviations that I've generated? Specifically, I have the following: A matrix of estimated betas (two different betas, 4 different simulations - categories). A matrix of estimated standard errors corresponding to each of those betas. I would like to plot the estimated beta, and make a confidence

Hi, all Here I created a data frame like mydates<- seq(as.Date("2010-05-29"), length = 43, by = "day") myvalues<-runif(43,0,1) myframe<-data.frame(dates=mydates, day=weekdays(dates), value=myvalues) dates day value 1 2010-05-29 Saturday 0.14576143 2 2010-05-30 Sunday 0.37669604 3 2010-05-31 Monday 0.74813943 4 2010-06-01 Tuesday

Dear everybody, I have the following challenge. I have a data set with 2 subgroups, dates (days), and corresponding values (see example code below). Within each subgroup: I need to aggregate (sum) the values by week - for weeks that start on a Monday (for example, 2008-12-29 was a Monday). I find it difficult because I have missing dates in my data - so that sometimes I don't even have the

Dear Researches, sorry for disturb. I wish to improve my figure in R plotting the relative frequencies of my data set. library(lattice) a <- c(0,0,0,1,1,2,4,5,6,7,7,7,7,7,8,8,8,8,9,9,9,9,10,10,11) histogram(a, xlab="myData") what i wish to do is: 1) invert the order of X and Y (eg: Precent of Total on X-axis and "MyData" on X-axis) 2) plot not the bar of histogram but a

I have a data set with about 6 million rows and 50 columns. It is a mixture of dates, factors, and numerics. What I am trying to accomplish can be seen with the following simplified data, which is given as dput output below. > head(myData) mydate gender mygroup id 1 2012-03-25 F A 1 2 2005-05-23 F B 2 3 2005-09-08 F B 2 4 2005-12-07 F B 2

(Sorry for reposting. Please delete previous msgs. Thanks!) Hi, all Here I created a data frame like mydates<- seq(as.Date("2010-05-29"), length = 43, by = "day") myvalues<-runif(43,0,1) myframe<-data.frame(dates=mydates, day=weekdays(dates), value=myvalues) dates day value 1 2010-05-29 Saturday 0.14576143 2 2010-05-30 Sunday 0.37669604

Hello all, I want to assign relative score to the predictor variables on the basis of its influence on the dependent variable. But I could not find any standard statistical approach appropriate for this purpose. Please suggest the possible approaches. Thanks in advance, Rupendra Chulyadyo Institute of Engineering, Tribhuvan University, Nepal [[alternative HTML version deleted]]

I've been playing around with various table tools, trying to construct a fairly simple cross-tab. It shouldn't be hard, but for some reason it turning out to be (for me). If I want to see how many men and how many women agree with a agree/disagree question (coded 1,0), I can do this: >attach(mydata) >mytable <- table(male, q1.bin) # gender and a binary response variable

Folks, I call the function calcAmorts like so: calcAmorts(prevAm, amort, myDates) Note that I use the package lubridate. The last line where do.call is called to first divide all the rows by the first row and then rbind gives the following error: Error in do.call("rbind", apply(amortsByYears, 1, "/", amortsByYears[, : second argument must be a list By contrast if

Hi all, I am trying to download some tab separated data from the internet. The data is not available directly at the URL that could be known apriori. There is an intermediate form where start and end dates have to be given to get to the required page. For example, I want to download data for a station 03015795. The form for this station is at:

My apologies for asking what is doubtless a dumb question, but I have scant experience in R. It would be very convenient in doing lots of plots to be able to do them in a loop that stepped through a vector of variable names. For example one could say x<-("mydates") y<-c("foo1","foo2","foo3") #where "foon" were vectors

I am trying to put 3 dotcharts side-by-side with minimal space between each. Each chart is for a different variable, but the vertical axes are the same. I want to have vertical axis labels on the lefthand chart but no vertical axis labels on the other two. Plus, I would like very little space between charts 1 & 2 and between charts 2 & 3. I have one approach but am not too happy with

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

When I import a simple dataset, run LDA, and then try to use the model to forecast out of sample data, I get a forecast for the training set not the out of sample set. Others have posted this question, but I do not see the answers to their posts. Here is some sample data: Date Names v1 v2 v3 c1 1/31/2009 Name1 0.714472361 0.902552278 0.783353694 a 1/31/2009 Name2 0.512158919 0.770451596

On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi at gmail.com> wrote: > > Btw, I think "lattice" graphics will provide a better solution than > "ggplot", because it puts appropriate (space saving) markers on the axes > and does axes labels well. However, I cannot figure out how to do it in > "lattice". You will need to convert Income to a