similar to: Help with data.frame subsets

Dear all, First, let's create some data to play around: set.seed(1) (df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10), Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),]) ## Now we need the empirical distribution function: edf <- function(x) ecdf(x)(x) # empirical distribution function evaluated at x ##

Hi folks, I created a subset of a dataframe (i.e., selected only men): subdata <- subset(data,data$gender==1) After a residual diagnostic of a regression analysis, I detected three outliers: linmod <- lm(y ~ x, data=subdata) plot(linmod) Say, the cases 11,22, and 33 were outliers. Here comes the problem: When I want to exclude these three cases in a further regression analysis, - for

Dear R-users, I have written the following code to generate some trellis plots. It works perfectly fine except that it is quite slow when it is apply to my typical datasets (over several thousands of lines). I believe the problem comes from the loops I am using to subset my data.frame. I read in the archives that the tapply function is often more efficient than a loop in R. Unfortunately ,

OS X R 4.3.3 Colleagues I have created objects using the Surv function in the survival package: > FIT.1 Call: survfit(formula = FORMULA1) n events median 0.95LCL 0.95UCL SUBDATA$ARM=1, SUBDATA[, EXP.STRAT]=0 18 13 345 156 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=1 13 5 NA 186 NA SUBDATA$ARM=2, SUBDATA[, EXP.STRAT]=2 5

Hi Dennis, look at the help page for summary.survfit, the Value n.event. G?ran On 2024-05-15 22:41, Dennis Fisher wrote: > OS X > R 4.3.3 > > Colleagues > > I have created objects using the Surv function in the survival package: >> FIT.1 > Call: survfit(formula = FORMULA1) > > n events median 0.95LCL 0.95UCL >

Dear list, this must be an easy one: I have a data.frame of two columns, "ID" with four different levels (A to D) and numerical "size", and each of the 4 different IDs is repeated a different number of times. I would like to get the mean size for each ID as another data.frame. I have tried the following: >ID= as.character(unique(data[,1])) # I use unique() because

Hi, I am trying to create a googleVis motion chart with monthly data. When formatting the date column as a Date class variable, the plot as presented in the browser becomes considerably slower and very prone to crashing the browser. To illustrate this issue I have modified the WorldBank demo. ### objects from demo("WorldBank", package = "googleVis") M <-

http://www.nabble.com/file/p18018170/subdata.csv subdata.csv I've attached 100 rows of a data frame I am working with. I have one factor, id, with 27 levels. There are two columns of reference data, x and y (UTM coordinates), one column "date" in POSIXct format, and one column "diff" in times format (chron package). What I am trying to do is as follows: For each day

Dear R Users, I recently posted an email on this list about the use of data.frame and overlaying multiple plots. Deepayan kindly indicated to me the panel.superposition command which worked perfectly in the context of the example I gave. I'd like to go a little bit further on this topic using a more complex dataset structure (actually the one I want to work on). >mydata Plot

Hello I have a dataframe that looks like this MSA CITY HIVEST YEAR YR CAT 1 0200 Albuquerque 0.50 1996 1996 5 2 0520 Atlanta 13.00 1997 1997 5 3 0720 Baltimore 29.10 1994 1994 1 4 0720 Baltimore 13.00 1995 1995 5 5 0720 Baltimore 3.68

Dear R experts, I got help to build a loop but there is a bug inside it that causes one part of the mechanism to fail. It should grow once, but if keep growing on rows where $ti_all is not NA. Here is a wall of code that very crudely demonstrates the problem, there is a couple of dim() outputs at the end where you can see how it the second time around keeps adds (2) rows, but this does not

Hi R users, I really need help with subsetting data frames: I have a large database of medical records and I want to be able to match patterns from a list of search terms . I've used this simplified data frame in a previous example: db <- structure(list(ind = c("ind1", "ind2", "ind3", "ind4"), test1 = c(1, 2, 1.3, 3), test2 = c(56L, 27L, 58L,

I have a large dataset similar to this: ID time result A 1 5 A 2 2 A 3 1 A 4 1 A 5 1 A 6 2 A 7 3 A 8 4 B 1 3 B 2 2 B 3 4 B 4 6 B 5 8 I need to extract a number of features for each individual in it (identified by "ID"). These are: * The lowest result (the nadir) * The time of the nadir - but if the nadir level is present at >1 time point, I need the minimum and maximum time of nadir

Hello, I've encountered a very weird issue with the method subset(), or maybe this is something I don't know about said method that when you're subsetting based on the columns of a data frame you can only use constants (0.1, 2.3, 2.2) instead of variables? Here's a look at my data frame called 'ea.cad.pwr': *>ea.ca.pwr[1:5,] MAF OR POWER 1 0.02 0.01 0.9999 2 0.02

Hello R users, I'm wondering whether it is possible to manage big data set in R? I have a data set with 3 million rows and 3 columns (X,Y,Z), where X is the group id. For each X, I need to run 2 regression on the submatrix. I used the function "split": datamatrix<-read.csv("datas.csv", header=F, sep=",") dim(datamatrix) # [1] 2980523 3

Hi all, I realise that the convention is to provide a working example of my problem but the data are of a sensitive nature so I'm not able to do that in this case. I need to query a database for multiple search terms: db <- structure(list(ind = c("ind1", "ind2", "ind3", "ind4"), test1 = c(1, 2, 1.3, 3), test2 = c(56L, 27L, 58L, 2L), test3 =

Hi, I have a very simple problem but I can't think how to solve it without using a for loop and creating a large logical vector. However given the nature of the problem I am sure there is a "1-liner" that could do the same thing much more efficiently. bascially I have a dataframe with characters in, eg >names.and.numbers (index) Name Fave.Number 1 John 7 2

Hi, I generally do my data preparation externally to R, so I this is a bit unfamiliar to me, but a colleague has asked me how to do certain data manipulations within R. Anyway, basically I can get his large file into a dataframe. One of the columns is a management group code (mg). There may be varying numbers of observations per management group, and he would like to subset the dataframe such

Help! I am a new R user. It has been slow getting up to speed, but definitely rewarding. I have come up against a problem I can't handle. I would very much appreciate any help. I am writing a vector auto regression (VAR) function that utilizes existing R statistical functions. I would like to use the step function to do step-wise elimination on each univariate time series model. No

https://bugs.freedesktop.org/show_bug.cgi?id=99354 Bug ID: 99354 Summary: [G71] "Assertion `bkref' failed" reproducible with glmark2 Product: Mesa Version: 13.0 Hardware: x86 (IA32) OS: Linux (All) Status: NEW Severity: normal Priority: medium