similar to: all duplicated wanted

On Thu, Jan 31, 2013 at 10:29 AM, Weijia Wang <wwang.nyu@gmail.com> wrote: > Hi, > > > > I have a new question about subsetting in R. > > > > Say we have this data frame: > > > > PT_ID Blood_Pressure OBS_TYPE > > 92 1900 90.0 DBP > > 94 1900 90.0 DBP > > 174 2900 140.0 SBP > > 176 2900

Hi, I have encountered an issue about finding a date closest to another date So this is how the data frame looks like: PT_ID IDX_DT OBS_DATE DAYS_DIFF OBS_VALUE CATEGORY 13 4549 2002-08-21 2002-08-20 -1 183 2 14 4549 2002-08-21 2002-11-14 85 91 1 15 4549 2002-08-21 2003-02-18 181 89 1 16 4549 2002-08-21 2003-05-15

Dear colleagues, I'm trying to have a look at the Assortative and Disassortative ( http://en.wikipedia.org/wiki/Assortative_mixing) of the network I have. But it seems that the igraph hasn't mentioned that yet. I have to get the in/out degree of the vertices of each edge and calculate the Pearson's Correlation coefficient which seems to be quite a huge task for me. :( So I wonder if

Dear r experts, Sorry for this basic question, but I can't seem to find a solution? I have this data frame: df <- data.frame(id = c("id1", "id1", "id1", "id2", "id2", "id2"), A = c(11905, 11907, 11907, 11829, 11829, 11829), v1 = c(NA, 3, NA,1,2,NA), v2 = c(NA,2,NA, 2, NA,NA), v3 = c(NA,1,NA,1,NA,NA), v4 = c("N",

Hi all, Is there anyone who ever used igraph to calculate the index of "centralization" ? I tried my best but can't find it in igraph. The brief introduction to "centralization" can be found here , and I think it's an important index for measuring the centrality on the aggregated level.(http://faculty.ucr.edu/~hanneman/nettext/C10_Centrality.html) Thank you for any

Hi friends, Is there anyone who happened to import data set in the "DL" format into R for further analysis? In the package of "network", there's only a method named "read.paj()". So now, I have to get the dl file from the original data set, and use UCINET to convert it to .net file. It's too complicated. :( In the package of "igraph", edgelist is

Dear all, I'm using igraph for some analysis about the network I have. I have a question about the function "power.law.fit". I wonder if there is any test for checking whether the "power.law.fit" is good for the input, i.e., under which situation, could we use this function to get a reliable result. I'm afraid even I input a random graph without any property of

Hi all, I would like to know the status of profile-guided optimization. What enhancements could be done to the current implementation? The ideas for profile-guided transformations from [0] are still available? Many thanks. Gener [0] http://llvm.org/OpenProjects.html#profileguided -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi R helpers, If I have a dataset looks like: ID record 1 20 . 30 . 25 2 26 . 15 3 21 4..................... And I want it becomes ID record 1 20 1 30 1 25 2 26 2 15 3 21 4..................... That is, I have to duplicate IDs for those with multiple records. I am wondering it is possible to be

Hi fellow R Users, I find that I typically rewrite my data specific to data in columns, which is by no means efficient and I am struggling to break out of this bad habit and utalise some of the excellent things R can do! I have tried to look at 'for' but I don't really follow it, and I wondered if anyone could help with a simple example using my script so I could follow this and build

Hello, Is there a simple and fast function that returns a vector of the number of replications for each object of a vector ? For example : I have a vector of IDs : ids <- c( "ID1", "ID2", "ID2", "ID3", "ID3","ID3", "ID5") I want the function returns the following vector where each term is the number of replicates for the

Dear all, First I''d like to thank authors for so nice Scriptaculous and Prototype libraries, which helped me already a lot! I have question regarding externalControl parameter in InPlaceEditor. If I understand correctly, I can use that to have one image as a trigger to enter edit mode? I tried with below code but without success: <span id="id1">My text</span>

Hi, I've tried to look through all the previous related Threads/posts but can't find a solution to what's probably a simple question. ? I have a data frame comprised of three columns e.g.: ? ID1?ID2?Value a?b?1 b?d?1 c?a?2 c?e?1 d?a?1 e?d?2 ? I'd like to convert the data to a matrix i.e.: ? ?a b c d e a n/a 1 2 1 n/a b 1 n/a n/a 1 n/a? c 2 n/a n/a n/a 1 d 1 1 n/a n/a 2 e n/a n/a 1

Thanks for pointing me out "aggregate", that works fine! There is one complication though: I have mixed types (numerical and character), So the matrix is of the form: A 1.0 200 ID1 A 3.0 800 ID1 A 2.0 200 ID1 B 0.5 20 ID2 B 0.9 50 ID2 C 5.0 70 ID1 One letter always has the same ID but one ID can be shared by many letters (like ID1) I just want to keep track of the ID, and get

Hi Together, I have a problem with the plyr package - more precisely with the ddply function - and would be very grateful for any help. I hope the example here is precise enough for someone to identify the problem. Basically, in this step I want to identify observations that are identical in terms of certain identifiers (ID1, ID2, ID3) and just want to save those observations (in this step,

Dear R users, I have a big text file formatted like this: x x_string y y_string id1 id1_string id2 id2_string z z_string w w_string stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string1 y y_string1 z z_string1 w w_string1 stuff stuff stuff stuff stuff stuff stuff stuff stuff // x x_string2 y y_string2 id1

Hi, I have tried search around this forum for the best way to access a data.frame.. i got the feeling that "no partial match" is the way to make it fast.... so I convert everything to factor.. but I'm still not 100% sure if the following code will do it... is this the fastest way to do something foreach (ID, ID2) pair? Thanks! data <- data.frame(ID = floor(runif(n = 40000, min=0,

Colleagues, I am trying to de-duplicate a large (long) database (approx 1mil records) of diagnostic tests. Individuals in the database can have up-to 25 observations, but most will have only one. IDs for de-duplication (names, sex, lab number...) are patchy. In a first step, I am using Andreas Borg's excellent record linkage package (), that leaves me with a list of 'pairs' looking

Hi - I have a data frame with a large number of observations (62,000 rows, but only 2 columns - a character ID and a result list). Sample: > my.df <- data.frame(id=c("ID1", "ID2", "ID3"), result=1:3) > my.df id result 1 ID1 1 2 ID2 2 3 ID3 3 I have a list of ID vectors. This list will have anywhere from 100 to 1000 members, and

Hi, I have a correlation matrix of about 3000 items, i.e., a 3000*3000 matrix. For each of the 3000 items, I want to get the top 50 items that have the highest correlation with it (excluding itself) and generate a data frame with 3 columns like ("ID", "ID2", "cor"), where ID is those 3000 items each repeat 50 times, and ID2 is the top 50 correlated items with ID,