similar to: Loop overwrite and data output problems

Hola A todos. Aún no he podido encontrar la causa de porqué la libraría tibbletime, al transformar la tabla a AS_TBL_TIME ME ARROJA EL SIGUIENTE EL SIGUIENTE MENSAJE Error: assert_that: assertion must return a logical value Si alguien ha tenido ese mismo problema, solicito ayuda al foro. El seguimiento de la transformación es el siguiente; library(tibbletime)

I calculate an anova test in the following way: expdata<-read.table("/home/dorien/UA/meta-music/optimuse/optimuse1-build-desktop/results/results_processedCP", header=TRUE)

Dear R users I am trying to create some new variables for a 4401 x 30 dataframe using ddply and transform. The "id" variable i am using is a factor with 1330 levles eg bb <- function(df) {transform(df, years = study.year - min(study.year) + 1, periods = length(study.year) )} test <- ddply(x,.(id),bb) I havent copied the data to avoid clogging the

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

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

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, 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,

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>

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, From your example data, dat1<- read.table(text=" id1?? id2?? value a????? b?????? 10 c????? d??????? 11 b???? a???????? 10 c????? e???????? 12 ",sep="",header=TRUE,stringsAsFactors=FALSE) #it is easier to get the output you wanted dat1[!duplicated(dat1$value),] #? id1 id2 value #1?? a?? b??? 10 #2?? c?? d??? 11 #4?? c?? e??? 12 But, if you have cases like the one

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

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 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

Consider: > x <- matrix(1:6, 2,3) > rownames(x) <- c("ID1", "ID2") > colnames(x) <- c("Attr1", "Attr2", "Attr3") > x Attr1 Attr2 Attr3 ID1 1 3 5 ID2 2 4 6 > write.csv(x,file="x.csv") "","Attr1","Attr2","Attr3" "ID1",1,3,5

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 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,

Hello, I have a list (mode and class are list) in R that is many elements long and of the form: >length(list) [1] 5778 >list[1:4] $ID1 [1] "num1" $ID2 [1] "num2" "num3" $ID3 [1] "num4" $ID4 [1] NA I'd like to convert the $ID2 value to be in one element rather than in two.?? It shows up as c(\"num2\", \"num3\") if I try to use

Hi, Has anyone been able to figure out how to print all duplicated observations? I have a dataset, with patients ID, and other lab records. Some patients have multiple lab records, but 'duplicated' ID will only show me the duplicates, not the original observation. How can I print both the original one and the duplicates? Thanks