similar to: Deleting rows based on duplicate entries in one columns in a data matrix

Hello everybody, I have usually solved this problem by repeating lines of codes instead of a loop, but it's such a waste of time, I thought I should really learn how to do it with loops: What I want to do: Say, I have several data files that differ only in a number, e.g. data points (or vector, or matrix...) Data_1, Data_2, Data_3,... and I want to manipulate them e.g. a simple sum of

Hello, I use read.xls from the gdata package to read in xlsx files. Sometimes these data.frames contain NA columns and rows only. I know how to get rid of those ones but here is the R output of a test data set read in with read.xls > t1 A B X D X.1 X.2 1 test 1 NA NA 2 <NA> asd NA

Could somebody advise me about importing a txt file as a frame? I am using the command: test <- read.delim ("~/docs/perl/expr_ctx.txt2", header=T, sep = "\t", row.names = 1) This gives me an error because there are duplicate rows. In the txt file, the columns are unique subjects and the rows are variables, so I had planned to transform the file after importing. The first

Hello everyone, when I run the "unique" command on my data frame, it deletes the majority of duplicate rows, but not all of them. Here is a sample of my data. How do I get it to delete all the rows? 6 -115.38 32.894 195 162.94 D 8419 D 7 -115.432 32.864 115 208.91 D 8419 D 8 -115.447 32.773 1170 264.57 D 8419 D 9 -115.447 32.773 1170 264.57 D 8419 D 10 -115.447 32.773 1170

Hello, I am relatively new to R, and I've run into a problem formatting my data for input into the package RankAggreg. I have a matrix of gene titles and P-values (weights) in two columns: KCTD12 4.06904E-22 UNC93A 9.91852E-22 CDKN3 1.24695E-21 CLEC2B 4.71759E-21 DAB2 1.12062E-20 HSPB1 1.23125E-20 ... The data contains many, many duplicate gene titles, and I need to remove all but one of

Sorry to bother the group but I am wondering if there are some official ways to delete a row/column, i.e., some functions of dataTable manipulation? For rows operation I use subset() but what about columns? Any advice is welcome and I will be more than grateful if somebody could make a summary on this issue. Xiaofan --------------------------------------------------------- Xiaofan Li

hi all hopefully some one can help. assume that i imported the following data into R (say the data frame is called a) x1 x2 x3 1 NA 3 1 2 NA 1 2 3 3 NA 6 4 5 9 7 5 6 7 8 9 NA 7 9 How can i construct a new data frame that only contains those rows that does not contain the NA's? is these a quick way? ie x1 x2 x3 1 2 3 4 5 9 7 5 6 7 8 9 in this example we can simple use

Hello List, I would like to simplify a data.frame like this columnA columnB user10 proj12 user10 proj19 user10 proj12 into something like: columnA columnB columnC user10 proj12 2 user10 proj19 1 I know unique() can simplify the data.frame, but how to count and store the duplicates? thanks in advance for any help. best regards, Simone

Hello, I have a dataset which consists of 9 columns (variables) and 35 rows (observations). I am doing a simple linear regression of one variable on the other. There are some observations that are outliers and I would like to remove them based on another variable (it's a unique, numeric variable). How do you tell R to remove multiple rows (observations) based on a variable value?

Dear List, I have a data matrix that consists of ~4500 rows and 25 columns (i.e. an exprSet object that I converted via the 'exprs' function into a data matrix) Now I want to remove/delete the rows where all exp. values in that particular row are below or equal to a specific cut-off value (e.g 1.11) I have tried using several commands to address this issue: >Matrix[rowSums(Matrix

Hi all, I'm relatively new to R and have a data management problem. I am importing a data matrix with some columns that have missing values. I am trying to figure out how to delete rows with NA for data FOR JUST ONE SPECIFIED column. For instance, with the example matrix: x<-matrix(nrow=5,ncol=3) x[,]<-1 x[5,1]<-NA x[3,3]<-NA how do I tell R to delete any rows with an NA value

n <- 10 P1 <- runif(n) P2 <- runif(n) P3 <- P1 + P2 + runif(n)/100 P4 <- P1 + P2 + P3 + runif(n)/100 mydata <- data.frame(cbind(P1,P2,P3,P4)) mydata[1,1] <- 8 mydata[3,1] <- -5 mydata[2,3] <- -6 mydata[7,3] <- 7 f=function(z){quantile(z, c(0.01, 0.99)) } temp1 <- lapply(mydata, f) temp1 $P1 1% 99% -4.542391 7.354209 $P2 1% 99%

Hi, I'm working with a big square matrix (15k x 15k) and I have some trouble. I want to delete selecting rows and columns. I'm using something like this: > sel_r=c(15,34,384,985,4302,6213) > sel_c=c(3,151,324,3384,7985,14302) > matrix=matrix[-sel_r,-sel_c] but it works very slow. Does anybody know how to make it in faster way? Thank's -- View this message in context:

Hello, I have a dataset (named "x") with many (966) columns. What I would like to do is delete any columns that do not have at least 375 non-blank observations (i.e., the cells have some value in them besides NA). How can I do this? I have come up with the following code to _count_ the non-blank observations in each column, but how would I adapt this code to _delete_ columns from the

Hi, folks, Finally Friday~~ Here comes the question: x=c('germany','poor italy','usa','england','poor italy','japan') y=c('Spain','germany','usa','brazil','england','chile') s=1:6 z=3:8 test=data.frame(x,y,s,z) #Now I only concern the countries ('germany','england','brazil').

as a r noob i am having another problem: i have a big dataframe where each row corresponds to one entry and each column is a field... for instance, i have the column ID and time and many more... Id like to get a dataframe where all IDs are just included once (some users with that ID might have several entries but Id like to kepp only one).. when i use unique I only get a list of the levels (or

Hi, I need to filter my data: I think its easy but i'm stuck so i'll appreciate some help: I have a data frame with 14 variables and 6 million rows. About half of this rows have a value of "0" in 12 variables (the other two variables always have values). How can I delete the rows in which all 12 variables have the value of "0". example (from my data, variable 14 is

Hi, dat1<- read.table(text=" Restaurant owner purchase_date ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Chuck 3/4/2011 ??????????? 23 Bob??????? 1/1/2013 ??????????? 23 Bob??????? 1/1/2013 ??????????? 23 Bob???????? 1/1/2013 ??????????? 15 Hazel 4/11/2010 ??????????? 15 Hazel 4/11/2010 ??????????? 15 Hazel 4/11/2010 ???????????

Hello. I have just started learning how to work with R program but I have encountered a problem. I can't think up how to remove the rows which contain two (2) or more NA or Zero (0). I would be glad if you could help me because I just have some basic knowledge so far and I even haven't mastered all the basics yet as well. Thanks in advance. -- View this message in context:

#Hello, # I have a question about the addition of values in specific columns and rows of a Data frame. # Below I have created two data frames, X.df and "Y.df". ## creation of X.df data frame X<- matrix(0,16,3) X.df<-data.frame(X) X.df[,1] <- c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4) X.df[,2] <- c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4) names(X.df)[1]<-"L(A)a(i)"