similar to: Performing a function on columns specified in another dataframe

Hello R listserve, I would appreciate someone's help with this problem. Consider the following toy dataset: x <- read.table(textConnection("worldclim.1 worldclim.2 cru.1 cru.2 indv.1 7 8 32 658 indv.2 7 7 39 422"), header = TRUE) How could I create a subset of the data based on the column prefix? For instance, let's say I wanted to subset only the columns with the

I know that there must be a cool way of doing this, but I can't think of it. Let's say I have an dataframe with NA's. > x <- data.frame(a = c(0,1,2,NA), b = c(0,NA,1,2), c = c(NA, 0, 1, 2)) > x a b c 1 0 0 NA 2 1 NA 0 3 2 1 1 4 NA 2 2 > I know it is easy to replace all the NA's with zeroes. > x[is.na(x)] <- 0 > x a b c 1 0 0 0 2 1 0 0 3 2 1

Hi all, I'm having a problem once again, trying to do something very simple. Consider the following data frame: x <- read.table(textConnection("locus1 locus2 locus3 A T C A T NA T C C A T G"), header = TRUE) closeAllConnections() I am trying to make a new data frame, replacing "A" with "A/A", "T" with "T/T", "G" with

The second beginner question. I want to create a new dataframe, where each element of the original dataframe is translated to 1 if it was "+", to 0 if it was "-" to -1 otherwise. I could do with: Lines <- "a b c d + - + + + + + - + 1 - '+ ' - + + + + N - +" DF <-

Hi all, I have a very simple problem that I cannot seem to find the answer to. Consider the following toy dataset: x <- read.table(textConnection("V1 apples bananas cherries indv.1 7 8 4 3 indv.2 7 7 4 9"), header = TRUE) How would I change the column name of ONLY the first column, not the others? Surely I should not have to re-specify the names of ALL the columns -- e.g.,

Hello again, How do I split a data frame into smaller, completely separate data frames (rather than separate data frames comprising a single "list")? Consider the following data, and my coding attempt: x <- read.table(textConnection("id type number indv.1 bagel 6 indv.2 bagel 1 indv.3 donuts 10 indv.4 donuts 9"), header = TRUE) closeAllConnections() x.split <-

Dear Listserv, Here is my latest in a series of simple-seeming questions that dog me. Consider the following data: x <- read.table(textConnection("temperature probability 0.11 9.4 0 2.3 0.38 8.7 0.43 9.2 0.6 15.6 0.47 8.7 0.09 12.8 0.11 9.4 0.01 7.7 0.83 8 0.65 9.3 0.05 7.4 0.34 10.1 0.02 4.8 0.07 9.1 0.6 15.6 0.01 8.4 0.9 9.6 0.83 8 0.12 8.4 0.01 8 0 5 0.11 9.7 0.41 7.4 0.05 9.4 0.09

Hi, I was hoping someone could help me with the following problem. Consider this toy example. For the input dataset there are four individuals (rows "indv.1" through "indv.4"), measured for two different variables (columns "var.1" and "var.2") at two different levels of a factor (column "factor.level"). I want to calculate a matrix that has the

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)

Dear all, I'm trying to remove some text after the period (a decimal point) in the data frame 'hi', below. This is one step in formatting a table. So I would like e.g. "2.0" to become "2" and "5.3" to be "5.3", where the variable digordered contains the number of digits after the decimal that I would like to display, in the same order in which

Hey all, I feel like the solution to this problem should be relatively simple, but for some reason I can't find answers or come up with my own solution. Given the dataframe: (SpA and SpB not important, want to look at distribution of cooccurance for each year) Year SpA SpB Coocc 2000 0 2000 2 2000 1 2001 8 2001 2 2001 0 2001 0 2002 1 2002 2 How can I apply different functions to

Dear R Users I'm writing my first simulation in R. I've put across my problems with a smaller example in the attachment along with the questions. Please help. Best regards Meenu -------------- next part -------------- mydat<-read.table(textConnection("Level spread change State 4.57 1.6 BlF NA 4.45 2.04 BrS NA 3.07 2.49 BlS NA 3.26 -0.26 BlF NA 2.80 0.22 BrF NA 3.22 2.5 BrS NA

Hi, I turn to you, the R Sages, once again for help. You've never let me down! (1) Please make the following toy files: x <- read.table(textConnection("var.1 var.2 var.3 var.1000 indv.1 1 5 9 7 indv.210000 2 9 3 8"), header = TRUE) y <- read.table(textConnection("var.3 var.1000"), header = TRUE) write.csv(x, file = "x.csv") write.csv(y, file =

Hi, I have a Dataframe. A B C D 0.1 0.7 0.9 0.8 0.20 0.60 0.80 0.70 0.40 0.80 0.70 0.76 I need a resultant dataframe (A-B) (C-D) -0.6 0.1 -0.40 0.1 -0.40 -0.06 Any suggestion would be of a great help Thanks Ramya -- View this message in context: http://r.789695.n4.nabble.com/Finding-a-Diff-within-a-Dataframe-columns-tp3247943p3247943.html Sent from

I read from external data source containing several columns. Each column represents value of a metric. The columns are time series data. I want to sort the resulting dataframe such that the column with the largest mean is the leftmost column, descending in colMean values to the right. I see many solutions for sorting rows based on some column characteristic, but haven't found any

Dear R experts,   I have a dataframe with 4 columns (variables). I want to redorder (or reposition) these columns on the basis of a value in its last row. e.g.   df1<-data.frame( v1= c(2,3,1,9,5), v2=c(8,5,12,4,11), v3=c(7,8,2,6,9), v4=c(1,4,6,3,6))    > df1    v1 v2 v3 v4 1  2  8  7  1 2  3  5  8  4 3  1 12  2  6 4  9  4  6  3 5  5 11  9  6 I wanto to get the order of df1 on the basis of

I need read a table in a string with special format. I used read.csv and textConnection function. But i am confuse about textConnection by follow code. case A: It is OK£¡ str0 <- '{"abc",{"def","X,1&Y,2&Z,3"}}' str1 <- strsplit(str0,'"')[[1]][6] str2 <- gsub("&","\n", str1) con <-

Hi Bill, I put stringsAsFactors = FALSE still did not work. tdat <- read.table(textConnection("A B C Y A12 B03 C04 0.70 A23 B05 C06 0.05 A14 B06 C07 1.20 A25 A23 A12 3.51 A16 A25 A14 2,16"),header = TRUE ,stringsAsFactors = FALSE) tdat$D <- 0 tdat$E <- 0 tdat$D <- (ifelse(tdat$B %in% tdat$A, tdat$A[tdat$B], 0)) tdat$E <- (ifelse(tdat$B %in% tdat$A, tdat$A[tdat$C], 0))

Here's an update of my rawConnection() implementation. In addition to providing a raw version of textConnection(), this fixes two existing issues with textConnection(): one is that the current textConnection() implementation carries around unprotected SEXP pointers, the other is a performance problem due to prolific copying of the output buffer as output is accumulated line by line. This new

Dear List, I am trying to sub-sample some data by taking a data point every x minutes. The data contains missing values, and I would like to take the sub-sample that maximizes the number of valid points in the sample. I.e. minimizes the number of NA's in the data set. For example, given the following: da<-seq(Sys.time(),by=1,length.out=10) x<-c(1,2,NA,4,NA,6,NA,8,9,10)