similar to: Naming an object after another object...can it be done?

Hi, I need to aggregate rows of a data.frame by computing the mean for rows with the same factor-level on one factor-variable; here is the sample code: x <- data.frame(rep(letters,2), rnorm(52), rnorm(52), rnorm(52)) aggregate(x, list(x[,1]), mean) Now my problem is, that the actual data-set is much bigger (120 rows and approximately 100.000 columns) ? and it takes very very long

Hello All, I am trying to write a function which would operate on columns of a dataframe specified in parameters passed to that function. f = function(dataf, col1 = "column1", col2 = "column2") { dataf$col1 = dataf$col2 # just as an example } The above, of course, does not work as intended. In some languages one can force evaluation of a variable, and then

Hi, In a function, I compute 10 (un-named) vectors of reasonable length (4471 in the particular example I have to hand) that I want to combine into a data frame object, that the function will return. This is very slow, so *I'm* doing something wrong if I want it to be quick and efficient, though I'm not sure what the best way to do this would be. I know it is the combining into data

Hello list I have been given some Excel sheets with data laid like this: Col1 Col2 A 3 2 3 B 4 5 4 C 1 4 3 I was hoping to import this into R as a csv and then get the mean and SD for each letter in column 1. Could someone give me some guidance on best to approach this? Thanks Iain

Dear R Community, The following seems like a simple problem, but I''ve been stuck on it for some time, with no luck using matching or subsetting functions. I''m trying to remove the rows from a large matrix that match rows in another large matrix. A (small scale) example: col1<-c("A", "B", "C", "D") col2<-c("A",

I think the rule is that you can do anything as long as you don't complain. If you want to complain, you must follow the instructions. -- Jari Oksanen in Re: [Rd] Keeping up to date with R-devel -- Patrick Burns pburns at pburns.seanet.com twitter: @burnsstat @portfolioprobe http://www.portfolioprobe.com/blog http://www.burns-stat.com (home of: 'Impatient R' 'The R

Hi R-experts, I try to find a way to transfer a matrix to a data.frame that is used as input of aov. can you give me advice for that? >mdat <- matrix(c(1,2,3, 11,12,13), nrow = 2, ncol=3, byrow=TRUE, dimnames = list(c("row1", "row2"), c("Col1", "Col2", "Col3"))) >mdat      Col1 Col2 Col3 row1    1    2    3 row2   11   12   13 ===>

R 2.15.1 OS X Colleagues, I am reading a 1 GB file into R using read.table. The file consists of 100 tables, each of which is headed by two lines of characters. The first of these lines is: TABLE NO. 1 The second is a list of column headers. For example: TABLE NO. 1 COL1 COL2 COL3 COL4 COL5 COL6 COL7 COL8 COL9 COL10

R-help is all about solving R problems. So here ya go: http://www.portfolioprobe.com/2011/09/12/solve-your-r-problems/ -- Patrick Burns pburns at pburns.seanet.com twitter: @portfolioprobe http://www.portfolioprobe.com/blog http://www.burns-stat.com (home of 'Some hints for the R beginner' and 'The R Inferno')

Dear All How can I transform 1 column to 2 columns in R? 211217_s_at GO:0005249 211217_s_at GO:0005251 211217_s_at GO:0005515 211217_s_at GO:0015271 211217_s_at GO:0030955 211217_s_at GO:0005249 211217_s_at GO:0005251 211217_s_at GO:0005515 211217_s_at GO:0015271 211217_s_at GO:0030955 Best Wishes, Soheila [[alternative HTML version deleted]]

Hi Would anyone have any pointers on how to slice up a large zoo table. I have the following structure: - > str(ZOO_OBJ) ?zoo [1:632, 1:83] 30.4 30.4 30.4 30.4 30.3 ... ?- attr(*, "dimnames")=List of 2 ??..$ : NULL ??..$ : chr [1:83] "COL1" "COL2" "COL3" "COL4" ... ?- attr(*, "index")= POSIXct[1:632], format: "2009-05-01

Dear all, I have a dataframe which looks like this (dummy): date<-c("jan", "feb", "mar", "apr", "may", "june", "july", "aug","sep","oct","nov","dec") col1<-c(8.2,5.4,4.3,4.1,3.1,2.5,1.1,4.5,3.2,1.9,7.8,6.5) col2<-c(3.1,2.3,4.7,6.9,7.5,1.1,3.6,8.5,7.5,2.5,4.1,2.3)

Anyone got any hints on how to make this code more efficient? An early version (which to be fair did more than this one is) ran for 330 hours and produced no output. I have a two column table, Dat, with 12,000,000 rows and I want to produce a lookup table, ltable, in a 1 dimensional matrix with one copy of each of the values in Dat: for (i in 1:nrow(Dat)) { for (j in 1:2) { #If next

Hi all, It seems like I cannot use normal 'if' for data frames. What would be the best way to do the following. if data$col1='high' data$col2='H' else if data$col1='Neutral' data$col2='N' else if data$col='low' data$col2='L' else #chuch a warning? Note that col2 was not an existing column and was newly assigned for this

Hi all, I put up an exhaustive model to use R's "step" function: ------------------------ mygam=gam(col1 ~ 1 + col2 + col3 + col4 + col2 ^ 2 + col3 ^ 2 + col4 ^ 2 + col2 ^ 3 + col3 ^ 3 + col4 ^ 3 + s(col2, 1) + s(col3, 1) + s(col4, 1) + s(col2, 2) + s(col3, 2) + s(col4, 2) + s(col2, 3) + s(col3, 3) + s(col4, 3) + s(col2, 4) + s(col3, 4) + s(col4, 4) + s(col2, 5) + s(col3,

Dear R fellows, I created a new column Date_flag to compare the dates of COL1 and COL2 using the code below. But it showed that 5/1/15 is greater than 6/1/2014 and 5/1/2015 greater than 7/1/2014 despite the year is greater. How do I fix that? I did try to format as %y/%m/%d but it does not fix that. data$Date_Flag <- ifelse(data$COL2 > data$COL1, 0,1) COL1 COL2 6/1/14

Hi, I want to calculate the Value at Risk with using some distirbutions and a volatility model. I use the following data(http://uploadeasy.net/upload/cdm3n.rar) which are losses (negative returns) of a company of approx. the last 10 years. So I want to calculated the Value at Risk, this is nothing else than the quantile. Since I have losses I consider the right tail of the distribution. Consider

Hi, The read.csv.ffdf function in package ff will create the ff object physical file in the default directories, I am trying to let the files created in the paths users specify, I think the point is to make use of the asffdf_args parameter, I have a test CSV file named D:\rtemp\fftest.csv, the content of the file is as following: col1,col2,col3 1,"amber",2.4 2,"linda",4.5

Thank you Jim, I read the data as you suggested but I could not find K1 in col1. rbind(preval,mydat) Col1 Col2 col3 1 <NA> <NA> <NA> 2 X1 <NA> <NA> 3 Y1 <NA> <NA> 4 K2 <NA> <NA> 5 W1 <NA> <NA> 6 Z1 K1 K2 7 Z2 <NA> <NA> 8 Z3 X1 <NA> 9 Z4 Y1 W1 On Sat, Feb 24, 2018 at 6:18 PM, Jim

Hi Val, My fault - I assumed that the NA would be first in the result produced by "unique": mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) val23<-unique(unlist(mydat[,c("Col2","col3")])) napos<-which(is.na(val23)) preval<-data.frame(Col1=val23[-napos],