similar to: Very slow using S4 classes

I'm creating an object of a S4 class that has two slots: ListExamples, which is a list, and idx, which is an integer (as the code below). Then, I read a data.frame file with 10000 (ten thousands) of lines and 10 columns, do some pre-processing and, basically, I store each line as an element of a list in the slot ListExamples of the S4 object. However, any kind of assignment operation (<-)

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,

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],

HI Jim and all, I want to put one more condition. Include col2 and col3 if they are not in col1. Here is the data mydat <- read.table(textConnection("Col1 Col2 col3 K2 X1 NA Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) The desired out put would be Col1 Col2 col3 1 X1 0 0 2 K1 0 0 3 Y1 0 0 4 W1 0 0 6 K2 X1

Sorry , I hit the send key accidentally here is my complete message. Thank you Jim and all, I got it. I have one more question on the original question What does this "[-1] " do? preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2

Hi, I would like to split dataframe based on one colum and want to connect the two dataframes by rows (like rbind). Here a small example: # The orgininal dataframe df1 <- data.frame(col1 = c("A","A","B","B"),col2 = c(1:4), col3 = c(1:4)) # The datafame how it could look like df2 <- data.frame(A.col2 = c(1,2), A.col3 = c(1,2), B.col2 = c(3,4), B.col3

Hi, I have the following data frame, where col2 is a startdate and col3 an enddate COL1 COL2 COL3 A 40462 40482 B 40462 40478 The above timeframe of 3 weeks I would like to splits it in weeks like this COL1 COL2 COL3 COL4 A 40462 40468 1 A 40469 40475 1 A 40476 40482 1 B

On 24/02/2018 1:53 PM, William Dunlap via R-help wrote: > x1 = rbind(unique(preval),mydat) > x2 <- x1[is.na(x1)] <- 0 > x2 # gives 0 > > Why introduce the 'x2'? x1[...] <- 0 alters x1 in place and I think that > altered x1 is what you want. > > You asked why x2 was zero. The value of the expression > f(a) <- b > and assignments

Is there any function/way to merge/unite the following data GENEID col1 col2 col3 col4 G234064 1 0 0 0 G234064 1 0 0 0 G234064 1 0 0 0 G234064 0 1

Jim has been exceedingly patient (and may well continue to be so), but this smells like "failure to launch". At what point will you start showing your (failed) attempts at solving your own problems so we can help you work on your specific weaknesses and become self-sufficient? -- Sent from my phone. Please excuse my brevity. On February 25, 2018 7:55:55 AM PST, Val <valkremk at

hi Val, Your problem seems to be that the data are read in as a factor. The simplest way I can think of to get around this is: mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) rbind(preval,mydat)

Hi, Here's my problem... I have a data frame with three columns containing strings. The first columns is a simple character. I want to get the index of that character in the second column and use it to extract the item from the third column. I can do this using a scalar method. But I'm not finding a vector method. An example is below. col1 col2 col3 'L'

Thank you Jim and all, I got it. I have one more question on the original question What does this "[-1] " do? preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE)

Hello, In my script I would like to use a loop, which sorts the dataframe according to different columns, pointed by the string variable. id col1 col2 col3 1 10 0 4 8 2 11 1 2 2 3 12 0 8 3 4 13 0 5 5 Usually the order() function can be used like this: sorted = mytable**[order(column3) , ] which results in properly sorted table: **

Suppose I have the following sort of dataframe, where each column name has a common structure: prefix, followed by a number (for this example, col1, col2, col3 and col4): d = data.frame( col1=runif(10), col2=runif(10), col3=runif(10),col4=runif(10)) What I haven't been able to suss out is how to efficiently 'extract/manipulate/play with' columns from the data frame, making use

Hello * i have to rename a lot of variables, and, given that they have regular name constructs, I would like to use regexps. Here's a dump of my head(names(df)) varnames <- c("id.quest", "txt.1.3", "col1.1.3", "col2.1.3", "col3.1.3", "col4.1.3", "col5.1.3", "txt.2.3", "col1.2.3",

Hi All, I am reading a file as follow, mydat <- read.table(textConnection("Col1 Col2 col3 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE) 1. "NA" are missing should be replace by 0 2. value that are in COl2 and Col3 should be included in col1 before they appear in col2 and col3. So the output data looks like as follow, X1 0 0 Y1 0 0 W1 0 0 Z2 0 0 Z3 X1 0 Z4 Y1

Hi all- I am wondering about using the mapply function to multiple data frames. Specifically, I would like to do a t-test on a subset of multiple data frames. All data frames have the same structure. Here is my code so far: f<-function(x,y) { test<-t.test(x$col1[x$col3=="num",],v$col2[x$col3=="num",],paired=T,alternative="greater") out<-test$p.value

Hi, I'm looking for some lines of code that does the following: I have a dataframe with 160 Columns and a number of rows (max 30): Col1 Col2 Col3 ... Col 159 Col 160 Row 1 0 0 LD ... 0 VD Row 2 HD 0 0 0 MD Row 3 0 HD HD 0 LD Row 4 LD HD HD 0 LD ... ... LastRow HD HD LD 0 MD Now I want a dataframe that looks like this. As you see