similar to: noob requesting help

I have a dataframe imported from csv file below: Houseid,Personid,Tripid,taz 1,1,1,4 1,1,2,7 2,1,1,96 2,1,2,4 2,1,3,2 2,2,1,58 There are three groups identified based on the combination of first and second columns. How do I split this data frame? I tried aa <- split(inpfil, inpfil[,1:2]) but it has problems. Output desired is aa[1] Houseid,Personid,Tripid,taz 1,1,1,4 1,1,2,7 aa[2]

Hello, I have sample data set that looks like: YEAR MONTH DAY CONTINUE SPL TIMEFISH TIMEUNIT AREA COUNTY DEPTH DEPUNIT GEAR TRIPID CONVUNIT 1992 1 26 1 SP0073928 8 H 7 25 4 NA 1000000 02163399054 161 1992 1 26 1 SP0073928 8 H 7 25 4 NA 1000000 02163399054 8 1992 1 26 2 SP0004228 8 H 7 25 4 NA 1000000 02163399054 161 1992 1 26 2 SP0004228 8 H 7 25 4 NA 1000000 02163399054 8 1992

Hello, I have a data set with a grouping variable (TRIPID) and several other variables. TRIPID is repeated in some areas and I would like to use a function like aggregate to sum the variable UNITS according to TRIPID. However I would also like to retain the other variables as they are in the data set with the new summed TRIPID. So what I have is something like this: YEAR MONTH DAY

Hello, I have a data set with a grouping variable (TRIPID) and several other variables. TRIPID is repeated in some areas and I would like to use a function like aggregate to sum the variable UNITS according to TRIPID. However I would also like to retain the other variables as they are in the data set with the new summed TRIPID. So what I have is something like this: YEAR MONTH DAY

G'day R (power) users, I have a many vectors, called: ib1 ib2 ib3 ... ib100 and I would like them in one data frame (df) such that: > df ib1 ib2 ib3 ib4 ..... ib100 x x x x x x x x x x x x x x x I have attempted: hold.list <- list(objects(pattern="ib")) df <- data.frame(hold.list) but that

I want to calculate "expansion factors" for elements in my dataframe based on a 2-d cross classification. Since I'll have "missing values" (many combinations will have no record) I'll need a second "expansion factor" for each "row". I've included my "work to date" below, but I'm not very close to getting this right. My

I have the following sample dataset (CSV input here:http://goo.gl/YR8LP. CSV output here: http://goo.gl/EFCC8) which I want to transform as follows. For each person in a household I want to create two new variables OrigTAZ and DestTAZ. It should take the value in TripendTAZ and put that in DestTAZ. For OrigTAZ it should put value of TripendTAZ from the previous row. For the first trip of every

Dear R users, My data have repeating "beh" parameter : 1 or 2 - type of animal behavior in subsequent locations. I need to assign unique number to each sequence of locations. My data is: >data=data.frame(row=seq(1:10),beh=c(1,1,1,2,2,2,1,1,2,2)) >attach(data) >data row beh 1 1 1 2 2 1 3 3 1 4 4 2 5 5 2 6 6 2 7 7 1 8

Hello everyone, I have a large dataset (x) with some rows that have duplicate variables that I would like to remove. I find which rows are the duplicates with X1<-which(duplicated(x)). That gives me the rows with duplicated variables. Now, how can I remove just those rose from the original data frame. I think I can create a new data frame without the duplicates using subset. I have tried:

HI, You may try this: dat1<- read.table(text=" CustID TripDate Store Bread Butter Milk Eggs 1 2-Jan-12 a 2 0 2 1 1 6-Jan-12 c 0 3 3 0 1 9-Jan-12 a 3 3 0 0 1 31-Mar-13 a 3 0 0 0 2 31-Aug-12 a 0 3 3 0 2 24-Sep-12 a 3 3 0 0 2 25-Sep-12 b 3 0 0 0 ",sep="",header=TRUE,stringsAsFactors=FALSE) dat2<- dat1[,-c(1:3)] res<- lapply(seq_len(ncol(dat2)),function(i)