similar to: Trying to "expand" some data - Newbie needs help

I'm having a problem reading data to set control totals for a dataframe. I want to adjust a dataframe based on a 2-d table of values, which I get by using : > CurrentX1Sums <- as.matrix(xtabs(~tripid_nu+lineon, data=SurveyData)) > CurrentX2Sums <- apply(CurrentX1Sums, 1, sum) I've created a .csv file with new (target) sums that looks like this: tripid_nu Warner

I want to import some "target values" to normalize elements of a dataframe. I'm summarizing the existing totals using as.matrix(xtabs(~tripid_nu+lineon, data=SurveyData)) and reading a .csv table of target values. I can't even get them to list out as similar data items. My idea is to do something like this, but I don't know how to do it in R

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

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 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

I have a dataframe with many hundreds of survey records containing: tripid_nu, lineon, MuchOtherData, X1, X2, X3, X4 tripid_nu = identifier for each "Trip" {E.g. for EB MTA-901 leaving the first stop at 07:24} lineon = identifier for each of the stop locations Where X1 is the ratio (for each trip/stop combination) of some target number to the number of records.

I'm fairly new to R and still learning how to use it. I could really use some help with the following problem. I have a huge .csv file containing thousands of measurements on 34 different birds. Measurements include longitude, latitude, altitude, speed, time, etc. All birds have a different number (ranging from 121 to 542). All measurements have a tripID (1 for the first trip of every bird, 2

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

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:

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

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)

I'm trying to learn how to calibrate/postStratify/rake survey data in preparation for a large survey effort we're about to embark upon. As a working example, I have results from a small survey of ~650 respondents, ~90 response fields each. I'm trying to learn how to (properly?) apply the aforementioned functions. My data are from a bus on board survey. The expansion in the