similar to: Merging vector data into one file

Hi, I am trying to sum column information in a list with 3 instances. For example: ID Traversed ID Traversed ID Traversed 1 5 1 7 1 8 2 8 2 11 2 7 3 11 3 22 3 16 What I want to do is sum the

Hi, I read in csv files with the following code: res <- vector(mode="list",length=3) for(i in 1: length(res)) res[[i]]<-read.csv(file=paste("/Users/markaltaweel/Desktop/Output/HydroDataOutput",i,".csv",sep=""),header=T,sep=",") This allows me to load the data into an array of length 3, with the res array containing my data from the csv

Hi, I have a scatter plot, with an equation that best fits the scatter plot expressed as: 1/x^.6. I know for normal linear regression lines you can use the abline() command; however, since my best fit line is not linear, how can I draw my line on the scatter plot in a similar fashion to abline(). Thanks for everyone's help again. I appreciate this board's advice. Mark

Hi, I have data stored in a list that I would like to aggregate and perform some basic stats. However, I would like to apply conditional statements so that not all the data are used. Basically, I want to get a specific variable, do some basic functions (such as a mean), but only get the data in each element's data that match the condition. The code I used is below: >

Hi, I am trying to load csv type data from a folder. However, rather than syntax that simply loads one file at a time I was wondering if there is a method that loads all data from a specific folder. For instance, I have the following data files in a folder nebraskaStats: 10-1-2009_10-7-2009.txt 10-2-2009_10-8-2009.txt 10-3-2009_10-9-2009.txt ....etc. (245 total files in folder) Each file

Dear all, I have several text files looking like this: 9063032 19700201 22:00 174.067 9063032 19700201 23:00 174.076 9063032 19700202 00:00 174.085 9063032 19700202 01:00 174.091 9063032 19700202 02:00 174.094 9063032 19700202 03:00 174.091 9063032 19700202 04:00 174.082 9063032 19700202 05:00 174.079 And I run this loop: for (j in 1:nr.of.files) { #Import: DF <-

Hi All, I am currently doing the following to compute summary statistics of aggregated data: a = aggregate(warpbreaks$breaks, warpbreaks[,-1], mean) b = aggregate(warpbreaks$breaks, warpbreaks[,-1], sum) c = aggregate(warpbreaks$breaks, warpbreaks[,-1], length) ans = cbind(a, b[,3], c[,3]) This seems unnecessarily complex to me so I tried > aggregate(warpbreaks$breaks, warpbreaks[,-1],

Wow.. thanks for the deluge of responses! Aggregate seems like the way to go here. But, suppose that instead of integers in column V2, I actually have dates (and instead of keeping the minimum integer, I want to keep the earliest date): > df =

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

Dear R-Users, I have a big data set "mydata" with repeated observation and some missing values. It looks like the format below: userid sex item score1 score2 1 0 1 1 1 1 0 2 0 1 1 0 3 NA 1 1 0 4 1 0 2 1 1 0 1 2 1 2 NA 1 2 1 3 1

Dear R-users, I've searched for an answer to my question, but so far haven't been able to find a solution. Its likely a simple issue, but have no idea how to do this. A simplified version my (very large) data set looks like this: > > bugs FRUIT SEED_ID SURVIVE 1 1 A 1 2 1 B 1 3 1 C 1 4 1 D 0 5 1 E

Hi, Browse[1]> d4 EVDO_Rev Session_Setup FCA bin counts 50 NA 0 5 1 1 51 NA 0 5 2 1 52 NA 0 5 3 1 53 NA 0 5 4 1 54 NA 0 5 5 1 55 NA 0 5 6 1 56 NA 0 5 7 1 57 NA 0 5 8

I would like to use aggregate() to combine statistics for several days in a data frame. My data frame looks similar to this: date type count value 1 2006-04-01 A 10 99.6 2 2006-04-01 B 4 33.2 3 2006-04-02 A 22 43.2 4 2006-04-02 B 8 44.9 5 2006-04-03 A 12 12.4 6 2006-04-03 B 14 18.5 ('date' is a factor, and my

Dear All, I have a large data set that looks like this: CVX 20070201 9 30 51 73.25 81400 0 CVX 20070201 9 30 51 73.25 100 0 CVX 20070201 9 30 51 73.25 100 0 CVX 20070201 9 30 51 73.25 300 0 First, I would like to import it by merging column 3 4 and 5, since that is the timestamp. Then, I would like to aggregate the data by splitting them in bins of 5 minutes size, therefore from 93000 up to

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

Hi, I have a data frame and want to merge adjacent rows if some condition is met. There's an obvious solution using a loop but it is prohibitively slow because my data frame is large. Is there an efficient canonical solution for that? > head(d) rt dur tid mood roi x 55 5523 200 4 subj 9 5 56 5523 52 4 subj 7 31 57 5523 209 4 subj 4 9 58 5523 188 4 subj 4 7

Hello, I have a data frame with hourly or sub-hourly weather records that span several years, and from that data frame I'm trying to select only the records taken closest to noon for each day. Here's what I've done so far: #Add a column to the data frame showing the difference between noon and the observation time (I converted time to a 0-1 scale so 0.5 represents noon):

try this: scores.melt = data.frame(grade = floor(runif(100, 1,10)), variable = 'score', value = rnorm(100)); cast(scores.melt, grade ~ variable, fun.aggregate = c(mean, length)) it has the nice column names of: grade score_mean score_length 1 1 0.08788535 8 2 2 0.16720313 15 3 3 0.41046299 7 4 4 0.13928356 13 ... but

Suppose I have a small dataframe > aa Target Eaten ID 50 TPP 0 1 51 TPP 1 2 52 TPP 3 3 53 TPP 1 4 54 TPP 2 5 50.1 GPA 9 1 51.1 GPA 11 2 52.1 GPA 8 3 53.1 GPA 8 4 54.1 GPA 10 5 And I want to reshape it into ID TPP GPA 1 1 0 9 2 2 1 11 3 3 3 8 4 4 1 8 5 5 2 10 I realise that

I've got a newbie question and I got a little lost in the "table helps". I've got a data.frame I would like to summarize as a (and pardon for the lack of correct vernacular) data collection matrix. My data looks like, stand siteindex age acres pct.acres 1 232 116 45 8477.3105 0.56159458 2 234 121 25 11120.1530 0.73667441 3 235 132 25