search for: quartering

Hi, I am trying to reproduce some functionalities of Excel pivot table in R, sadly, I couldn't figure out how to do it. I am wondering if this is even possible in R. Does anyone know? Here is an example: year=rep(2003,16) quarter=rep(1:4,each=4) sales=1:16 company=rep(c("a","b","c","d"),4) df=data.frame(year,quarter,sales,company) #this is the

Dear Gavin, This is really great, thank you! I created some long loops to get rid of extra months at the beginning and the end of my data but your code is great for putting it then together quarterly. thanks again, Denise On Mon, 2008-08-18 at 14:31 +0100, Denise Xifara wrote: > Thank you very much Stephen, but how will aggregate deal with months that > fall outside annual quarters? eg,

Hi-- I have three columns in an input file: MONTH QUARTER YEAR 2012-07 2012-3 2012 2001-07 2001-3 2001 2002-01 2002-1 2002 I want to make output like so: MONTH QUARTER YEAR 07 3 2012 07 3 2001 01 1 2002 I was having some trouble getting the regular expression to work. I think it should

Dataframe cust has Date-type column open.date. I wish to set up another column, with (first day of) the quarter of open.date. To be comprehensive (of course, improvement suggestions are welcome), month = function(date) { return(as.numeric(format(date,"%m"))) } first.day.of.month = function(date) { return(date + 1 - as.numeric(format(date,"%d"))) } first.day.of.quarter =

Folks, I want to make the following function more efficient, by vectorizing it: getCriterionDecisionDate <- function (quarter , year) { if (length(quarter) != length(year)) stop ("Quarter and year vectors of unequal length!"); ret <- character(0); for (i in 1:length(quarter)) { currQuarter <- quarter[i]; currYear <- year[i]; if ((currQuarter < 1) |

I have two data frames. One (arr) has all arrivals to an airport for a year, and the other (gw) has the dates and quarter hour of the day when the weather is good. arr has a Date and quarter hour column. >names(arr) [1] "Date" "weekday" "hour" "month" "minute" [6] "quarter" "ICAO"

I have financial data on a a set of firms, with a quarterly period (fundamental data). The data spans 10 years, and four quarters per year. The present file (.csv) reads the Date columns as "200706" for the second quarter of 2007; "199809" for the third quarter of 1997. Is there a way I can convert it to something like "2007 Q2", "1998 Q3"? I am aware of

I successfully combined my data frames, and am now on my next hurdle. I had combined the data and quarter, and used tapply to count the entries for each unique date/quarter pair. ar= tapply(ewrgnd$gw, list(ewrgnd$dq), sum) #for each date/quarter combination sums the gw (which are all 1) dq=row.names(ar) spl=strsplit(dq) But I need to split them back into the separate date and quarter. So I used

Dear List, I have a data frame of data taken every few seconds. I would like to subset the data to retain only the data taken on the quarter hour, and as close to the quarter hour as possible. So far I have figured out how to subset the data to the quarter hour, but not how to keep only the minimum time for each quarter hour. For example:

I have the initial matrice: > *data.frame(Subject=rep(100:101, each=4), Quarter=rep(paste("Q",1:4, sep=""),2), Boolean = rep(c("Y","N"),4))* Subject Quarter Boolean 1 100 Q1 Y 2 100 Q2 N 3 100 Q3 Y 4 100 Q4 N 5 101 Q1 Y 6 101 Q2 N 7 101 Q3 Y 8 101

Hi, This is probably really simple, but I am clearly not R-minded, I have read the help files, and reread them, and I still can't work out what to do... I have a data frame (d) with 3 columns (age (0-5), quarter (1-4) and x). I want to estimate the precision of my mean x by age and quarter, so I want to carry out a bootstrap for each group. I am trying to do this within a loop, so I don't

Hello R-Community, I have the following matching problem: I have two data.frames, one with an observation every month (per company ID), and one with an observation every quarter (per company ID; note that quarter means fiscal quarter; therefore 1Q = Jan, Feb, Mar is not necessarily correct and also, a fiscal quarter is not necessarily 3 month long). For every month and company, I want to get the

Hi everyone! I have a question about data processing efficiency. My data are as follows: I have a data set on quarterly institutional ownership of equities; some of them have had recent IPOs, some have not (I have a binary flag set). The total dataset size is 700k+ rows. My goal is this: For every quarter since issue for each IPO, I need to find a "matched" firm in the same

Hello, I have two date strings, say "1972-06-30" and "2012-01-31", and I'd like to get every quarter period end date between those dates? Does anyone know how to do this? Speed is important... Here is a small sample: Two dates: "2007-01-31" "2012-01-31" And I'd like to get this: [1] "2007-03-31" "2007-06-30"

Hello, I am trying to carry out a bootstrap analysis (using the boot package) on a table and cannot work out how to get the results I need! I have a table ("d2") with 4 columns: "ID_code", "Age", "Quarter" and "StomWt". Age (0-5) and Quarter (1-4) are my strata Therefore I wish to estimate the confidence intervals for the mean StomWt for each Age

Dear R users, I have a dataframe where column is has countries, column 2 is dates (monthly) for each countrly, the next 10 columns are my factors where I have measurements for each country and for each date. I have attached a sample of the data in csv format with the data for 3 countries. I would like to convert my monthly data into quarterly data, finding the mean over 3 month periods for

hii all i need some suggestion about implementing samba 4 in multisite environment im still new in samba 4, i have finish install my first samba 4 DC in my centos 6 machine without any problem. i have plan to implement samba 4 in distribute / multisite environment, i have one head quarter office and aroung 20 site office, in my head quarter office i have not more than 50 PC client and in every

I have a zooreg object and I want to be able to generate a value for seasons and 11-day composites paste it onto my zoo data frame, along with year, month and days. Right now I have the following to work from: eg. dat.zoo.mdy <- with(month.day.year(time(dat.zoo)), cbind(dat.zoo, year, month, day, quarter = (month - 1) %/% 3 + 1, dow = as.numeric(format(time(dat.zoo), "%w")))) For

I have the initial matrice: > *data.frame(Subject=rep(100:101, each=4), Quarter=rep(paste("Q",1:4, sep=""),2), Boolean = rep(c("Y","N"),4))* Subject Quarter Boolean 1 100 Q1 Y 2 100 Q2 N 3 100 Q3 Y 4 100 Q4 N 5 101 Q1 Y 6 101 Q2 N 7 101 Q3 Y 8 101

Hi WizaRds, I'd like to overplot UK fuel consumption per quarter over the course of five years. Sounds simple enough? Unless I'm missing something, the following seems very involved for what I'm trying to do. Any suggestions on simplifications? The way I did it is awkward mainly because of the first call to plot ... but isn't this necessary, especially to set limits for the