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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

...r list members, I have got another problem. I imported an SPSS file with the Memisc package using the following commands: mz <- spss.system.file("myspssfile.sav") mz <- subset(mz,select=c( bsex,balt,xurb,dtaet,kartab,bgeb,boseit,bgeblan,xnuts2,kausb,xerwstat, asbper,asbhh,ajahr,aquartal,bstaat,xwieoft,gew1,apkz,bpkzm,bpkzv)) Afterwards I checked the measurements of the variables and they are all right for most of them (e.g. the variable containing the sex of a person is "nominal" and the variable containing the year is "interval"). For two of the variables the...

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.