search for: 144mb

I'm having trouble using split on a very large data-set with ~1400 levels of the factor to be split. Unfortunately, I can't reproduce it with the simple self-contained example below. As you can see, splitting the artificial dataframe of size ~13MB results in a split dataframe of ~ 144MB, with an increase memory allocation of ~10 fold for the split object. If split scales linearly, then my actual 52MB dataframe should be easily handled by my 12GB of RAM, but it is not. instead, when I try to split selectSubAct.df on one of its factors with 1473 levels, my memory is slowly gobbled u...

Hi, I am new to R, but a fairly `old' user of Stata. I read posts asking about survey methods and large datasets in the archive, so I will not ask those questions again. But some still remain: - R seems to consume more memory given the same set of data, say if I have only a data frame defined, than Stata. Am I right if I think that this is because the object oriented nature of R and can

Hi, I am new to R, but a fairly `old' user of Stata. I read posts asking about survey methods and large datasets in the archive, so I will not ask those questions again. But some still remain: - R seems to consume more memory given the same set of data, say if I have only a data frame defined, than Stata. Am I right if I think that this is because the object oriented nature of R and can

Hello! Disapointed about SPSS I have to choose another statistic program. And altough I sympathise with the idea of a non-commercial software-project like R and I like the spirit of the R community (and of course I am not keen on paying 150$ to SAS for a one-year students license), I will probably buy SAS, because people I will work with use SAS and I want a close cooperation with them. Besides I