Hello, Also, note that to rbind data frames, like the op says, takes less memory than to cbind.
x <- 1:6 list.1 <- list(x,x,x,x,x,x,x,x,x,x,x,x) test.df3 <- as.data.frame(do.call(cbind, list.2)) test.df4 <- as.data.frame(do.call(rbind, list.2)) object.size(list.1) object.size(test.df3) object.size(test.df4) (More columns == more variables == more memory.) Rui Barradas jholtman wrote > > I think you really have to show use your exact code that you did along > with an 'str' of each intermediate data structure since my quick test > does not bear out what you were saying: > >> test.df <- data.frame(a1= 1:6, a2= 1:6, a3 = 1:6, a4 = 1:6, a5 = 1:6, a6 >> = 1:6 > + , a7=1:6, a8 = 1:6, a9 = 1:6, a10 = 1:6, a11 = 1:6, a12 = 1:6) >> test.df > a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 > 1 1 1 1 1 1 1 1 1 1 1 1 1 > 2 2 2 2 2 2 2 2 2 2 2 2 2 > 3 3 3 3 3 3 3 3 3 3 3 3 3 > 4 4 4 4 4 4 4 4 4 4 4 4 4 > 5 5 5 5 5 5 5 5 5 5 5 5 5 > 6 6 6 6 6 6 6 6 6 6 6 6 6 >> object.size(test.df) > 2264 bytes >> x <- 1:6 >> test.df1 <- data.frame(x,x,x,x,x,x,x,x,x,x,x,x) >> object.size(test.df1) > 2264 bytes >> list.1 <- list(x,x,x,x,x,x,x,x,x,x,x,x) >> object.size(list.1) > 1032 bytes >> list.2 <- NULL >> for (i in 1:12) list.2[[i]] <- x >> object.size(list.2) > 1032 bytes >> test.df3 <- as.data.frame(do.call(cbind, list.2)) >> object.size(test.df3) > 2264 bytes >> >> >> > > > On Sat, May 5, 2012 at 5:50 PM, Shivam <shivamsingh@> wrote: >> Hi, >> >> I had a query regarding which object, a list or a dataframe, consumes >> more >> R memory. Let me clarify this: >> >> For example, I have a df of 6 rows and 12 columns, say 'test'. I do >> object.size() and find it uses 3.3 KB of memory. >> >> I run a loop and make a list, say 'testlist', of 6 elements, each element >> being the above mentioned df 'test'. The size of this list is 19.9 KB, >> understandably. >> >> Now I combine this list into a dataframe using rbind. The df formed has >> 12 >> cols and 36 rows. The size of this df is just 5.8 KB, almost a 75% >> reduction in memory. >> >> I had to work with a much larger list, and I thought of using the same >> method to convert my bigger list (62 dataframes, each having 4 cols and >> close to 200,000 rows) into a single dataframe. The big list, sat LIST A, >> had a size of 571 MB. But when I convert it into a dataframe, say DF A, >> using rbind, the object size increases to 1.35 GB. This was in >> contradiction to the earlier result. >> >> What am I missing? Why a 75% reduction in size in one case and double >> size >> in other? Anyone with any explanation? >> >> Sorry for the verbose email, just wanted to make my case clear. >> >> Thanks in advance, >> Regards >> Shivam >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@ mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > > > -- > Jim Holtman > Data Munger Guru > > What is the problem that you are trying to solve? > Tell me what you want to do, not how you want to do it. > > ______________________________________________ > R-help@ mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- View this message in context: http://r.789695.n4.nabble.com/Query-about-memory-used-in-list-and-dataframe-tp4611896p4612876.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
