search for: sqlitedf

Dear list, i have installed SQLiteDF (and SQlite 3.5.3 too) After the suggested dataframe generation iris.sdf <- sqlite.data.frame(iris) i have close R and than restart it for verify the correct load of dataframe : the file data1 is saved in the usual folder .SQLiteDF after the command : attachSdf("c:/R/Report/.S...

Hi all, I am working with some large data sets (1-4 GB) and have some questions that I hope someone can help me with: 1. Is there a way to turn off garbage collector from within C interface ? what I am trying to do is suck data from mysql (using my own C functions) and I see that allocating each column (with about 1-4 million items) takes between 0.5 and 1 seconds. My

Good evening to everybody, I have problems to import in R a really big dataset (more than 1000000 values). Which is the best package to install? Is there someone who works with this kind of dataset and can help me, please? Thank you very much, Regards Dr.ssa Erika Frigo Department of Veterinary Sciences and Technology for Food Safety University of Milan Via Grasselli, 7 20137 Milano Tel.

Dear R cracks I am trying to fetch 38 Tables from 38 ESRI Geodatabases through an ODBC connection. I stored the 38 channels in a list and the 38 tablenames in an other list. With a for(i in 1:38) .... sqlFetch(....) I try to read the tables into a third list. But always after a certain amount of rounds (mostly 16) i get Fehler in odbcQuery(channel, query, rows_at_time) : Calloc konnte

How does one tell R to compile code contained in subdirs of the /src directory? I have a few files that I'd like to keep together as one unit. The cheesy way that I can think of is to put slinks in the src directory to the files contained in the subdir, but that's not really the solution I'm looking for. I was hoping to avoid adding a configure.in file to the project. By way of

Hello, I searched the internet but i didn't find the answer for the next problem: I want to do a glm on a csv file consisting of 25 columns and 4 mln rows. Not all the columns are relevant. My problem is to read the data into R. Manipulate the data and then do a glm. I've tried with: dd<-scan("myfile.csv",colClasses=classes) dat<-as.data.frame(dd) My question is: what

Hello Colleagues, I programmed in SAS for 3 years and would like to switch to a not so costly software product. Hence I started to evaluate R, and my first test look promising. However I have some question: 1. Is it possible to query R files by SQL internally on data frames (not on a database) and how is the syntax (I have the RODBC package installed). I would like to extract year, Quarter,

I am a SAS user currently evaluating R as a possible addition or even replacement for SAS. The difficulty I have come across straight away is R's apparent difficulty in handling relatively large data files. Whilst I would not expect it to handle datasets with millions of records, I still really need to be able to work with dataset with 100,000+ records and 100+ variables. Yet, when reading

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Hi all, Using big vectors (more than 4GB) is unfortunately not possible under Windows or other OS's if not enough RAM exists. Could it be possible to implement an a new data type in R, like a vector, but instead holding the information in memory, the data lies on an file. If data is accessed, the data type vector get the information automatically from the file. There is a package out there

Hello folks, I am very excited to have discovered R and have been exploring its capabilities. R's regression models are of great interest to me as my company is in the business of running thousands of linear regressions on large datasets. I am using biglm to run linear regressions on datasets that are as large as several GB's. I have been pleasantly surprised that biglm runs the

Dear R users, I am analysing a very large data set and I need to perform several data manipulations. The dataset is so big that the only way I can play with it without having memory problems (E.g. "cannot allocate vectors of size...") is to write a batch script to: 1. cut the data into pieces 2. save the pieces in seperate .RData files 3. Remove everything from the environment 4. load

Hello, I do some computations on datasets that come from climate models. These data are huge arrays, significantly larger than typically available RAM, so they have to be accessed row-by-row, or rather slice-by slice, depending on the task. I would like to make an R package to easily access such datasets within R. The C++ backend is ready and being used under Windows/.Net/Visual Basic, but I have

I'd like to fit linear models on very large datasets. My data frames are about 2000000 rows x 200 columns of doubles and I am using an 64 bit build of R. I've googled about this extensively and went over the "R Data Import/Export" guide. My primary issue is although my data represented in ascii form is 4Gb in size (therefore much smaller considered in binary), R consumes about

Hi there, I would like some advice, not so much about how to use R, but about software that I need to complement R. I've rooted around in the FAQ's and done a few searches on this mailing list but haven't quite found the perspective I need. I am an experienced data analyst in my field (forest ecology and ecological monitoring) but new to R. I am a long time user of SPSS and have

Tranquilo que no te han hackeado tu "R"... Simplemente que al importar tu CSV, no has indicado que los decimales son las ",". Y ese campo lo importa como un character (un string). Y cuando lo conviertes a numeric, el resultado es un tanto impredecible. Si utilizas read.table para importar, simplemente incluye el parámetro "dec" de esta forma "read.table(..... ,

...oice of interfaces to a DBMS, RODBC and the DBI+ family, > e.g. DBI+RMySQL and DBI+RSQLite. I'm biased, but I find RODBC more > intuitive, and many people have reported it to be faster. If all you want > is non-permanent storage for manipulation of large data sets, consider > also SQLiteDF. > > On Sat, 18 Aug 2007, Duncan Murdoch wrote: > > > Martin Brown wrote: > >> [i sent this message earlier but apparently should have sent it plain > >> text, as follows..] > >> > >> Hi there, > >> > >> I would like some advice,...