[R] Advantages of using SQLite for data import in comparison to csv files

[Gabor Grothendieck]

You could look at read.csv.sql in sqldf (http://sqldf.googlecode.com) as well.

On Wed, Jan 13, 2010 at 2:00 PM, Juliet Jacobson <julietjacobson at aim.com> wrote:
> Hello everybody out there using R,
>
> I'm using R for the analysis of biological data and write the results
> down using LaTeX, both on a notebook with linux installed.
> I've already tried two options for the import of my data:
> 1. Import from a SQLite database
> 2. Import from individual csv files edited with sed, awk and sort.
> Both methods actually work very well, since I don't need advanced
> features like multi-user network access to the data.
> My data sets are tables with up to 20 columns and 1000 rows, containing
> mostly numerical values and strings. Moreover,
> I might also have to handle microarray data, but I'm not so sure about
> that yet. Moreover, I need to organise tags for a collection of photos,
> but this data is of course not analysed with R.
> I'm now beginning to work on a larger project and have to decide,
> whether it is better to use SQLite or csv-files for handling my data.
> I fear, it might get difficult to switch between the two system after
> having accumulated the data, adapted software for backups and revision
> control, written makefiles etc.
> Could anyone of you give me a hint on the additional benefits of
> importing data from a SQLite database to R to the simpler way of
> organising the data in csv files? Is it for example possible to select
> values from a column within a certain range from a csv file using awk?
>
> Thanks in advance,
> Juliet Jacobson
>
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