Well, I don't know RPy nor Python enought, and maybe I misunderstand your
data structure, but did you tried the RPy corresponding to the R
function"as.data.frame(dl)"
Cheers
2008/12/13 Gary Strangman <str...@nmr.mgh.harvard.edu>
>
> Hi again,
>
> I have a list-of-lists that I want to convert to an R dataframe. (In R, it
> should end up as 306 rows by 12 columns.) The rpy2 instructions suggested
> in this forum were basically: (1) convert my list of lists to a list of
> array.array()s, (2) convert each array.array() to an RVector, (3) convert
> the list of RVectors to a TaggedList, and (4) convert the taggedlist to a
> RDataFrame. While a touch unwieldy, that all works fine ... in most cases.
>
> However, I have some datasets with string columns in my source data
> (categorical data). These cannot be converted by array.array(), as it
> doesn't accept strings. TaggedList appears to work fine (as shown below)
> if I skip step 1 above and create RVectors straight from lists. But when I
> convert a TaggedList created a list of RVectors created this way, I get
> one LONG dataframe (1 row by 12*306=3672 columns):
>
> [in what follows, dl is my data, a list of lists]
>
> >>> import rpy2.robjects as ro
> >>> import rpy2.rlike.container as rlc
> >>> thisd = map(ro.RVector,dl)
> >>> len(thisd)
> 12
> >>> map(len,thisd)
> [306, 306, 306, 306, 306, 306, 306, 306, 306, 306, 306, 306]
> >>> h
> ['subj', 'age', 'educ', 'pre', 'r_tot', 'post', 'r_tot2', 'mild',
> 'moderate', 'severe', 'cond', 'run']
> >>> len(h)
> 12
> >>> tl = rlc.TaggedList(thisd,h)
> >>> len(tl)
> 12
> >>> map(len,tl)
> [306, 306, 306, 306, 306, 306, 306, 306, 306, 306, 306, 306]
> >>> df = ro.RDataFrame(tl)
> >>> len(df)
> 3672
> >>>
>
> Is this a limitation? A bug? Or just a knowledge gap on my part? FWIW, I'm
> on linux, rpy2.0.0, python2.4.3, R2.8.0.
>
> I need to do this /lots/ of times (hundreds of thousands or more), so I
> would like this to be as efficient as possible. For the same reason, I
> don't want to save the data to disk and use r.read_table(). I could of
> course recode my strings to some numeric stand-ins and go the
> array.array() route, but I was hoping to carry the strings into R ......
>
> -best
> Gary
>
>
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