Hi RPy gurus,
I'm trying to upgrade to rpy2 and ran into the following trouble (CentOS5,
R2.8.0). I got rpy2 to build without difficulty, and set RHOME
appropriately (note, if it matters I have R and rpy installed in a
non-standard site, as I don't have admin rights to put it in /usr/local).
fixed in svn and will be fixed in the next release.
>
> Laurent
>
> 2008/12/12 Gary Strangman :
>>
>> Hi RPy gurus,
>>
>> I'm trying to upgrade to rpy2 and ran into the following trouble (CentOS5,
>> R2.8.0). I got rpy2 to build without difficulty, and se
Hi again,
Forgive me if this is a completely silly question for rpy2. I'm trying to
wean myself from rpy, but am confused by the new approach to conversion.
If I fit a model and collect summary info as follows ...
fit = robjects.r.lm(fmla,data)
summary = robjects.r.summary(fit)
... the summar
n Fri, 12 Dec 2008, laurent oget wrote:
> I do std-error=r['$'](summary,'sigma')
> I think r.names(summary) will give you the components.
>
> Laurent
>
> 2008/12/12 Gary Strangman :
>>
>> Hi again,
>>
>> Forgive me if this is a completely
>> (Intercept) 10.9205792 2.9934159 3.6481997 0.001341692
>> prerbmt 0.4226101 0.1729016 2.4442236 0.022599474
>> mri -0.3495370 0.7497424 -0.4662095 0.645450898
>>
>> ... and if I want the estimate for the 2nd coefficient ...
>>
> print summary[3][1]
>> 0.4226101
>
> You c
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, (
13 Dec 2008, Marcos Silva wrote:
> 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
>
>>
>> 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,
Forgive this seemingly simple question for rpy2 ... how do you specify
'dotted' function arguments from python? I want to specify the
na.action=na.omit for lme, but the python code below (which I though would
be equivalent to that required by rpy) doesn't work for rpy2:
R:
> fit = lme(fmla,dat
The rnumpy concept looks great, and addresses some annoyances I've
encountered working at the interface between R and numpy. I hope to test
rnumpy this week, but in the meantime ... the text suggests that R data
frames can be manipulated/sliced using rnumpy. Can they be created
directly as wel
Hi all,
I have a python list of lists (each sublist is a row of data), plus a list
of column names. Something like this ...
>>> d = [['S80', 'C', 137.5, 0],
['S82', 'C', 155.1, 1],
['S83', 'T', 11.96, 0],
['S84', 'T', 47,1]]
['S85', 'T', numpy.nan, 1]
t
Gary
On Tue, 29 Sep 2009, Laurent Gautier wrote:
> Gary,
>
> Two things come to my mind:
>
> - Try having an initial Python data structure that requires less
> transformations than your current one in order to become a DataFrame.
>
> - Use rpy2.rinterface when speed ma
Great. Thanks for the jump-start!
On Tue, 29 Sep 2009, Laurent Gautier wrote:
> Gary Strangman wrote:
>>
>> Hi Laurent,
>>
>> The only way to reduce the number of transformations is to add an
>> equivalent number of columns to the dataframe (so that instea
disk
hits each time I ran the thing, I worried about burning a hole in my disk.
;-) I'll try a few things and post any useful results ...
Gary
On Tue, 29 Sep 2009, Peter wrote:
> On Tue, Sep 29, 2009 at 12:21 PM, Gary Strangman wrote:
>>
>> Hi Laurent,
>>
>
ad off to do some tinkering and profiling now.
-best
Gary
On Tue, 29 Sep 2009, Nathaniel Smith wrote:
> On Tue, Sep 29, 2009 at 4:21 AM, Gary Strangman
> wrote:
>> Without benchmarking, that seems mighty inefficient. Nathaniel Smith's
>> rnumpy mostly allows t
Hi again,
What is the proper syntax to set parameters like na.action in R's lm()
function? For example, if I create a dataframe with NAs and want them to
be dealt with via R's na.exclude, how do I formulate the call? Things
like the following fail:
>>> from rpy2.robjects import *
>>> f = r.fo
Has anyone out there buit a windows installer for rpy2.1rc that they might
be able to share?
-best
Gary
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Does the following happen for anyone else?
/space/nsg/8/users> python
Python 2.6.3 (r263:75183, Oct 16 2009, 12:24:10)
[GCC 3.4.6 20060404 (Red Hat 3.4.6-10)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import rpy2.robjects
>>> print rpy2.__version__
2.1.0
Hi rpy'ers,
In the older versions of rpy(2?), I could redirect stdout to a file to
capture all console output. This was adequate, though I got lots of extra
info over and above what R would print for the same object. (For example,
when printing the result of an lm() model fit, I'd get the enti
Done ... #36.
On Wed, 14 Apr 2010, Gary Strangman wrote:
>
> Does the following happen for anyone else?
>
> /space/nsg/8/users> python
> Python 2.6.3 (r263:75183, Oct 16 2009, 12:24:10)
> [GCC 3.4.6 20060404 (Red Hat 3.4.6-10)] on linux2
> Type "help", "
>> In the older versions of rpy(2?), I could redirect stdout to a file to
>> capture all console output. This was adequate, though I got lots of extra
>> info over and above what R would print for the same object. (For example,
>> when printing the result of an lm() model fit, I'd get the entire d
Hi all,
I have a mixed-type structured numpy array (including columns of ints,
floats and strings), sometimes with missing values. In rpy2-2.1, what is
the recommended (including fastest and least memory-expensive) way to
convert such a structure to an R dataframe? Here's where I've been:
1)
Does anyone have a guess why creating a data frame created from a python
dictionary of lists would "occasionally" segfault? That is, given ...
a = a list
b = another list
c = another list
df = r.data_frame(a=a, b=b, c=c) has never failed me. However, if I create
a dictionary first ...
>>> dct
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