Laurent,

Thanks for your suggestions.  The following code:

import rpy
f = rpy.r.attach('.RDatalongrun',pos=2)
dat = rpy.with_mode(rpy.NO_CONVERSION, rpy.r.get)("longrun",pos=2)
print "type(dat) = " + str(type(dat))
colnames = rpy.r.colnames(dat)
print "type(colnames) = " + str(type(colnames))
print colnames

now produces a Python list of the columns:

type(dat) = <type 'Robj'>
type(colnames) = <type 'list'>
['time', 'index', 'lat', 'lon', 'agl', 'grdht', 'foot', 'sampt',
'temp0', 'swrad', 'zi', 'dens', 'dmass', 'sigmaw', 'TL']

- Tyler

Laurent Gautier wrote:
> Tyler Erickson wrote:
>> I am trying to read in a R-formatted datafile using RPy.  When I read in
>> the file using R and display the data, the column headers are included.
>>
>> $ R
>>> attach(".RDatalongrun",pos=2)
>>> dat<-get("longrun",pos=2)
>>> dat[1:5,1:9]
>>      time index     lat      lon       agl    grdht      foot  
>> sampt  temp0
>> [1,]  -60     1 45.7993 -90.4651  220.1694 496.0374 0.1794837 51.8537
>> 296.35
>> [2,]  -60     2 45.7283 -90.7861 1187.4362 366.4808 0.0025203  0.7241
>> 296.77
>> [3,]  -60     3 45.7782 -90.5021  237.6977 496.0374 0.1530388 44.1661
>> 296.39
>> [4,]  -60     4 45.7706 -90.5811  976.4551 496.0374 0.1043193 30.1000
>> 296.35
>> [5,]  -60     5 45.8013 -90.4390   55.8362 496.0374 0.2078631 60.0000
>> 296.30
>>
>>
>> However, I can't figure out how to determine the column headers when I
>> read in the same file with RPy.
>>
>> $ python
>> Python 2.5.2 (r252:60911, Oct  5 2008, 19:24:49)
>> [GCC 4.3.2] on linux2
>> Type "help", "copyright", "credits" or "license" for more information.
>>>>> from rpy import *
>>>>> f = r.attach('.RDatalongrun',pos=2)
>>>>> dat = r.get("longrun",pos=2)
>
> You'll most likely have to switch to the NO_CONVERSION mode before
> calling r.get(), then you'll be able to call r.colnames() on the
> resulting object.
>
> rpy2 could be making things easier, here with an example from the dev
> version:
> http://rpy.sourceforge.net/rpy2/doc-dev/html/robjects.html#names
>
>
>
> L.
>
>
>>>>> type(dat)
>> <type 'numpy.ndarray'>
>>>>> dat[0:4,1:8]
>> array([[  1.00000000e+00,   4.57993000e+01,  -9.04651000e+01,
>>           2.20169400e+02,   4.96037400e+02,   1.79483700e-01,
>>           5.18537000e+01],
>>        [  2.00000000e+00,   4.57283000e+01,  -9.07861000e+01,
>>           1.18743620e+03,   3.66480800e+02,   2.52030000e-03,
>>           7.24100000e-01],
>>        [  3.00000000e+00,   4.57782000e+01,  -9.05021000e+01,
>>           2.37697700e+02,   4.96037400e+02,   1.53038800e-01,
>>           4.41661000e+01],
>>        [  4.00000000e+00,   4.57706000e+01,  -9.05811000e+01,
>>           9.76455100e+02,   4.96037400e+02,   1.04319300e-01,
>>           3.01000000e+01]])
>>
>>
>> ------------------------------------------------------------------------------
>>
>> Crystal Reports - New Free Runtime and 30 Day Trial
>> Check out the new simplified licensing option that enables unlimited
>> royalty-free distribution of the report engine for externally facing
>> server and web deployment.
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>


-- 
Tyler A. Erickson, Ph.D.
Research Scientist, Michigan Tech Research Institute, and 
Adjunct Assistant Professor, Dept. of Civil & Environmental Engineering
Michigan Technological University
3600 Green Court, Suite 100
Ann Arbor, MI 48105
W 83.6889°, N 42.3021° (WGS84) 
tyler.erick...@mtu.edu 
(734) 913-6846
http://people.mtri.org/tyler+erickson
http://www.mtri.org
http://www.michiganview.org


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Crystal Reports - New Free Runtime and 30 Day Trial
Check out the new simplified licensing option that enables unlimited
royalty-free distribution of the report engine for externally facing 
server and web deployment.
http://p.sf.net/sfu/businessobjects
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