On Wed, Feb 6, 2013 at 5:36 PM, Yarden Katz <yarden.k...@gmail.com> wrote:
> [cross listed to pandas list since it's at intersection of pandas/rpy2
> - apologies for redundancy]
>
> Hi all,
>
> I'm trying to plot numpy arrays and pandas DataFrames with Rpy2 and am
> running into several problems. I import rpy2, pandas and scipy/numpy
> as follows:
>
> import rpy2
> from rpy2.robjects import r
> import rpy2.robjects.numpy2ri
> import pandas.rpy.common as com
> rpy2.robjects.numpy2ri.activate()
> from numpy import *
> import scipy
> import pandas
>
> Then I read a CSV file as a pandas DataFrame as usual:
>
> # Read a pandas DataFrame from file
> data = pandas.read_table("myfile.txt")
> r.hist(data.col1, xlab="", ylab="")
>
> "col1" of the "data" DataFrame contains only floats. When I plot it,
> my plot is littered with random numbers from the array on the
> histogram plot. They appear in bold in the top of the plot, and below
> the x-axis is regular font. They completely
> hide the xtick labels and the x-axis label (if there was one.) If I
> don't pass xlab="", the entire histogram is covered with numbers.
>
> My question is: how can I get rpy2 to actually read the information
> from the pandas DataFrame and use it in the plot? This is what
> happens natively in R with DataFrames, and I'm trying to get the same
> behavior here. For example, since it knows the names/labels of each
> column (in this case "col1"), it can place that on the X-axis. Is
> this possible? Does it require a conversion to an Rpy DataFrame
> before?
>
> Related issue: When I try to plot the DataFrame with:
>
> r.plot(data)
>
> It fails as well, with the error:
>
> ValueError: Nothing can be done for the type <class
> 'pandas.core.frame.DataFrame'> at the moment.
>
> Is it possible to get rpy2 to plot the DataFrame as best as it can
> (just like in native R, where R does whatever guessing is most
> reasonable to plot the DF in the requested way)? Since pandas
> DataFrames can do everything R DataFrames can, it should be possible.
>
> I also tried to explicitly convert to R DataFrames first:
>
> r.plot(com.convert_to_r_dataframe(data))
>
> which generates this output (the first part just prints a column from
> my dataframe for some reason)
>
> ==
> 0 1.791385
> 1 0.152134
> 2 0.000000
> 3 0.649393
> 4 0.000000
> 5 0.605132
> 6 0.000000
> 7 0.000000
> 8 0.000000
> 9 0.000000
> 10 2.084081
> 11 0.488127
> 12 0.006791
> 13 0.000000
> 14 0.244846
> ...
> 21500 1.578385
> 21501 0.080556
> 21502 166.923864
> 21503 15.274696
> 21504 0.000000
> 21505 1.333847
> 21506 0.000000
> 21507 0.000000
> 21508 0.000000
> 21509 0.075611
> 21510 0.000000
> 21511 2.025098
> 21512 0.562991
> 21513 0.000000
> 21514 0.000000
> Name: rpkm, Length: 21515
> Error in plot.window(...) : need finite 'xlim' values
> In addition: Warning messages:
> 1: In data.matrix(x) : NAs introduced by coercion
> 2: In data.matrix(x) : NAs introduced by coercion
> 3: In min(x) : no non-missing arguments to min; returning Inf
> 4: In max(x) : no non-missing arguments to max; returning -Inf
> 5: In min(x) : no non-missing arguments to min; returning Inf
> 6: In max(x) : no non-missing arguments to max; returning -Inf
> ---------------------------------------------------------------------------
> RRuntimeError Traceback (most recent call last)
> /home/yarden/.local/lib/python2.7/site-packages/IPython/utils/py3compat.pyc
> in execfile(fname, *where)
> 176 else:
> 177 filename = fname
> --> 178 __builtin__.execfile(filename, *where)
>
> /home/yarden/test_rpy2.py in <module>()
> 19 print data.rpkm
> 20 #r.hist(data.rpkm.values, xlab="", ylab="")
> ---> 21 r.plot(com.convert_to_r_dataframe(data))
> 22
> 23
>
> /home/yarden/.local/lib/python2.7/site-packages/rpy2-2.3.2-py2.7-linux-x86_64.egg/rpy2/robjects/functions.pyc
> in __call__(self, *args, **kwargs)
> 84 v = kwargs.pop(k)
> 85 kwargs[r_k] = v
> ---> 86 return super(SignatureTranslatedFunction,
> self).__call__(*args, **kwargs)
>
> /home/yarden/.local/lib/python2.7/site-packages/rpy2-2.3.2-py2.7-linux-x86_64.egg/rpy2/robjects/functions.pyc
> in __call__(self, *args, **kwargs)
> 33 for k, v in kwargs.iteritems():
> 34 new_kwargs[k] = conversion.py2ri(v)
> ---> 35 res = super(Function, self).__call__(*new_args, **new_kwargs)
> 36 res = conversion.ri2py(res)
> 37 return res
>
> RRuntimeError: Error in plot.window(...) : need finite 'xlim' values
> ==
>
> Advice on this will be very much appreciated. Thank you.
>
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Could you move this to GitHub? I don't have time to look at it right
now but dalejung or other active pandas users may be able to help.
- Wes
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