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R dataset #5036
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R dataset #5036
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…port for converting R datasets to pandas objects.
| add rpy2 in ci/requirements 2.7, 3.3 maybe |
| i think need to add |
| problem is that is a huge honking install on ubuntu |
| all this for |
| any way to have it skip all of the display stuff ? |
| someone more knowledgeable than me about |
| It's simply not the case that all of those deps are required to install R. On Arch Linux, these are the dependencies: blas lapack bzip2 libpng libjpeg libtiff ncurses pcre readline zlib perl gcc-libs libxt libxmu pango xz desktop-file-utils |
| why do you need to build R, can't you just use apt-get to get the package On Sun, Sep 29, 2013 at 12:12 AM, Phillip Cloud notifications@github.comwrote:
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| those ubuntu deps i listed above are from calling |
| well -- it feels that list a bit bloated due to recommends -- what if you do |
| Installing R on Travis seems like an unsolved problem for many people: http://yihui.name/en/2013/04/travis-ci-general-purpose/. Would it be helpful if I move the unit tests back into rpy/common.py so those with R installed could run the tests, but not have it part of the official test suite? |
| just add a |
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can you change to nose.SkipTest('R not installed') thxs....then squash to smaller num of commits
Motivation for this pull request came from this problem: http://stackoverflow.com/q/19039356/190597.
The problems:
pandas.rpy.common.load_datacurrently fails to load high-dimensional arrays such as the "Titanic" dataset.load_dataprints an error to stdout and returns None.load_datato "iris3", "state.division" or "state.region" R datasets currently raise a TypeError.This pull request:
load_datato convert the "Titanic" dataset (and similar high-dimensional arrays) to "melted" DataFrames. The code does not use R's melt function, since that would introduce a new dependency.