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POHow can I efficiently save a python pandas dataframe in hdf5 and open it as a dataframe in R?
 

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  1. POHow can I efficiently save a python pandas dataframe in hdf5 and open it as a dataframe in R?
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    <p>I think the title covers the issue, but to elucidate:</p> <p>The <a href="http://pandas.pydata.org" rel="noreferrer">pandas</a> python package has a DataFrame data type for holding table data in python. It also has a convenient interface to the <a href="http://www.hdfgroup.org/HDF5/" rel="noreferrer">hdf5</a> file format, so pandas DataFrames (and other data) can be saved using a simple dict-like interface (assuming you have <a href="http://pytables.org" rel="noreferrer">pytables</a> installed)</p> <pre><code>import pandas import numpy d = pandas.HDFStore('data.h5') d['testdata'] = pandas.DataFrame({'N': numpy.random.randn(5)}) d.close() </code></pre> <p>So far so good. However, if I then try to load that same hdf5 into R I see things aren't so simple:</p> <pre><code>&gt; library(hdf5) &gt; hdf5load('data.h5') NULL &gt; testdata $block0_values [,1] [,2] [,3] [,4] [,5] [1,] 1.498147 0.8843877 -1.081656 0.08717049 -1.302641 attr(,"CLASS") [1] "ARRAY" attr(,"VERSION") [1] "2.3" attr(,"TITLE") [1] "" attr(,"FLAVOR") [1] "numpy" $block0_items [1] "N" attr(,"CLASS") [1] "ARRAY" attr(,"VERSION") [1] "2.3" attr(,"TITLE") [1] "" attr(,"FLAVOR") [1] "numpy" attr(,"kind") [1] "string" attr(,"name") [1] "N." $axis1 [1] 0 1 2 3 4 attr(,"CLASS") [1] "ARRAY" attr(,"VERSION") [1] "2.3" attr(,"TITLE") [1] "" attr(,"FLAVOR") [1] "numpy" attr(,"kind") [1] "integer" attr(,"name") [1] "N." $axis0 [1] "N" attr(,"CLASS") [1] "ARRAY" attr(,"VERSION") [1] "2.3" attr(,"TITLE") [1] "" attr(,"FLAVOR") [1] "numpy" attr(,"kind") [1] "string" attr(,"name") [1] "N." attr(,"TITLE") [1] "" attr(,"CLASS") [1] "GROUP" attr(,"VERSION") [1] "1.0" attr(,"ndim") [1] 2 attr(,"axis0_variety") [1] "regular" attr(,"axis1_variety") [1] "regular" attr(,"nblocks") [1] 1 attr(,"block0_items_variety") [1] "regular" attr(,"pandas_type") [1] "frame" </code></pre> <p>Which brings me to my question: ideally I would be able to save back and forth from R to pandas. I can obviously write a wrapper from pandas to R (I think... though I think if I use a pandas <a href="http://pandas.sourceforge.net/indexing.html" rel="noreferrer">MultiIndex</a> that might become trickier), but I don't think I can easily then use that data back in pandas. Any suggestions?</p> <p>Bonus: what I <em>really</em> want to do is use the <a href="http://datatable.r-forge.r-project.org/" rel="noreferrer">data.table</a> package in R with a pandas dataframe (the keying approach is suspiciously similar in both packages). Any help on that one greatly appreciated.</p>
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    1. COWhat is the problem exactly? Doesn't `testdata$block0_values` return the values you saved from the panda?
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      1. POHow can I efficiently save a python pandas dataframe in hdf5 and open it as a dataframe in R?
      1. USPaul Hiemstra
    2. COThe problem is then being able to reopen again in pandas (see the later part of my question). I can convert to an R data.frame (or data.table) do some manipulations, but then I can't save back to pandas easily (without another, probably more complicated, wrapper).
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      1. USGriffith Rees
    3. COI think what you're asking about would be very useful. For now, would it be acceptable to use something like this: http://pandas.pydata.org/pandas-docs/stable/r_interface.html or perhaps even use the R bridge support in recent ipython? (http://ipython.org/ipython-doc/stable/config/extensions/rmagic.html)
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      1. USDav Clark
 

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