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    <p>You can store the dataframe with an index of the columns as follows:</p> <pre><code>import pandas as pd import numpy as np from pandas.io.pytables import Term index = pd.date_range('1/1/2000', periods=8) df = pd.DataFrame( np.random.randn(8,3), index=index, columns=list('ABC')) store = pd.HDFStore('mydata.h5') store.append('df_cols', df, axes='columns') </code></pre> <p>and then select as you might hope:</p> <pre><code>In [8]: store.select('df_cols', [Term('columns', '=', 'A')]) Out[8]: 2000-01-01 0.347644 2000-01-02 0.477167 2000-01-03 1.419741 2000-01-04 0.641400 2000-01-05 -1.313405 2000-01-06 -0.137357 2000-01-07 -1.208429 2000-01-08 -0.539854 </code></pre> <p>Where:</p> <pre><code>In [9]: df Out[9]: A B C 2000-01-01 0.347644 0.895084 -1.457772 2000-01-02 0.477167 0.464013 -1.974695 2000-01-03 1.419741 0.470735 -0.309796 2000-01-04 0.641400 0.838864 -0.112582 2000-01-05 -1.313405 -0.678250 -0.306318 2000-01-06 -0.137357 -0.723145 0.982987 2000-01-07 -1.208429 -0.672240 1.331291 2000-01-08 -0.539854 -0.184864 -1.056217 </code></pre> <p>.</p> <p>To me this isn't an ideal solution, as we can only indexing the DataFrame by one thing! Worryingly <a href="http://pandas.pydata.org/pandas-docs/dev/io.html#hdf5-pytables" rel="noreferrer">the docs</a> seem to suggest you <em>can</em> only index a DataFrame by one thing, at least using <code>axes</code>:</p> <blockquote> <p>Pass the axes keyword with a list of dimension (currently must by exactly 1 less than the total dimensions of the object).</p> </blockquote> <p>I may be reading this incorrectly, in which case <strong>hopefully someone can prove me wrong!</strong></p> <p>.</p> <p>Note: One way I have found to index a DataFrame by two things (index and columns), is to convert it to a Panel, which can then retrieve using two indices. However then we have to convert to the selected subpanel to a DataFrame each time items are retrieved... again, not ideal.</p>
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    1. POSelecting columns from pandas.HDFStore table
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    1. USAndy Hayden
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    1. COShould the index be datetime? I used chars as index, and proceeded the same way you did. However, when I came by the select statement in your code (in[8]). It retrieved the whole dataframe. Am I missing something here ??
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    2. COsee my answer below; your are basically storing a transposed frames. the axes argument is not needed here
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