title: Pandas Pytables warnings and slow performance
body: <p>I have been testing out pandas and pytables for some large financial data sets, and have run in to a real stumbling block:</p>
  
  <p>When storing in a pytables file, pandas appears to be storing multidimensional data in massively long rows, not columns.</p>
  
  <p>try this:</p>
  
  <pre><code>from pandas import *
  df = DataFrame({'col1':randn(100000000),'col2':randn(100000000)})
  store = HDFStore('test.h5')
  store['data'] = df    #should be a warning here about exceeding the maximum recommended rowsize
  store.handle
  </code></pre>
  
  <p>output:</p>
  
  <pre><code>File(filename=test7.h5, title='', mode='a', rootUEP='/', filters=Filters(complevel=0, shuffle=False, fletcher32=False))
  / (RootGroup) ''
  /data (Group) ''
  /data/axis0 (Array(2,)) ''
    atom := StringAtom(itemsize=4, shape=(), dflt='')
    maindim := 0
    flavor := 'numpy'
    byteorder := 'irrelevant'
    chunkshape := None
  /data/axis1 (Array(100000000,)) ''
    atom := Int64Atom(shape=(), dflt=0)
    maindim := 0
    flavor := 'numpy'
    byteorder := 'little'
    chunkshape := None
  /data/block0_items (Array(2,)) ''
    atom := StringAtom(itemsize=4, shape=(), dflt='')
    maindim := 0
    flavor := 'numpy'
    byteorder := 'irrelevant'
    chunkshape := None
  /data/block0_values (Array(2, 100000000)) ''
    atom := Float64Atom(shape=(), dflt=0.0)
    maindim := 0
    flavor := 'numpy'
    byteorder := 'little'
    chunkshape := None
  </code></pre>
  
  <p>I'm not totally sure, but i reckon that combined with the error message, the Array(2,100000000) means a 2D array with 2 rows and 100,000,000 columns. This is also the way it's shown in HDFView.</p>
  
  <p>I've been experiencing extremely poor performance (10 seconds for data['ticks'].head() in some cases), is this what's to blame?</p>