title: How to correctly use Pandas iterators for hdf5?
body: <p>I have an HDF5 file that I am simply trying to read the data in chunks and output to a mySQL table. </p>
  
  <p>Using pandas v. 0.12.0
  Code looks like,</p>
  
  <pre><code>iter = store.select('data',iterator=True, chunksize=5000)
  for data in iter:
      # write the data out 
  </code></pre>
  
  <p>But I get an exception:</p>
  
  <pre><code>for data in iter:
    File "d:\python27\lib\site-packages\pandas\io\pytables.py", line 969, in __iter__
    v = self.func(current, stop)
    File "d:\python27\lib\site-packages\pandas\io\pytables.py", line 451, in func
      return s.read(where=where, start=_start, stop=_stop, columns=columns, **kwargs)
    File "d:\python27\lib\site-packages\pandas\io\pytables.py", line 3175, in read
  
      mgr = BlockManager([block], [cols_, index_])
    File "d:\python27\lib\site-packages\pandas\core\internals.py", line 1001, in __init__
      self._verify_integrity()
    File "d:\python27\lib\site-packages\pandas\core\internals.py", line 1239, in _verify_integrity
  construction_error(tot_items,block.values.shape[1:],self.axes)
    File "d:\python27\lib\site-packages\pandas\core\internals.py", line 2216, in construction_error
  tuple(map(int, [len(ax) for ax in axes]))))
  ValueError: Shape of passed values is (1, 5000), indices imply (1, 3751044)
  </code></pre>
  
  <p>I don't understand what the error is trying to say, ValueError: Shape of passed values is (1, 5000), indices imply (1, 3751044). And I don't know how to make it happy.</p>
  
  <p>I thought that the chunksize=5000 value would tell pandas to read the data in 5000 row chunks, but apparently it does not like that doing the iteration. What is the correct usage of the select(chunksize=XXXX)?</p>