title: Pandas HDFStore.info() providing incorrect information regarding DataFrame size
body: <p>I'm trying to get an idea of the total size of my dataset, which is broken up into chunks due to memory constraints on the server that I am using to aggregate the data. The raw data is accessed through a mongodb aggregation pipeline, and the cursor objects from this query are transformed to DataFrames and committed to an HDFStore with pandas. The actual DataFrames in this store are intact and display the proper size once I load them into memory, however when calling HDFStore.info() some of the items show incorrect dimensions:</p>
  
  <pre class="lang-py prettyprint-override"><code>import pandas as pd
  
  store = pd.HDFStore('store.h5')
  print(store.info())
  </code></pre>
  
  <pre><code>&lt;class 'pandas.io.pytables.HDFStore'&gt;
  File path: store.h5
  /auto0             frame        (shape-&gt;[127609,14])
  /auto1             frame        (shape-&gt;[130097,14])
  /auto10            frame        (shape-&gt;[174314,14])
  /auto11            frame        (shape-&gt;[176243,14])
  /auto12            frame        (shape-&gt;[16290,13]) 
  /auto13            frame        (shape-&gt;[687,12])   
  /auto14            frame        (shape-&gt;[653,12])   
  /auto15            frame        (shape-&gt;[1244,12])  
  /auto16            frame        (shape-&gt;[1064,12])  
  /auto17            frame        (shape-&gt;[96335,14]) 
  /auto18            frame        (shape-&gt;[193038,14])
  /auto19            frame        (shape-&gt;[214158,14])
  /auto2             frame        (shape-&gt;[133799,14])
  /auto20            frame        (shape-&gt;[239648,14])
  /auto21            frame        (shape-&gt;[250819,14])
  ...
  /habl56            frame        (shape-&gt;[1,12])     
  /habl57            frame        (shape-&gt;[103150,12])
  /habl58            frame        (shape-&gt;[97122,12]) 
  /habl59            frame        (shape-&gt;[117226,12])
  /habl6             frame        (shape-&gt;[61320,12]) 
  /habl60            frame        (shape-&gt;[123106,12])
  /habl61            frame        (shape-&gt;[106783,12])
  /habl62            frame        (shape-&gt;[1,12])     
  /habl63            frame        (shape-&gt;[1,12])     
  /habl7             frame        (shape-&gt;[65562,12]) 
  /habl8             frame        (shape-&gt;[77967,12]) 
  /habl9             frame        (shape-&gt;[79227,12]) 
  </code></pre>
  
  <p>There are ~150 DataFrames in the HDFStore and they should all be in the neighborhood of 50k - 250k rows. Explicitly checking some of the (shape->[1,12]) items:</p>
  
  <pre class="lang-py prettyprint-override"><code>store.get('habl56').shape
  store.get('habl62').shape
  </code></pre>
  
  <pre><code>(132145, 12)
  (144802, 12)
  </code></pre>
  
  <p>They load in without issue. </p>
  
  <p>Now this is not a hugely important problem and it doesn't stop me from doing any analysis, however I figured I'd post it since my initial googling-around of this issue came up empty. </p>
  
  <p>The true sizes of the (shape->[1,12]) items are not excessively large, so it isn't an overflow. The data present in these items is also not atypical in the context of my dataset (which I unfortunately cannot provide). </p>
  
  <p>Nothing changed when I performed the aggregation a second time to obtain a fresh copy of the data. </p>
  
  <p>The data is a mix of numeric, string, and dict objects, however each column contains strictly one dtype. The dict objects come from the JSON-like (BSON) structure of mongodb, and they are consistent between all DataFrames.</p>
  
  <p>If anyone has experienced this interesting bug, please let me know whether you found a way to circumvent it (without loading in each frame individually and calling .shape on it that is).</p>