defining min_itemsize creates "data_columns"
I am trying to write results from a dataframe to hdf using the append (or .to_hdf) function. A few of my columns are large string whose length will vary (around 1k characters). Because its length will vary, I have to set, min_itemsize, for each of the variable columns. I do not want these fields to be treated as data_columns, but each time I define the column in the field min_itemsize, they become data_columns when looking at the result in hdf.

```
>>> df = pd.DataFrame(columns=['long string', 'a', 'b', 'longstring2'])
>>>df.to_hdf('test', 'key', data_columns=['a'])  # => only a is a data_column
>>>df.to_hdf('test', 'key', data_columns=['a'], min_itemsize={'long string': 1000, 'lonstring2': 1000}) # => now a, longstring2, and long string are datacolumns.
```

Is there any way to define min_itemsizes but not make those fields data_columns? I ask because when I make them data_columns I get warnings that my rowsize is too large. 
