Is the storage cost of fixed-format vs. tabular HDF documented?
I discovered that `store.put('key', df)` takes a whopping 40X more storage than `store('key', df, format='table')` for my DataFrames of floats. (See soft-matter/trackpy#144 for one demonstration.)
1. Am I doing it wrong? Is cost difference really that high?
2. I see that the read/write speed differences (which favor fixed-format) are documented, but I can't find mention of the storage requirements.

For my purposes, and for this issue, documenting it is sufficient. But if someone understands why the difference is so large, I'd be interested in that too.
