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Annoying bug in PyTables (affects Big Data analysis with Pandas)

Pandas HDF5 interface through PyTables is awesome because it allows you to select and process small chunks of data from a much larger data file stored on disk. PyTables, however, has an annoying and subtle bug and I just wanted to point you to it so that you don't have to spend hours debugging code like I did.

In short, if you have a DataFrame, and a column of that DF starts with a NaN, any select statements that you run with that conditions on that column will return empty (you won't get any results back, ever). There is a work around, but I chose to use a dummy value instead.

This shook my confidence in Pandas as an analysis platform a bit (though it is really PyTable's fault).
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