uint64 inferred as float64
I'm running into an issue with `read_csv` where a column is being inferred as a `float64` column when it should be `uint64`. There are no nulls or missing values. Unfortunately, I am unable to provide the data and I have been unable to reliably reproduce the error with a synthetic dataset.

I managed to reduce my CSV file to 5-columns, 131074 rows. If I drop any row at the beginning or end, then I get the correct dtype (uint64). If I reorder the rows of the CSV, then the problem goes away as well. If I drop (meaning, textually alter the CSV) all columns from the CSV except the problematic one, then the problem goes away too. Similarly, dropping all columns after the problematic one also makes the problem go away. If I manually specify the type as uint64, then I get the correct dtype.

So the situation seems to be that type inference is being affected by things that really shouldn't be affecting the type inference of this column. I didn't look at the source code for the inference, but I'm hoping this might be enough information to help identify the issue.  I'm running pandas 0.22.