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html_url id node_id tag_name target_commitish name draft author prerelease created_at published_at assets body repo 8575785 MDc6UmVsZWFzZTg1NzU3ODU= 0.5 master csvs-to-sqlite 0.5 0 9599 0 2017-11-19T05:11:27Z 2017-11-19T05:53:25Z [] ## Now handles columns with integers and nulls in correctly Pandas does a good job of figuring out which SQLite column types should be used for a DataFrame - with one exception: due to a limitation of NumPy it treats columns containing a mixture of integers and NaN (blank values) as being of type float64, which means they end up as REAL columns in SQLite. To fix this, we now check to see if a float64 column actually consists solely of NaN and integer-valued floats (checked using v.is_integer() in Python). If that is the case, we over-ride the column type to be INTEGER instead. See #5 - also a8ab524 and 0997b7b 110509816
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