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Discussion: how to handle the new Int64 (nullable integer) dtype with pandas 0.24.0 #242
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FWIW: I'm leaning towards "Add an argument to |
Related to #149, does |
Just added I think we can do the same here. We might even want to call |
Great! Agree with your suggestion. We can always choose to default to (Sorry to be out of the discussion for a bit) |
Currently unreleased, but pandas 0.24.0 will add an extension dtype to allow a nullable integer dtype: http://pandas-docs.github.io/pandas-docs-travis/integer_na.html#integer-na Unfortunately, we won't use it with our current logic of deferring to the DataFrame constructor for type inference.
The question is how can we support this dtype in pandas-gbq? I see a few options.
pd.Int64Dtype()
by default for nullable integer columns, similar to how previously pandas-gbq defaulted tostring
for integer columns.pd.Int64Dtype()
for nullable integer columns when pandas-gbq 0.24.0+ is installed.read_gbq
which is a map of column names to dtypes, overriding the dtype of any column present.The text was updated successfully, but these errors were encountered: