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Automated feature engineering for geospatial data

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Right now, SpellBook relies on a simple ordered index from the input dataframe. If that's not the case, the output dataframe will be misaligned.

bug

We upload a dataframe into BQ (as a table) for every call. This is inefficient given larger datasets. There should be a better way to: - Check if the dataframe...

performance

We should first validate that the input columns exist before running the actual query.

enhancement