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It seems that nullable strings, integers, and booleans are not supported as input types. When passing a pandas DataFrame, each column is converted to numpy arrays and validated with np.dtype, which doesn't support certain nullable types. Similarly, when passing a Snowpark DataFrame, it is converted using the signature type, which also relies on np.dtype.
np.dtype
Can we improve validation to use pandas dtypes instead of numpy dtypes, given that some ML models like LightGBM can work with nullable columns?
The text was updated successfully, but these errors were encountered:
Hi @kenkoooo - this should be addressed in version 1.7.1. Please let us know if you run into any issues
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It seems that nullable strings, integers, and booleans are not supported as input types. When passing a pandas DataFrame, each column is converted to numpy arrays and validated with
np.dtype
, which doesn't support certain nullable types. Similarly, when passing a Snowpark DataFrame, it is converted using the signature type, which also relies onnp.dtype
.Can we improve validation to use pandas dtypes instead of numpy dtypes, given that some ML models like LightGBM can work with nullable columns?
The text was updated successfully, but these errors were encountered: