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Describe the bug
When nan_as_null=False, we seem to raising an error saying there is mixed type of data:
Steps/Code to reproduce bug
In [1]: importcudfIn [2]: s=cudf.Series(["a", None])
In [3]: cudf.set_option("mode.pandas_compatible", True)
In [4]: ps=s.to_pandas()
In [5]: cudf.from_pandas(ps)
>/nvme/0/pgali/envs/cudfdev/lib/python3.11/site-packages/cudf/core/column/column.py(1958)as_column()
->raiseMixedTypeError(f"Cannot have NaN with {inferred_dtype}")
Expected behavior
We can error when we find string + nans but not when we find string + None's
The text was updated successfully, but these errors were encountered:
Fixes: #15708
This PR fixes an issue where we were throwing an error when `None` is present and `nan_as_null=False`, this is a bug because of using `pd.isna`, this returns `True` for `nan`, `None` and `NA`. Whereas we are only looking for `np.nan` and not `None` and `pd.NA`
Authors:
- GALI PREM SAGAR (https://github.com/galipremsagar)
Approvers:
- Matthew Roeschke (https://github.com/mroeschke)
- Bradley Dice (https://github.com/bdice)
URL: #15709
Describe the bug
When nan_as_null=False, we seem to raising an error saying there is mixed type of data:
Steps/Code to reproduce bug
Expected behavior
We can error when we find string + nans but not when we find string + None's
The text was updated successfully, but these errors were encountered: