DAAworld commented on PR #37232:
URL: https://github.com/apache/spark/pull/37232#issuecomment-2378324786
> With the release of pandas 2.0, I think this is PR should be re-opened,
right?
>
> I can recreate the issue originally described with
>
> ```python
> Python 3.9.16 (main, May 3 2023, 09:54:39)
> [GCC 10.2.1 20210110] on linux
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import pyspark
> >>> pyspark.__version__
> '3.4.0'
> >>> import pandas
> >>> pandas.__version__
> '2.0.1'
> >>> import pyspark.pandas as ps
> >>> ps.DatetimeIndex(["1970-01-01", "1970-01-02", "1970-01-03"])
> Setting default log level to "WARN".
> To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
> 23/05/18 21:07:30 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
> 23/05/18 21:07:31 WARN Utils: Service 'SparkUI' could not bind on port
4040. Attempting port 4041.
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/pandas/indexes/base.py",
line 2705, in __repr__
> pindex =
self._psdf._get_or_create_repr_pandas_cache(max_display_count).index
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/pandas/frame.py", line
13347, in _get_or_create_repr_pandas_cache
> self, "_repr_pandas_cache", {n: self.head(n + 1)._to_internal_pandas()}
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/pandas/frame.py", line
13342, in _to_internal_pandas
> return self._internal.to_pandas_frame
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/pandas/utils.py", line
588, in wrapped_lazy_property
> setattr(self, attr_name, fn(self))
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/pandas/internal.py",
line 1056, in to_pandas_frame
> pdf = sdf.toPandas()
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pyspark/sql/pandas/conversion.py",
line 251, in toPandas
> if (t is not None and not
all([is_timedelta64_dtype(t),is_datetime64_dtype(t)])) or
should_check_timedelta:
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/generic.py", line
6324, in astype
> new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/internals/managers.py",
line 451, in astype
> return self.apply(
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/internals/managers.py",
line 352, in apply
> applied = getattr(b, f)(**kwargs)
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/internals/blocks.py",
line 511, in astype
> new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/dtypes/astype.py",
line 242, in astype_array_safe
> new_values = astype_array(values, dtype, copy=copy)
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/dtypes/astype.py",
line 184, in astype_array
> values = values.astype(dtype, copy=copy)
> File
"/home/ubuntu/.local/lib/python3.9/site-packages/pandas/core/arrays/datetimes.py",
line 694, in astype
> raise TypeError(
> TypeError: Casting to unit-less dtype 'datetime64' is not supported. Pass
e.g. 'datetime64[ns]' instead.
> ```
my pandas == 2.2.2,pyspark==3.4.3,also raise TypeError: Casting to unit-less
dtype 'datetime64' is not supported. Pass e.g. 'datetime64[ns]' instead.
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