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FAILED python/pyarrow/tests/test_pandas.py::test_table_from_pandas_schema_index_columns - AssertionError: DataFrame.index are different
FAILED python/pyarrow/tests/parquet/test_dataset.py::test_read_partitioned_directory[False] - AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="foo") are different
FAILED python/pyarrow/tests/parquet/test_dataset.py::test_read_partitioned_directory_s3fs[False] - AssertionError: Attributes of DataFrame.iloc[:, 2] (column name="foo") are different
I think all those cases are where now an int32 dtype is preserved, while before it would have been cast to int64 by pandas. But the expected result still uses int64, causing the test failures.
The text was updated successfully, but these errors were encountered:
…ll numeric dtypes (not only 64bit versions) (#34498)
### Rationale for this change
Several failing tests in the nightly build (https://github.com/ursacomputing/crossbow/actions/runs/4277727973/jobs/7446784501)
### What changes are included in this PR?
Due to change in supported dtypes for Index in pandas, the tests expecting `int64`and not `int32` are failing with dev version of pandas. The failing tests are updated to match the new pandas behaviour.
* Closes: #34404
Authored-by: Alenka Frim <frim.alenka@gmail.com>
Signed-off-by: Joris Van den Bossche <jorisvandenbossche@gmail.com>
We have several failing tests in the nightly build (https://github.com/ursacomputing/crossbow/actions/runs/4277727973/jobs/7446784501) because of a change in pandas 2.0: the Index can now store all numeric dtypes, and not just int64/uint64/float64, see https://pandas.pydata.org/docs/dev/whatsnew/v2.0.0.html#index-can-now-hold-numpy-numeric-dtypes.
Failing tests because of this:
I think all those cases are where now an int32 dtype is preserved, while before it would have been cast to int64 by pandas. But the expected result still uses int64, causing the test failures.
The text was updated successfully, but these errors were encountered: