BUG: `check_dtype=False` in `assert_series_equal` is not returning expected results for `datetime` & `timedelta` types in `pandas-2.0` · Issue #52449 · pandas-dev/pandas (original) (raw)

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Reproducible Example

In [1]: import pandas as pd

In [2]: s = pd.Series([1000213, 2131232, 21312331], dtype='datetime64[s]')

In [3]: s Out[3]: 0 1970-01-12 13:50:13 1 1970-01-25 16:00:32 2 1970-09-04 16:05:31 dtype: datetime64[s]

In [4]: p = s.astype('datetime64[ms]')

In [6]: p Out[6]: 0 1970-01-12 13:50:13 1 1970-01-25 16:00:32 2 1970-09-04 16:05:31 dtype: datetime64[ms]

In [7]: s Out[7]: 0 1970-01-12 13:50:13 1 1970-01-25 16:00:32 2 1970-09-04 16:05:31 dtype: datetime64[s]

In [8]: pd.testing.assert_series_equal(s, p) # Failure: Works as expected since `dtype's` are different

AssertionError Traceback (most recent call last) Cell In[8], line 1 ----> 1 pd.testing.assert_series_equal(s, p)

[... skipping hidden 2 frame]

File /nvme/0/pgali/envs/cudfdev/lib/python3.10/site-packages/pandas/_testing/asserters.py:596, in raise_assert_detail(obj, message, left, right, diff, first_diff, index_values) 593 if first_diff is not None: 594 msg += f"\n{first_diff}" --> 596 raise AssertionError(msg)

AssertionError: Attributes of Series are different

Attribute "dtype" are different [left]: datetime64[s] [right]: datetime64[ms]

In [9]: pd.testing.assert_series_equal(s, p, check_dtype=False) # I expect this to not raise, because we are asking for the dtypes to be ignored and the data as seen above is perfectly identical.

AssertionError Traceback (most recent call last) Cell In[9], line 1 ----> 1 pd.testing.assert_series_equal(s, p, check_dtype=False)

[... skipping hidden 1 frame]

File /nvme/0/pgali/envs/cudfdev/lib/python3.10/site-packages/pandas/_testing/asserters.py:741, in assert_extension_array_equal(left, right, check_dtype, index_values, check_exact, rtol, atol, obj) 732 assert_attr_equal("dtype", left, right, obj=f"Attributes of {obj}") 734 if ( 735 isinstance(left, DatetimeLikeArrayMixin) 736 and isinstance(right, DatetimeLikeArrayMixin) (...) 739 # Avoid slow object-dtype comparisons 740 # np.asarray for case where we have a np.MaskedArray --> 741 assert_numpy_array_equal( 742 np.asarray(left.asi8), 743 np.asarray(right.asi8), 744 index_values=index_values, 745 obj=obj, 746 ) 747 return 749 left_na = np.asarray(left.isna())

[... skipping hidden 1 frame]

File /nvme/0/pgali/envs/cudfdev/lib/python3.10/site-packages/pandas/_testing/asserters.py:666, in assert_numpy_array_equal.._raise(left, right, err_msg) 664 diff = diff * 100.0 / left.size 665 msg = f"{obj} values are different ({np.round(diff, 5)} %)" --> 666 raise_assert_detail(obj, msg, left, right, index_values=index_values) 668 raise AssertionError(err_msg)

AssertionError: Series are different

Series values are different (100.0 %) [index]: [0, 1, 2] [left]: [1000213, 2131232, 21312331] [right]: [1000213000, 2131232000, 21312331000]

Issue Description

With the newly introduced datetime64 & timedelta64 time resolutions, it is possible to hold the identical data in different dtypes. So when we pass check_dtype=False to assert_frame_equal we expect identical data to pass and not raise an error.

Expected Behavior

In [9]: pd.testing.assert_series_equal(s, p, check_dtype=False) # Passes.

In [10]: pd.testing.assert_series_equal(s, p, check_dtype=True) # Raises error

Installed Versions

INSTALLED VERSIONS

commit : c2a7f1a
python : 3.10.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
Version : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.0rc1
numpy : 1.23.5
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.6.1
pip : 23.0.1
Cython : 0.29.33
pytest : 7.2.2
hypothesis : 6.70.1
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.12.0
pandas_datareader: None
bs4 : 4.12.0
bottleneck : None
brotli :
fastparquet : None
fsspec : 2023.3.0
gcsfs : None
matplotlib : None
numba : 0.56.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2023.3.0
scipy : 1.10.1
snappy :
sqlalchemy : 1.4.46
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

BUG: check_dtype=False in assert_series_equal is not returning expected results for datetime & timedelta types in pandas-2.0 · Issue #52449 · pandas-dev/pandas (original) (raw)