BUG: Series.compare with differently named series raises ValueError, but should not

[sfc-gh-mvashishtha]

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• I have confirmed this bug exists on the latest released version of Modin.

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Reproducible Example

import modin.pandas as pd

pd.Series(1, name='a').compare(pd.Series(2, name='b'))

Issue Description

DataFrame.compare requires the two frames to have the same columns, but Series.compare should not.

Expected Behavior

should match pandas and ignore the series name.

Error Logs

RayTaskError(ValueError)                  Traceback (most recent call last)
File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/IPython/core/formatters.py:708, in PlainTextFormatter.__call__(self, obj)
    701 stream = StringIO()
    702 printer = pretty.RepresentationPrinter(stream, self.verbose,
    703     self.max_width, self.newline,
    704     max_seq_length=self.max_seq_length,
    705     singleton_pprinters=self.singleton_printers,
    706     type_pprinters=self.type_printers,
    707     deferred_pprinters=self.deferred_printers)
--> 708 printer.pretty(obj)
    709 printer.flush()
    710 return stream.getvalue()

File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/IPython/lib/pretty.py:410, in RepresentationPrinter.pretty(self, obj)
    407                         return meth(obj, self, cycle)
    408                 if cls is not object \
    409                         and callable(cls.__dict__.get('__repr__')):
--> 410                     return _repr_pprint(obj, self, cycle)
    412     return _default_pprint(obj, self, cycle)
    413 finally:

File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/IPython/lib/pretty.py:778, in _repr_pprint(obj, p, cycle)
    776 """A pprint that just redirects to the normal repr function."""
    777 # Find newlines and replace them with p.break_()
--> 778 output = repr(obj)
    779 lines = output.splitlines()
    780 with p.group():

File ~/sources/modin/modin/logging/logger_decorator.py:144, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    129 """
    130 Compute function with logging if Modin logging is enabled.
    131
   (...)
    141 Any
    142 """
    143 if LogMode.get() == "disable":
--> 144     return obj(*args, **kwargs)
    146 logger = get_logger()
    147 logger.log(log_level, start_line)

File ~/sources/modin/modin/pandas/dataframe.py:273, in DataFrame.__repr__(self)
    271 num_rows = pandas.get_option("display.max_rows") or len(self.index)
    272 num_cols = pandas.get_option("display.max_columns") or len(self.columns)
--> 273 result = repr(self._build_repr_df(num_rows, num_cols))
    274 if len(self.index) > num_rows or len(self.columns) > num_cols:
    275     # The split here is so that we don't repr pandas row lengths.
    276     return result.rsplit("\n\n", 1)[0] + "\n\n[{0} rows x {1} columns]".format(
    277         len(self.index), len(self.columns)
    278     )

File ~/sources/modin/modin/logging/logger_decorator.py:144, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    129 """
    130 Compute function with logging if Modin logging is enabled.
    131
   (...)
    141 Any
    142 """
    143 if LogMode.get() == "disable":
--> 144     return obj(*args, **kwargs)
    146 logger = get_logger()
    147 logger.log(log_level, start_line)

File ~/sources/modin/modin/pandas/base.py:276, in BasePandasDataset._build_repr_df(self, num_rows, num_cols)
    254 """
    255 Build pandas DataFrame for string representation.
    256
   (...)
    273     A pandas dataset with `num_rows` or fewer rows and `num_cols` or fewer columns.
    274 """
    275 # Fast track for empty dataframe.
--> 276 if len(self.index) == 0 or (self._is_dataframe and len(self.columns) == 0):
    277     return pandas.DataFrame(
    278         index=self.index,
    279         columns=self.columns if self._is_dataframe else None,
    280     )
    281 row_indexer = _get_repr_axis_label_indexer(self.index, num_rows)

File ~/sources/modin/modin/pandas/base.py:4294, in BasePandasDataset.__getattribute__(self, item)
   4280 @disable_logging
   4281 def __getattribute__(self, item) -> Any:
   4282     """
   4283     Return item from the `BasePandasDataset`.
   4284
   (...)
   4292     Any
   4293     """
-> 4294     attr = super().__getattribute__(item)
   4295     if item not in _DEFAULT_BEHAVIOUR and not self._query_compiler.lazy_execution:
   4296         # We default to pandas on empty DataFrames. This avoids a large amount of
   4297         # pain in underlying implementation and returns a result immediately rather
   4298         # than dealing with the edge cases that empty DataFrames have.
   4299         if callable(attr) and self.empty and hasattr(self._pandas_class, item):

File ~/sources/modin/modin/pandas/base.py:643, in BasePandasDataset._get_index(self)
    634 def _get_index(self) -> pandas.Index:
    635     """
    636     Get the index for this DataFrame.
    637
   (...)
    641         The union of all indexes across the partitions.
    642     """
--> 643     return self._query_compiler.index

File ~/sources/modin/modin/core/storage_formats/pandas/query_compiler.py:102, in _get_axis.<locals>.<lambda>(self)
     89 """
     90 Build index labels getter of the specified axis.
     91
   (...)
     99 callable(PandasQueryCompiler) -> pandas.Index
    100 """
    101 if axis == 0:
--> 102     return lambda self: self._modin_frame.index
    103 else:
    104     return lambda self: self._modin_frame.columns

File ~/sources/modin/modin/core/dataframe/pandas/dataframe/dataframe.py:709, in PandasDataframe._get_index(self)
    700 """
    701 Get the index from the cache object.
    702
   (...)
    706     An index object containing the row labels.
    707 """
    708 if self.has_index_cache:
--> 709     index, row_lengths = self._index_cache.get(return_lengths=True)
    710 else:
    711     index, row_lengths = self._compute_axis_labels_and_lengths(0)

File ~/sources/modin/modin/core/dataframe/pandas/metadata/index.py:194, in ModinIndex.get(self, return_lengths)
    192 if not self.is_materialized:
    193     if callable(self._value):
--> 194         index, self._lengths_cache = self._value()
    195         self._value = ensure_index(index)
    196     elif self._value is None:

File ~/sources/modin/modin/core/dataframe/pandas/metadata/index.py:106, in ModinIndex._get_default_callable.<locals>.<lambda>()
     91 @staticmethod
     92 def _get_default_callable(dataframe_obj, axis):
     93     """
     94     Build a callable extracting index labels and partitions lengths for the specified axis.
     95
   (...)
    104     callable() -> tuple(pandas.Index, list[ints])
    105     """
--> 106     return lambda: dataframe_obj._compute_axis_labels_and_lengths(axis)

File ~/sources/modin/modin/logging/logger_decorator.py:144, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    129 """
    130 Compute function with logging if Modin logging is enabled.
    131
   (...)
    141 Any
    142 """
    143 if LogMode.get() == "disable":
--> 144     return obj(*args, **kwargs)
    146 logger = get_logger()
    147 logger.log(log_level, start_line)

File ~/sources/modin/modin/core/dataframe/pandas/dataframe/dataframe.py:835, in PandasDataframe._compute_axis_labels_and_lengths(self, axis, partitions)
    833 if partitions is None:
    834     partitions = self._partitions
--> 835 new_index, internal_idx = self._partition_mgr_cls.get_indices(axis, partitions)
    836 return new_index, list(map(len, internal_idx))

File ~/sources/modin/modin/logging/logger_decorator.py:144, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    129 """
    130 Compute function with logging if Modin logging is enabled.
    131
   (...)
    141 Any
    142 """
    143 if LogMode.get() == "disable":
--> 144     return obj(*args, **kwargs)
    146 logger = get_logger()
    147 logger.log(log_level, start_line)

File ~/sources/modin/modin/core/dataframe/pandas/partitioning/partition_manager.py:1193, in PandasDataframePartitionManager.get_indices(cls, axis, partitions, index_func)
   1191 if len(target):
   1192     new_idx = [idx.apply(func) for idx in target[0]]
-> 1193     new_idx = cls.get_objects_from_partitions(new_idx)
   1194 else:
   1195     new_idx = [pandas.Index([])]

File ~/sources/modin/modin/logging/logger_decorator.py:144, in enable_logging.<locals>.decorator.<locals>.run_and_log(*args, **kwargs)
    129 """
    130 Compute function with logging if Modin logging is enabled.
    131
   (...)
    141 Any
    142 """
    143 if LogMode.get() == "disable":
--> 144     return obj(*args, **kwargs)
    146 logger = get_logger()
    147 logger.log(log_level, start_line)

File ~/sources/modin/modin/core/dataframe/pandas/partitioning/partition_manager.py:1134, in PandasDataframePartitionManager.get_objects_from_partitions(cls, partitions)
   1130             partitions[idx] = part.force_materialization()
   1131     assert all(
   1132         [len(partition.list_of_blocks) == 1 for partition in partitions]
   1133     ), "Implementation assumes that each partition contains a single block."
-> 1134     return cls._execution_wrapper.materialize(
   1135         [partition.list_of_blocks[0] for partition in partitions]
   1136     )
   1137 return [partition.get() for partition in partitions]

File ~/sources/modin/modin/core/execution/ray/common/engine_wrapper.py:139, in RayWrapper.materialize(cls, obj_id)
    136     return ray.get(obj_id) if isinstance(obj_id, ray.ObjectRef) else obj_id
    138 if all(isinstance(obj, ray.ObjectRef) for obj in obj_id):
--> 139     return ray.get(obj_id)
    141 ids = {}
    142 result = []

File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/ray/_private/auto_init_hook.py:24, in wrap_auto_init.<locals>.auto_init_wrapper(*args, **kwargs)
     21 @wraps(fn)
     22 def auto_init_wrapper(*args, **kwargs):
     23     auto_init_ray()
---> 24     return fn(*args, **kwargs)

File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/ray/_private/client_mode_hook.py:103, in client_mode_hook.<locals>.wrapper(*args, **kwargs)
    101     if func.__name__ != "init" or is_client_mode_enabled_by_default:
    102         return getattr(ray, func.__name__)(*args, **kwargs)
--> 103 return func(*args, **kwargs)

File ~/miniconda3/envs/modin-latest/lib/python3.9/site-packages/ray/_private/worker.py:2563, in get(object_refs, timeout)
   2561     worker.core_worker.dump_object_store_memory_usage()
   2562 if isinstance(value, RayTaskError):
-> 2563     raise value.as_instanceof_cause()
   2564 else:
   2565     raise value

RayTaskError(ValueError): ray::remote_exec_func() (pid=58063, ip=127.0.0.1)
  At least one of the input arguments for this task could not be computed:
ray.exceptions.RayTaskError: ray::_deploy_ray_func() (pid=58063, ip=127.0.0.1)
  File "/Users/mvashishtha/sources/modin/modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py", line 335, in _deploy_ray_func
    result = deployer(axis, f_to_deploy, f_args, f_kwargs, *deploy_args, **kwargs)
  File "/Users/mvashishtha/sources/modin/modin/logging/logger_decorator.py", line 144, in run_and_log
    return obj(*args, **kwargs)
  File "/Users/mvashishtha/sources/modin/modin/core/dataframe/pandas/partitioning/axis_partition.py", line 575, in deploy_func_between_two_axis_partitions
    result = func(lt_frame, rt_frame, *f_args, **f_kwargs)
  File "/Users/mvashishtha/sources/modin/modin/core/dataframe/pandas/dataframe/dataframe.py", line 2078, in _tree_reduce_func
    series_result = func(df, *args, **kwargs)
  File "/Users/mvashishtha/sources/modin/modin/core/storage_formats/pandas/query_compiler.py", line 4663, in <lambda>
    lambda left, right: pandas.DataFrame.compare(
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/frame.py", line 8580, in compare
    return super().compare(
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/generic.py", line 10118, in compare
    mask = ~((self == other) | (self.isna() & other.isna()))
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/ops/common.py", line 76, in new_method
    return method(self, other)
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/arraylike.py", line 40, in __eq__
    return self._cmp_method(other, operator.eq)
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/frame.py", line 7884, in _cmp_method
    self, other = self._align_for_op(other, axis, flex=False, level=None)
  File "/Users/mvashishtha/miniconda3/envs/modin-latest/lib/python3.9/site-packages/pandas/core/frame.py", line 8183, in _align_for_op
    raise ValueError(
ValueError: Can only compare identically-labeled (both index and columns) DataFrame objects

Installed Versions

INSTALLED VERSIONS
------------------
commit                : 759d548814a6ac224e83e7531cf98e20b13d85cb
python                : 3.9.18.final.0
python-bits           : 64
OS                    : Darwin
OS-release            : 23.5.0
Version               : Darwin Kernel Version 23.5.0: Wed May  1 20:14:38 PDT 2024; root:xnu-10063.121.3~5/RELEASE_ARM64_T6020
machine               : arm64
processor             : arm
byteorder             : little
LC_ALL                : None
LANG                  : en_US.UTF-8
LOCALE                : en_US.UTF-8

Modin dependencies
------------------
modin                 : 0.31.0+2.g759d5488
ray                   : 2.8.0
dask                  : 2024.3.1
distributed           : 2024.3.1

pandas dependencies
-------------------
pandas                : 2.2.1
numpy                 : 1.26.1
pytz                  : 2023.3.post1
dateutil              : 2.8.2
setuptools            : 68.0.0
pip                   : 23.3
Cython                : None
pytest                : 8.1.1
hypothesis            : None
sphinx                : 7.2.6
blosc                 : None
feather               : None
xlsxwriter            : None
lxml.etree            : 5.1.0
html5lib              : None
pymysql               : None
psycopg2              : 2.9.9
jinja2                : 3.1.2
IPython               : 8.17.2
pandas_datareader     : None
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : 4.12.3
bottleneck            : None
dataframe-api-compat  : None
fastparquet           : 2024.2.0
fsspec                : 2024.3.1
gcsfs                 : None
matplotlib            : 3.8.1
numba                 : None
numexpr               : 2.8.4
odfpy                 : None
openpyxl              : 3.1.2
pandas_gbq            : 0.22.0
pyarrow               : 14.0.1
pyreadstat            : None
python-calamine       : None
pyxlsb                : None
s3fs                  : 2024.3.1
scipy                 : 1.11.3
sqlalchemy            : 2.0.29
tables                : 3.9.2
tabulate              : 0.9.0
xarray                : 2024.2.0
xlrd                  : 2.0.1
zstandard             : None
tzdata                : 2023.3
qtpy                  : None
pyqt5                 : None

[sfc-gh-mvashishtha]

We should probably combine the fix for this issue with the fix for #5699.