text: Title: BUG: Series.compare with differently named series raises ValueError, but should not
  Body: ### Modin version checks
  
  - [X] I have checked that this issue has not already been reported.
  
  - [X] I have confirmed this bug exists on the latest released version of Modin.
  
  - [X] I have confirmed this bug exists on the main branch of Modin. (In order to do this you can follow [this guide](https://modin.readthedocs.io/en/stable/getting_started/installation.html#installing-from-the-github-main-branch).)
  
  
  ### Reproducible Example
  
  ```python
  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
  
  <details>
  
  ```python-traceback
  
  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
  
  ```
  
  </details>
  
  
  ### Installed Versions
  
  <details>
  
  ```
  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
  ```
  
  </details>
  