# Buggy code
def _map(self, func, dtypes=None, validate_index=False, validate_columns=False):
    """Perform a function that maps across the entire dataset.

    Pamareters
    ----------
        func : callable
            The function to apply.
        dtypes :
            (optional) The data types for the result. This is an optimization
            because there are functions that always result in a particular data
            type, and allows us to avoid (re)computing it.
        validate_index : bool, (default False)
            Is index validation required after performing `func` on partitions.
    Returns
    -------
        A new dataframe.
    """
    new_partitions = self._frame_mgr_cls.lazy_map_partitions(self._partitions, func)
    if dtypes == "copy":
        dtypes = self._dtypes
    elif dtypes is not None:
        dtypes = pandas.Series(
            [np.dtype(dtypes)] * len(self.columns), index=self.columns
        )
    if validate_index:
        new_index = self._frame_mgr_cls.get_indices(
            0, new_partitions, lambda df: df.index
        )
    else:
        new_index = self.index
    if len(new_index) != len(self.index):
        new_row_lengths = None
    else:
        new_row_lengths = self._row_lengths

    if validate_columns:
        new_columns = self._frame_mgr_cls.get_indices(
            1, new_partitions, lambda df: df.columns
        )
    else:
        new_columns = self.columns
    if len(new_columns) != len(self.columns):
        new_column_widths = None
    else:
        new_column_widths = self._column_widths
    return self.__constructor__(
        new_partitions,
        new_index,
        new_columns,
        new_row_lengths,
        new_column_widths,
        dtypes=dtypes,
    )


# Traceback (Exception)
Traceback (most recent call last):
File "test.py", line 15, in <module>
print(f"modin:\n{modin_df.sum(min_count=1)}")
File "modin\pandas\base.py", line 3512, in __str__
return repr(self)
File "modin\pandas\series.py", line 307, in __repr__
temp_df = self._build_repr_df(num_rows, num_cols)
File "modin\pandas\base.py", line 108, in _build_repr_df
return self.iloc[indexer]._query_compiler.to_pandas()
File "modin\backends\pandas\query_compiler.py", line 191, in to_pandas
return self._modin_frame.to_pandas()
File "modin\engines\base\frame\data.py", line 1801, in to_pandas
"Internal and external indices do not match.",
File "modin\error_message.py", line 54, in catch_bugs_and_request_email
" caused this error.\n{}".format(extra_log)
Exception: Internal Error. Please email bug_reports@modin.org with the traceback and command that caused this error.
Internal and external indices do not match.

# Fixed code
def _map(self, func, dtypes=None, validate_index=False, validate_columns=False):
    """Perform a function that maps across the entire dataset.

    Pamareters
    ----------
        func : callable
            The function to apply.
        dtypes :
            (optional) The data types for the result. This is an optimization
            because there are functions that always result in a particular data
            type, and allows us to avoid (re)computing it.
        validate_index : bool, (default False)
            Is index validation required after performing `func` on partitions.
    Returns
    -------
        A new dataframe.
    """
    new_partitions = self._frame_mgr_cls.lazy_map_partitions(self._partitions, func)
    if dtypes == "copy":
        dtypes = self._dtypes
    elif dtypes is not None:
        dtypes = pandas.Series(
            [np.dtype(dtypes)] * len(self.columns), index=self.columns
        )

    axis_validate_mask = [validate_index, validate_columns]
    new_axes = [
        self._compute_axis_labels(axis, new_partitions)
        if should_validate
        else self.axes[axis]
        for axis, should_validate in enumerate(axis_validate_mask)
    ]

    new_lengths = [
        self._axes_lengths[axis]
        if len(new_axes[axis]) == len(self.axes[axis])
        else None
        for axis in [0, 1]
    ]

    return self.__constructor__(
        new_partitions,
        *new_axes,
        *new_lengths,
        dtypes=dtypes,
    )