# Buggy code
def __getattribute__(self, item):
    default_behaviors = [
        "__init__",
        "series",
        "parent_df",
        "_loc",
        "__arithmetic_op__",
        "__comparisons__",
        "__class__",
    ]
    if item not in default_behaviors:
        method = self.series.__getattribute__(item)
        # Certain operations like `at`, `loc`, `iloc`, etc. are callable because in
        # pandas they are equivalent to classes. They are verified here because they
        # cannot be overridden with the functions below. This generally solves the
        # problem where the instance property is callable, but the class property is
        # not.
        # The isclass check is to ensure that we return the correct type. Some of
        # the objects that are called result in classes being returned, and we don't
        # want to override with our own function.
        is_callable = (
            callable(method)
            and callable(getattr(type(self.series), item))
            and not inspect.isclass(getattr(type(self.series), item))
        )
        try:
            has_inplace_param = is_callable and "inplace" in str(
                inspect.signature(method)
            )
        # This will occur on Python2
        except AttributeError:
            has_inplace_param = is_callable and "inplace" in str(
                inspect.getargspec(method)
            )

        if is_callable and has_inplace_param and self.parent_df is not None:

            def inplace_handler(*args, **kwargs):
                """Replaces the default behavior of methods with inplace kwarg.

                Note: This method will modify the DataFrame this Series is attached
                    to when `inplace` is True. Instead of rewriting or overriding
                    every method that uses `inplace`, we use this handler.

                    This handler will first check that the keyword argument passed
                    for `inplace` is True, if not then it will just return the
                    result of the operation requested.

                    If `inplace` is True, do the operation, keeping track of the
                    previous length. This is because operations like `dropna` still
                    propagate back to the DataFrame that holds the Series.

                    If the length did not change, we propagate the inplace changes
                    of the operation back to the original DataFrame with
                    `__setitem__`.

                    If the length changed, we just need to do a `reindex` on the
                    parent DataFrame. This will propagate the inplace operation
                    (e.g. `dropna`) back to the parent DataFrame.

                    See notes in SeriesView class about when it is okay to return a
                    pandas Series vs a SeriesView.

                Returns:
                    If `inplace` is True: None, else: A new Series.
                """
                if kwargs.get("inplace", False):
                    prev_len = len(self.series)
                    self.series.__getattribute__(item)(*args, **kwargs)
                    if prev_len == len(self.series):
                        self.parent_df.loc[self._loc] = self.series
                    else:
                        self.parent_df.reindex(index=self.series.index, copy=False)
                    return None
                else:
                    return self.series.__getattribute__(item)(*args, **kwargs)

            # We replace the method with `inplace_handler` for inplace operations
            method = inplace_handler
        elif is_callable:

            def other_handler(*args, **kwargs):
                """Replaces the method's args and kwargs with the Series object.

                Note: This method is needed because sometimes operations like
                    `df['col0'].equals(df['col1'])` do not return the correct value.
                    This mostly has occurred in Python2, but overriding of the
                    method will make the behavior more deterministic for all calls.

                Returns the result of `__getattribute__` from the Series this wraps.
                """
                args = tuple(
                    arg if not isinstance(arg, SeriesView) else arg.series
                    for arg in args
                )
                kwargs = {
                    kw: arg if not isinstance(arg, SeriesView) else arg.series
                    for kw, arg in kwargs.items()
                }
                return self.series.__getattribute__(item)(*args, **kwargs)

            method = other_handler
        return method
    # We need to do this hack for equality checking.
    elif item == "__class__":
        return self.series.__class__
    else:
        return object.__getattribute__(self, item)


# Traceback (TypeError)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-7-f7a945237ab9> in <module>()
3     header=[0,1,2,3], index_col=0)
4 DF2.loc[1]
----> 5 DF2.loc[1, 'Presidents']

~/anaconda3/lib/python3.7/site-packages/modin/pandas/indexing.py in __getitem__(self, key)
232         row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
233         ndim = self._expand_dim(row_lookup, col_lookup, ndim)
--> 234         result = super(_LocIndexer, self).__getitem__(row_lookup, col_lookup, ndim)
235         return result
236

~/anaconda3/lib/python3.7/site-packages/modin/pandas/indexing.py in __getitem__(self, row_lookup, col_lookup, ndim)
163             single_axis = 1 if self.col_scaler else 0
164             return SeriesView(
--> 165                 qc_view.squeeze(ndim=1, axis=single_axis),
166                 self.df,
167                 (row_lookup, col_lookup),

~/anaconda3/lib/python3.7/site-packages/modin/data_management/query_compiler/pandas_query_compiler.py in squeeze(self, ndim, axis)
2781             if axis is None:
2782                 axis = 0 if self.data.shape[1] > 1 else 1
-> 2783             squeezed = pandas.Series(to_squeeze.squeeze(axis))
2784             scaler_axis = self.columns if axis else self.index
2785             non_scaler_axis = self.index if axis else self.columns

~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
260             else:
261                 data = sanitize_array(data, index, dtype, copy,
--> 262                                       raise_cast_failure=True)
263
264                 data = SingleBlockManager(data, index, fastpath=True)

~/anaconda3/lib/python3.7/site-packages/pandas/core/internals/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
658             raise Exception('Data must be 1-dimensional')
659         else:
--> 660             subarr = com.asarray_tuplesafe(data, dtype=dtype)
661
662     # This is to prevent mixed-type Series getting all casted to

~/anaconda3/lib/python3.7/site-packages/pandas/core/common.py in asarray_tuplesafe(values, dtype)
238         # Avoid building an array of arrays:
239         # TODO: verify whether any path hits this except #18819 (invalid)
--> 240         values = [tuple(x) for x in values]
241         result = construct_1d_object_array_from_listlike(values)
242

~/anaconda3/lib/python3.7/site-packages/pandas/core/common.py in <listcomp>(.0)
238         # Avoid building an array of arrays:
239         # TODO: verify whether any path hits this except #18819 (invalid)
--> 240         values = [tuple(x) for x in values]
241         result = construct_1d_object_array_from_listlike(values)
242

TypeError: 'int' object is not iterable

# Fixed code
def __getattribute__(self, item):
    default_behaviors = [
        "__init__",
        "series",
        "parent_df",
        "_loc",
        "__arithmetic_op__",
        "__comparisons__",
        "__class__",
        "index",
        "_get_index",
        "_set_index",
    ]
    if item not in default_behaviors:
        method = self.series.__getattribute__(item)
        # Certain operations like `at`, `loc`, `iloc`, etc. are callable because in
        # pandas they are equivalent to classes. They are verified here because they
        # cannot be overridden with the functions below. This generally solves the
        # problem where the instance property is callable, but the class property is
        # not.
        # The isclass check is to ensure that we return the correct type. Some of
        # the objects that are called result in classes being returned, and we don't
        # want to override with our own function.
        is_callable = (
            callable(method)
            and callable(getattr(type(self.series), item))
            and not inspect.isclass(getattr(type(self.series), item))
        )
        try:
            has_inplace_param = is_callable and "inplace" in str(
                inspect.signature(method)
            )
        # This will occur on Python2
        except AttributeError:
            has_inplace_param = is_callable and "inplace" in str(
                inspect.getargspec(method)
            )

        if is_callable and has_inplace_param and self.parent_df is not None:

            def inplace_handler(*args, **kwargs):
                """Replaces the default behavior of methods with inplace kwarg.

                Note: This method will modify the DataFrame this Series is attached
                    to when `inplace` is True. Instead of rewriting or overriding
                    every method that uses `inplace`, we use this handler.

                    This handler will first check that the keyword argument passed
                    for `inplace` is True, if not then it will just return the
                    result of the operation requested.

                    If `inplace` is True, do the operation, keeping track of the
                    previous length. This is because operations like `dropna` still
                    propagate back to the DataFrame that holds the Series.

                    If the length did not change, we propagate the inplace changes
                    of the operation back to the original DataFrame with
                    `__setitem__`.

                    If the length changed, we just need to do a `reindex` on the
                    parent DataFrame. This will propagate the inplace operation
                    (e.g. `dropna`) back to the parent DataFrame.

                    See notes in SeriesView class about when it is okay to return a
                    pandas Series vs a SeriesView.

                Returns:
                    If `inplace` is True: None, else: A new Series.
                """
                if kwargs.get("inplace", False):
                    prev_len = len(self.series)
                    self.series.__getattribute__(item)(*args, **kwargs)
                    if prev_len == len(self.series):
                        self.parent_df.loc[self._loc] = self.series
                    else:
                        self.parent_df.reindex(index=self.series.index, copy=False)
                    return None
                else:
                    return self.series.__getattribute__(item)(*args, **kwargs)

            # We replace the method with `inplace_handler` for inplace operations
            method = inplace_handler
        elif is_callable:

            def other_handler(*args, **kwargs):
                """Replaces the method's args and kwargs with the Series object.

                Note: This method is needed because sometimes operations like
                    `df['col0'].equals(df['col1'])` do not return the correct value.
                    This mostly has occurred in Python2, but overriding of the
                    method will make the behavior more deterministic for all calls.

                Returns the result of `__getattribute__` from the Series this wraps.
                """
                args = tuple(
                    arg if not isinstance(arg, SeriesView) else arg.series
                    for arg in args
                )
                kwargs = {
                    kw: arg if not isinstance(arg, SeriesView) else arg.series
                    for kw, arg in kwargs.items()
                }
                return self.series.__getattribute__(item)(*args, **kwargs)

            method = other_handler
        return method
    # We need to do this hack for equality checking.
    elif item == "__class__":
        return self.series.__class__
    else:
        return object.__getattribute__(self, item)