# Buggy code
def __getitem__(self, key):
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    if isinstance(row_loc, slice) and row_loc == slice(None):
        # If we're only slicing columns, handle the case with `__getitem__`
        if not isinstance(col_loc, slice):
            # Boolean indexers can just be sliced into the columns object and
            # then passed to `__getitem__`
            if is_boolean_array(col_loc):
                col_loc = self.df.columns[col_loc]
            return self.df.__getitem__(col_loc)
        else:
            result_slice = self.df.columns.slice_locs(col_loc.start, col_loc.stop)
            return self.df.iloc[:, slice(*result_slice)]

    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    if any(i == -1 for i in row_lookup) or any(i == -1 for i in col_lookup):
        raise KeyError(
            "Passing list-likes to .loc or [] with any missing labels is no longer "
            "supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"
        )
    result = super(_LocIndexer, self).__getitem__(row_lookup, col_lookup, ndim)
    # Pandas drops the levels that are in the `loc`, so we have to as well.
    if hasattr(result, "index") and isinstance(result.index, pandas.MultiIndex):
        if (
            isinstance(result, Series)
            and not isinstance(col_loc, slice)
            and all(col_loc[i] in result.index.levels[i] for i in range(len(col_loc)))
        ):
            result.index = result.index.droplevel(list(range(len(col_loc))))
        elif all(row_loc[i] in result.index.levels[i] for i in range(len(row_loc))):
            result.index = result.index.droplevel(list(range(len(row_loc))))
    if (
        hasattr(result, "columns")
        and isinstance(result.columns, pandas.MultiIndex)
        and all(col_loc[i] in result.columns.levels[i] for i in range(len(col_loc)))
    ):
        result.columns = result.columns.droplevel(list(range(len(col_loc))))
    return result


# Traceback (TypeError)
TypeError                                 Traceback (most recent call last)
<ipython-input-2-ad6eab4f4683> in <module>()
4              np.array(['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two'])]
5 df = pd.DataFrame(np.random.randn(8, 4), index=arrays).T
----> 6 df.loc[df.index>2,:]

/usr/local/lib/python3.6/dist-packages/modin/pandas/indexing.py in __getitem__(self, key)
249             hasattr(result, "columns")
250             and isinstance(result.columns, pandas.MultiIndex)
--> 251             and all(col_loc[i] in result.columns.levels[i] for i in range(len(col_loc)))
252         ):
253             result.columns = result.columns.droplevel(list(range(len(col_loc))))

TypeError: object of type 'slice' has no len()

# Fixed code
def __getitem__(self, key):
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    if isinstance(row_loc, slice) and row_loc == slice(None):
        # If we're only slicing columns, handle the case with `__getitem__`
        if not isinstance(col_loc, slice):
            # Boolean indexers can just be sliced into the columns object and
            # then passed to `__getitem__`
            if is_boolean_array(col_loc):
                col_loc = self.df.columns[col_loc]
            return self.df.__getitem__(col_loc)
        else:
            result_slice = self.df.columns.slice_locs(col_loc.start, col_loc.stop)
            return self.df.iloc[:, slice(*result_slice)]

    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    if any(i == -1 for i in row_lookup) or any(i == -1 for i in col_lookup):
        raise KeyError(
            "Passing list-likes to .loc or [] with any missing labels is no longer "
            "supported, see https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#deprecate-loc-reindex-listlike"
        )
    result = super(_LocIndexer, self).__getitem__(row_lookup, col_lookup, ndim)
    # Pandas drops the levels that are in the `loc`, so we have to as well.
    if hasattr(result, "index") and isinstance(result.index, pandas.MultiIndex):
        if (
            isinstance(result, Series)
            and not isinstance(col_loc, slice)
            and all(col_loc[i] in result.index.levels[i] for i in range(len(col_loc)))
        ):
            result.index = result.index.droplevel(list(range(len(col_loc))))
        elif all(row_loc[i] in result.index.levels[i] for i in range(len(row_loc))):
            result.index = result.index.droplevel(list(range(len(row_loc))))
    if (
        hasattr(result, "columns")
        and not isinstance(col_loc, slice)
        and isinstance(result.columns, pandas.MultiIndex)
        and all(col_loc[i] in result.columns.levels[i] for i in range(len(col_loc)))
    ):
        result.columns = result.columns.droplevel(list(range(len(col_loc))))
    return result