# Buggy code
def __getitem__(self, key):
    # When getting along a single axis,
    if not isinstance(key, tuple):
        # Try to fasttrack the code through already optimized path
        try:
            return self.df.__getitem__(key)
        # This can happen if it is a list of rows
        except KeyError:
            pass
    else:
        if len(key) > self.df.ndim:
            raise IndexingError("Too many indexers")
        if isinstance(key[0], slice) and key[0] == slice(None):
            return self.df.__getitem__(key[1])
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    # Check that the row_lookup/col_lookup is longer than 1 or that the
    # row_loc/col_loc is not boolean list to determine the ndim of the
    # result properly for multiindex.
    ndim = (0 if len(row_lookup) == 1 and not is_boolean_array(row_loc) else 1) + (
        0 if len(col_lookup) == 1 and not is_boolean_array(col_loc) else 1
    )
    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)
In [4]: df.loc[:, "col0":"col3"]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-f1d9690a44cf> in <module>
----> 1 df.loc[:, "col0":"col3"]

~/software_builds/modin/modin/pandas/indexing.py in __getitem__(self, key)
213                 raise IndexingError("Too many indexers")
214             if isinstance(key[0], slice) and key[0] == slice(None):
--> 215                 return self.df.__getitem__(key[1])
216         row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
217         row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)

~/software_builds/modin/modin/pandas/base.py in __getitem__(self, key)
3284         # This lets us reuse code in Pandas to error check
3285         indexer = convert_to_index_sliceable(
-> 3286             getattr(pandas, self.__name__)(index=self.index), key
3287         )
3288         if indexer is not None:

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/indexing.py in convert_to_index_sliceable(obj, key)
2356     idx = obj.index
2357     if isinstance(key, slice):
-> 2358         return idx._convert_slice_indexer(key, kind="getitem")
2359
2360     elif isinstance(key, str):

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/indexes/base.py in _convert_slice_indexer(self, key, kind)
3188             if self.is_integer() or is_index_slice:
3189                 return slice(
-> 3190                     self._validate_indexer("slice", key.start, kind),
3191                     self._validate_indexer("slice", key.stop, kind),
3192                     self._validate_indexer("slice", key.step, kind),

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/indexes/base.py in _validate_indexer(self, form, key, kind)
5069             pass
5070         elif kind in ["iloc", "getitem"]:
-> 5071             self._invalid_indexer(form, key)
5072         return key
5073

/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/indexes/base.py in _invalid_indexer(self, form, key)
3338             "cannot do {form} indexing on {klass} with these "
3339             "indexers [{key}] of {kind}".format(
-> 3340                 form=form, klass=type(self), key=key, kind=type(key)
3341             )
3342         )

TypeError: cannot do slice indexing on <class 'pandas.core.indexes.range.RangeIndex'> with these indexers [col0] of <class 'str'>

# Fixed code
def __getitem__(self, key):
    # When getting along a single axis,
    if not isinstance(key, tuple):
        # Try to fasttrack the code through already optimized path
        try:
            return self.df.__getitem__(key)
        # This can happen if it is a list of rows
        except KeyError:
            pass
    else:
        if len(key) > self.df.ndim:
            raise IndexingError("Too many indexers")
        if isinstance(key[0], slice) and key[0] == slice(None):
            if not isinstance(key[1], slice):
                return self.df.__getitem__(key[1])
            else:
                result_slice = self.df.columns.slice_locs(key[1].start, key[1].stop)
                return self.df.iloc[:, slice(*result_slice)]
    row_loc, col_loc, ndim, self.row_scaler, self.col_scaler = _parse_tuple(key)
    row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc)
    # Check that the row_lookup/col_lookup is longer than 1 or that the
    # row_loc/col_loc is not boolean list to determine the ndim of the
    # result properly for multiindex.
    ndim = (0 if len(row_lookup) == 1 and not is_boolean_array(row_loc) else 1) + (
        0 if len(col_lookup) == 1 and not is_boolean_array(col_loc) else 1
    )
    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