def fast_xs(self, loc):
if len(self.blocks) == <NUM_LIT:1>:<EOL><INDENT>return self.blocks[<NUM_LIT:0>].iget((slice(None), loc))<EOL><DEDENT>items = self.items<EOL>if not items.is_unique:<EOL><INDENT>result = self._interleave()<EOL>if self.ndim == <NUM_LIT:2>:<EOL><INDENT>result = result.T<EOL><DEDENT>return result[loc]<EOL><DEDENT>dtype = _interleaved_dtype(self.blocks)<EOL>n = len(items)<EOL>if is_extension_array_dtype(dtype):<EOL><INDENT>result = np.empty(n, dtype=object)<EOL><DEDENT>else:<EOL><INDENT>result = np.empty(n, dtype=dtype)<EOL><DEDENT>for blk in self.blocks:<EOL><INDENT>for i, rl in enumerate(blk.mgr_locs):<EOL><INDENT>result[rl] = blk._try_coerce_result(blk.iget((i, loc)))<EOL><DEDENT><DEDENT>if is_extension_array_dtype(dtype):<EOL><INDENT>result = dtype.construct_array_type()._from_sequence(<EOL>result, dtype=dtype<EOL>)<EOL><DEDENT>return result<EOL>
get a cross sectional for a given location in the
items ; handle dups

return the result, is *could* be a view in the case of a
single block