pandas || xor, with explanation || T/S: 98% / 97%
Here\'s the plan:\n\n- We convert the two series employees.employee_idand salaries.employee_id to sets.\n\n- The employees with missing information are exactly 
Here\'s the plan:\n\n- We convert the two series `employees.employee_id`and `salaries.employee_id` to sets.\n\n- The employees with missing information are exactly those in one set but not both. Thus, we take the `xor` of the two sets, convert that set to a sorted list, and return that set in a frame.\n```\nimport pandas as pd\n\ndef find_employees(employees: pd.DataFrame, salaries: pd.DataFrame) -> pd.DataFrame:\n\n    return pd.DataFrame({\'employee_id\':sorted(set(employees.employee_id) ^\n                                              set(salaries .employee_id))})\n```\n[https://leetcode.com/problems/employees-with-missing-information/submissions/1084180417/](http://)\n\nPython 3 || xor, with explanation || T/S: 98% / 97%\n\nI could be wrong, but I think that time complexity is *O*(*N*) and space complexity is *O*(*N*), in which *N* ~ the greater of the number of rows in the two given frames.
['Pandas']