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| 1 | +Here’s a well-structured `README.md` for **LeetCode 1378 - Replace Employee ID With The Unique Identifier**, formatted for a GitHub repository: |
| 2 | + |
| 3 | +```md |
| 4 | +# 🏢 Replace Employee ID With The Unique Identifier - LeetCode 1378 |
| 5 | + |
| 6 | +## 📌 Problem Statement |
| 7 | +You are given two tables: **Employees** and **EmployeeUNI**. |
| 8 | + |
| 9 | +Your task is to return a table with: |
| 10 | +- Each employee's **unique ID** if it exists. |
| 11 | +- If an employee **does not** have a unique ID, return `NULL`. |
| 12 | + |
| 13 | +The result can be returned in **any order**. |
| 14 | + |
| 15 | +--- |
| 16 | + |
| 17 | +## 📊 Table Structure |
| 18 | + |
| 19 | +### **Employees Table** |
| 20 | +| Column Name | Type | |
| 21 | +| ----------- | ------- | |
| 22 | +| id | int | |
| 23 | +| name | varchar | |
| 24 | + |
| 25 | +- `id` is the **primary key** (unique for each employee). |
| 26 | +- `name` is the **employee's name**. |
| 27 | + |
| 28 | +--- |
| 29 | + |
| 30 | +### **EmployeeUNI Table** |
| 31 | +| Column Name | Type | |
| 32 | +| ----------- | ---- | |
| 33 | +| id | int | |
| 34 | +| unique_id | int | |
| 35 | + |
| 36 | +- `(id, unique_id)` is the **primary key** (ensuring unique mapping of employee IDs to unique IDs). |
| 37 | +- Each employee **may or may not** have a corresponding **unique ID**. |
| 38 | + |
| 39 | +--- |
| 40 | + |
| 41 | +## 📊 Example 1: |
| 42 | +### **Input:** |
| 43 | +#### **Employees Table** |
| 44 | +| id | name | |
| 45 | +| --- | -------- | |
| 46 | +| 1 | Alice | |
| 47 | +| 7 | Bob | |
| 48 | +| 11 | Meir | |
| 49 | +| 90 | Winston | |
| 50 | +| 3 | Jonathan | |
| 51 | + |
| 52 | +#### **EmployeeUNI Table** |
| 53 | +| id | unique_id | |
| 54 | +| --- | --------- | |
| 55 | +| 3 | 1 | |
| 56 | +| 11 | 2 | |
| 57 | +| 90 | 3 | |
| 58 | + |
| 59 | +### **Output:** |
| 60 | +| unique_id | name | |
| 61 | +| --------- | -------- | |
| 62 | +| null | Alice | |
| 63 | +| null | Bob | |
| 64 | +| 2 | Meir | |
| 65 | +| 3 | Winston | |
| 66 | +| 1 | Jonathan | |
| 67 | + |
| 68 | +### **Explanation:** |
| 69 | +- `Alice` and `Bob` **do not have** a unique ID, so we return `NULL`. |
| 70 | +- The **unique ID** of `Meir` is **2**. |
| 71 | +- The **unique ID** of `Winston` is **3**. |
| 72 | +- The **unique ID** of `Jonathan` is **1**. |
| 73 | + |
| 74 | +--- |
| 75 | + |
| 76 | +## 🖥 SQL Solution |
| 77 | + |
| 78 | +### ✅ **Using `LEFT JOIN`** |
| 79 | +#### **Explanation:** |
| 80 | +- Use a **LEFT JOIN** to **include all employees**. |
| 81 | +- If an employee **does not have** a matching `unique_id`, return `NULL`. |
| 82 | + |
| 83 | +```sql |
| 84 | +SELECT eu.unique_id, e.name |
| 85 | +FROM Employees e |
| 86 | +LEFT JOIN EmployeeUNI eu |
| 87 | +ON e.id = eu.id; |
| 88 | +``` |
| 89 | + |
| 90 | +### ✅ **Using `USING(id)`** |
| 91 | +#### **Explanation:** |
| 92 | +- `USING(id)` is a cleaner alternative when both tables share a column. |
| 93 | + |
| 94 | +```sql |
| 95 | +SELECT unique_id, name |
| 96 | +FROM Employees |
| 97 | +LEFT JOIN EmployeeUNI |
| 98 | +USING (id); |
| 99 | +``` |
| 100 | + |
| 101 | +### ✅ **Sorting by `id` (Optional)** |
| 102 | +#### **Explanation:** |
| 103 | +- If you want to return the result **sorted by `id`**, add `ORDER BY e.id`: |
| 104 | + |
| 105 | +```sql |
| 106 | +SELECT eu.unique_id, e.name |
| 107 | +FROM Employees e |
| 108 | +LEFT JOIN EmployeeUNI eu |
| 109 | +ON e.id = eu.id |
| 110 | +ORDER BY e.id; |
| 111 | +``` |
| 112 | + |
| 113 | +--- |
| 114 | + |
| 115 | +## 🐍 Pandas Solution (Python) |
| 116 | +#### **Explanation:** |
| 117 | +- Merge `Employees` with `EmployeeUNI` **using `left` join** on `id`. |
| 118 | +- Fill missing values (`NaN`) with `None`. |
| 119 | + |
| 120 | +```python |
| 121 | +import pandas as pd |
| 122 | + |
| 123 | +def replace_employee_id(employees: pd.DataFrame, employee_uni: pd.DataFrame) -> pd.DataFrame: |
| 124 | + merged_df = employees.merge(employee_uni, on="id", how="left") |
| 125 | + return merged_df[["unique_id", "name"]] |
| 126 | +``` |
| 127 | + |
| 128 | +--- |
| 129 | + |
| 130 | +## 📁 File Structure |
| 131 | +``` |
| 132 | +📂 Replace-Employee-ID |
| 133 | +│── 📜 README.md |
| 134 | +│── 📜 solution.sql |
| 135 | +│── 📜 solution_pandas.py |
| 136 | +│── 📜 test_cases.sql |
| 137 | +``` |
| 138 | + |
| 139 | +--- |
| 140 | + |
| 141 | +## 🔗 Useful Links |
| 142 | +- 📖 [LeetCode Problem](https://leetcode.com/problems/replace-employee-id-with-the-unique-identifier/) |
| 143 | +- 📚 [SQL `LEFT JOIN`](https://www.w3schools.com/sql/sql_join_left.asp) |
| 144 | +- 🐍 [Pandas Merge Documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html) |
| 145 | +``` |
| 146 | + |
| 147 | +### Features of this `README.md`: |
| 148 | +✅ **Clear problem description with tables** |
| 149 | +✅ **Example with step-by-step explanation** |
| 150 | +✅ **SQL and Pandas solutions with detailed breakdowns** |
| 151 | +✅ **File structure for easy organization** |
| 152 | +✅ **Helpful references for further learning** |
| 153 | + |
| 154 | +Would you like any modifications? 🚀 |
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