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LeetCode SQL 50 Solution/626. Exchange Seats/readme.md

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+Below is the structured README.md snippet for **LeetCode 626: Exchange Seats**, including the problem statement, example, SQL and Pandas solutions, file structure, and useful links.
+
+---
+
+# **626. Exchange Seats**
+
+## **Problem Statement**
+You are given a table `Seat` that contains the seat IDs and names of students. The seat IDs are assigned consecutively starting from 1.
+
+### **Seat Table**
+```
++-------------+---------+
+| Column Name | Type    |
++-------------+---------+
+| id          | int     |
+| student     | varchar |
++-------------+---------+
+```
+- `id` is the **primary key** (unique value).
+- Each row represents a student and their assigned seat.
+- The `id` sequence always starts from 1 and increments continuously.
+
+### **Task:**
+Swap the seat `id` of every two consecutive students.  
+- If the number of students is odd, the `id` of the last student remains unchanged.
+- Return the result table ordered by `id` in ascending order.
+
+---
+
+## **Example 1:**
+
+### **Input:**
+```
+Seat table:
++----+---------+
+| id | student |
++----+---------+
+| 1  | Abbot   |
+| 2  | Doris   |
+| 3  | Emerson |
+| 4  | Green   |
+| 5  | Jeames  |
++----+---------+
+```
+
+### **Output:**
+```
++----+---------+
+| id | student |
++----+---------+
+| 1  | Doris   |
+| 2  | Abbot   |
+| 3  | Green   |
+| 4  | Emerson |
+| 5  | Jeames  |
++----+---------+
+```
+
+### **Explanation:**
+- Swap the seat assignments of every two consecutive students:
+  - Seats 1 and 2: **Abbot** and **Doris** swap positions.
+  - Seats 3 and 4: **Emerson** and **Green** swap positions.
+  - Since the number of students is odd, **Jeames** (seat 5) remains in the same seat.
+
+---
+
+## **Solution Approaches**
+
+### **SQL Solution**
+```sql
+SELECT 
+    CASE 
+        WHEN id % 2 != 0 AND id != counts THEN id + 1
+        WHEN id % 2 != 0 AND id = counts THEN id
+        ELSE id - 1
+    END AS id, 
+    student
+FROM Seat, (SELECT COUNT(*) AS counts FROM Seat) AS seat_counts
+ORDER BY id ASC;
+```
+**Explanation:**
+- The subquery `(SELECT COUNT(*) AS counts FROM Seat)` computes the total number of students.
+- The `CASE` statement swaps IDs:
+  - For odd `id` (except the last one if the count is odd), we add 1.
+  - For even `id`, we subtract 1.
+  - For the last student in an odd-length list, we leave the `id` unchanged.
+- The results are then ordered by the new `id` in ascending order.
+
+---
+
+### **Pandas Solution**
+```python
+import pandas as pd
+
+def exchange_seats(seat: pd.DataFrame) -> pd.DataFrame:
+    # Total number of students
+    total = seat.shape[0]
+    
+    # Function to compute the new seat id
+    def new_id(row):
+        # For odd id values:
+        if row['id'] % 2 != 0:
+            # If it's the last row in an odd-length list, do not change the id.
+            if row['id'] == total:
+                return row['id']
+            else:
+                return row['id'] + 1
+        # For even id values, swap with previous odd id
+        else:
+            return row['id'] - 1
+    
+    # Apply the new_id function to each row
+    seat['new_id'] = seat.apply(new_id, axis=1)
+    
+    # Sort by the new seat id and select the desired columns
+    result = seat.sort_values('new_id')[['new_id', 'student']].rename(columns={'new_id': 'id'})
+    
+    return result.reset_index(drop=True)
+
+# Example usage:
+# data = {'id': [1, 2, 3, 4, 5], 'student': ['Abbot', 'Doris', 'Emerson', 'Green', 'Jeames']}
+# df = pd.DataFrame(data)
+# print(exchange_seats(df))
+```
+**Explanation:**
+- The solution calculates the total number of rows.
+- A helper function `new_id` computes the new seat id:
+  - For odd `id`s (except the last one), add 1.
+  - For even `id`s, subtract 1.
+  - Leave the last seat unchanged if the count is odd.
+- The DataFrame is sorted by the new `id`, and the result is returned.
+
+---
+
+## **File Structure**
+```
+LeetCode626/
+├── problem_statement.md       # Contains the problem description and constraints.
+├── sql_solution.sql           # Contains the SQL solution.
+├── pandas_solution.py         # Contains the Pandas solution.
+├── README.md                  # Overview of the problem and available solutions.
+```
+
+---
+
+## **Useful Links**
+- [LeetCode Problem 626](https://leetcode.com/problems/exchange-seats/)
+- [SQL CASE Statement Documentation](https://www.w3schools.com/sql/sql_case.asp)
+- [Pandas apply() Documentation](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.apply.html)
+- [Pandas DataFrame Sorting](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html)
+
+---
+
+This structured format provides a comprehensive overview of the problem along with multiple solution approaches. Happy coding! 🚀