Update prosnal_database.py

Author: iamAntimPal

LeetCode SQL 50 Solution/prosnal_database/prosnal_database.py

@@ -0,0 +1,141 @@
+Below is a complete Python solution using a class with methods to solve the problem with Pandas. This code creates the data (mimicking the SQL tables), then provides methods to run each query.
+
+```python
+import pandas as pd
+
+class ProsnalDatabase:
+    def __init__(self):
+        # Create tables (as Pandas DataFrames)
+        self.create_tables()
+
+    def create_tables(self):
+        # Employees Table
+        self.employees = pd.DataFrame({
+            'Id': [1, 2, 3, 4, 5],
+            'Name': ['John Doe', 'Jane Smith', 'Mike Johnson', 'Sarah Black', 'David White'],
+            'Salary': [50000, 60000, 70000, 60000, 70000],
+            'Department': ['HR', 'Finance', 'IT', 'Finance', 'IT']
+        })
+
+        # Projects Table
+        self.projects = pd.DataFrame({
+            'Id': [1, 2, 3],
+            'Name': ['Project A', 'Project B', 'Project C'],
+            'Department': ['IT', 'Finance', 'IT']
+        })
+
+        # EmployeeProjects Table
+        self.employee_projects = pd.DataFrame({
+            'EmployeeId': [1, 1, 2, 3, 3, 4, 5],
+            'ProjectId': [1, 2, 1, 1, 3, 2, 1]
+        })
+
+        # Users Table
+        self.users = pd.DataFrame({
+            'id': [1, 2],
+            'name': ['John Doe', 'Jane Smith'],
+            'email': ['[email protected]', '[email protected]']
+        })
+
+        # Sessions Table
+        self.sessions = pd.DataFrame({
+            'id': [1, 2, 3],
+            'user_id': [1, 1, 2],
+            'session_date': pd.to_datetime(['2022-01-01', '2022-01-02', '2022-01-03'])
+        })
+
+        # Products Table
+        self.products = pd.DataFrame({
+            'id': [1, 2, 3],
+            'name': ['Product A', 'Product B', 'Product C'],
+            'price': [10.99, 20.99, 30.99]
+        })
+
+        # Orders Table
+        self.orders = pd.DataFrame({
+            'id': [1, 2, 3, 4, 5],
+            'product_id': [1, 2, 3, 1, 2],
+            'quantity': [5, 3, 1, 2, 4]
+        })
+
+    def query_employee_projects(self):
+        """
+        Returns a DataFrame that lists each employee's project details.
+        This joins the Employees, EmployeeProjects, and Projects DataFrames.
+        """
+        # Merge Employees with EmployeeProjects
+        emp_proj = self.employees.merge(
+            self.employee_projects, left_on='Id', right_on='EmployeeId'
+        )
+        # Merge with Projects to get project details
+        emp_proj = emp_proj.merge(
+            self.projects, left_on='ProjectId', right_on='Id', suffixes=('_Employee', '_Project')
+        )
+        # Select and rename desired columns
+        result = emp_proj[['Name_Employee', 'Department_Employee', 'Name_Project', 'Department_Project']]
+        result = result.rename(columns={
+            'Name_Employee': 'EmployeeName',
+            'Department_Employee': 'EmployeeDepartment',
+            'Name_Project': 'ProjectName',
+            'Department_Project': 'ProjectDepartment'
+        })
+        return result
+
+    def query_user_sessions(self):
+        """
+        Returns a DataFrame that lists the session dates for each user.
+        This joins the Users and Sessions DataFrames.
+        """
+        user_sessions = self.users.merge(
+            self.sessions, left_on='id', right_on='user_id'
+        )
+        result = user_sessions[['name', 'session_date']].rename(columns={'name': 'user_name'})
+        return result
+
+    def query_order_totals(self):
+        """
+        Returns a DataFrame that calculates the total price for each order.
+        This joins the Products and Orders DataFrames and computes total price = price * quantity.
+        """
+        orders_merged = self.orders.merge(
+            self.products, left_on='product_id', right_on='id'
+        )
+        orders_merged['total_price'] = orders_merged['price'] * orders_merged['quantity']
+        result = orders_merged[['name', 'quantity', 'total_price']].rename(columns={'name': 'product_name'})
+        return result
+
+# Example usage:
+if __name__ == '__main__':
+    db = ProsnalDatabase()
+    
+    print("Employee Projects:")
+    print(db.query_employee_projects(), "\n")
+    
+    print("User Sessions:")
+    print(db.query_user_sessions(), "\n")
+    
+    print("Order Totals:")
+    print(db.query_order_totals())
+```
+
+### Explanation:
+- **Class Initialization (`__init__`)**:  
+  The `ProsnalDatabase` class initializes by calling `create_tables()`, which creates sample DataFrames for all tables.
+  
+- **`create_tables()`**:  
+  This method creates DataFrames for `Employees`, `Projects`, `EmployeeProjects`, `Users`, `Sessions`, `Products`, and `Orders` with sample data.
+  
+- **Query Methods**:
+  - **`query_employee_projects()`**:  
+    Merges the `employees`, `employee_projects`, and `projects` DataFrames to show which employee works on which project. Columns are renamed for clarity.
+    
+  - **`query_user_sessions()`**:  
+    Merges the `users` and `sessions` DataFrames to list session dates for each user.
+    
+  - **`query_order_totals()`**:  
+    Merges the `orders` DataFrame with the `products` DataFrame and calculates the total price for each order.
+
+- **Main Block**:  
+  An instance of `ProsnalDatabase` is created, and the query methods are executed to display results.
+
+This modular, class-based approach using Pandas helps encapsulate data and query logic in a single, easy-to-manage unit. Let me know if you need any further modifications!