2-in-1 Adjustable Baby Gate & Play Yard with Bonus Kit

The Features That Matter

SUPERWIDE GATE: FLEXIBLE AND VERSATILE SIZER

• Dimensions: Opens up to 192 inches wide and stands 28 inches tall, perfect for wide spaces.

2-IN-1 PLAY YARD AND GATE

• 2-IN-1: Convert from a wide gate to an 8-panel play yard with no tools required. Quick and easy conversion for versatile use.

EASY INSTALLATION

• No Tools Needed: Easy to use with quick and simple installation. Includes 4 pack of wall mounts for secure setup.
• Convenient Wall Mounting Brackets: Adds 2 inches to each side for a total of 4 inches, ensuring a secure fit.

CONFIGURABLE AND ADAPTABLE

• Flexible Panels: Each panel can be adjusted to fit almost any opening – ideal for wide spaces, angled openings, hallways, doorways, and bottom of stairs.
• Folds Flat for Storage: Compact design when folded, making it convenient for storage.

EASY CLEANING

• Wipes Clean: Simple to clean and maintain for a hassle-free experience.

DURABLE AND USER-FRIENDLY

• All-Steel Construction: Durable and convenient with a walk-through door, ensuring long-lasting use.
• Walk-Through Door with Safety Locking Feature: Adds an extra layer of safety and security.

SAFETY FEATURES

• Wall-Mounted for Added Security: Includes wall mounted hardware for enhanced protection.
• Meets All Current Safety Standards: Designed for children up to 24 months and suitable for pets too.

SQL INSERT Statements:

1. Insert a new row into the "employees" table:

SQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('John', 'Doe', 'Sales', 70000)" MySQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('John', 'Doe', 'Sales', 70000)" Postgres: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('John', 'Doe', 'Sales', 70000)" Oracle: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('John', 'Doe', 'Sales', 70000)" Interchange: "0951" Python: "employees.append({'first_name': 'John', 'last_name': 'Doe', 'department': 'Sales', 'salary': 70000})" JSON: "{'first_name': 'John', 'last_name': 'Doe', 'department': 'Sales', 'salary': 70000}"

1. Insert multiple rows into the "employees" table:

SQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Jane', 'Smith', 'Marketing', 80000), ('Mike', 'Johnson', 'HR', 75000)" MySQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Jane', 'Smith', 'Marketing', 80000), ('Mike', 'Johnson', 'HR', 75000)" Postgres: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Jane', 'Smith', 'Marketing', 80000), ('Mike', 'Johnson', 'HR', 75000)" Oracle: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Jane', 'Smith', 'Marketing', 80000), ('Mike', 'Johnson', 'HR', 75000)" Interchange: "0952" Python: "new_employees = [{'first_name': 'Jane', 'last_name': 'Smith', 'department': 'Marketing', 'salary': 80000}, {'first_name': 'Mike', 'last_name': 'Johnson', 'department': 'HR', 'salary': 75000}]" JSON: "[{'first_name': 'Jane', 'last_name': 'Smith', 'department': 'Marketing', 'salary': 80000}, {'first_name': 'Mike', 'last_name': 'Johnson', 'department': 'HR', 'salary': 75000}]"

1. Insert a row into the "employees" table with a generated sequence value for the primary key:

SQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Alice', 'Brown', 'Engineering', 90000)" MySQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Alice', 'Brown', 'Engineering', 90000)" Postgres: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Alice', 'Brown', 'Engineering', 90000)" Oracle: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Alice', 'Brown', 'Engineering', 90000)" Interchange: "0953" Python: "employees.append({'first_name': 'Alice', 'last_name': 'Brown', 'department': 'Engineering', 'salary': 90000})" JSON: "{'first_name': 'Alice', 'last_name': 'Brown', 'department': 'Engineering', 'salary': 90000}"

1. Insert a row into the "employees" table with an explicit ID:

SQL: "INSERT INTO employees (id, first_name, last_name, department, salary) VALUES (4, 'Charlie', 'Green', 'Finance', 85000)" MySQL: "INSERT INTO employees (id, first_name, last_name, department, salary) VALUES (4, 'Charlie', 'Green', 'Finance', 85000)" Postgres: "INSERT INTO employees (id, first_name, last_name, department, salary) VALUES (4, 'Charlie', 'Green', 'Finance', 85000)" Oracle: "INSERT INTO employees (id, first_name, last_name, department, salary) VALUES (4, 'Charlie', 'Green', 'Finance', 85000)" Interchange: "0954" Python: "employees[3] = {'id': 4, 'first_name': 'Charlie', 'last_name': 'Green', 'department': 'Finance', 'salary': 85000}" JSON: "{'id': 4, 'first_name': 'Charlie', 'last_name': 'Green', 'department': 'Finance', 'salary': 85000}"

1. Insert a row into the "employees" table with auto-increment on the primary key:

SQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Dave', 'White', 'HR', 76000)" MySQL: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Dave', 'White', 'HR', 76000)" Postgres: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Dave', 'White', 'HR', 76000)" Oracle: "INSERT INTO employees (first_name, last_name, department, salary) VALUES ('Dave', 'White', 'HR', 76000)" Interchange: "0955" Python: "employees.append({'first_name': 'Dave', 'last_name': 'White', 'department': 'HR', 'salary': 76000})" JSON: "{'first_name': 'Dave', 'last_name': 'White', 'department': 'HR', 'salary': 76000}"

1. Insert a row into the "employees" table with additional attributes:

SQL: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (5, 'Ella', 'Black', 'Engineering', 92000, '2022-06-15')" MySQL: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (5, 'Ella', 'Black', 'Engineering', 92000, '2022-06-15')" Postgres: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (5, 'Ella', 'Black', 'Engineering', 92000, '2022-06-15')" Oracle: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (5, 'Ella', 'Black', 'Engineering', 92000, TO_DATE('2022-06-15', 'YYYY-MM-DD'))" Interchange: "0956" Python: "employees[4] = {'id': 5, 'first_name': 'Ella', 'last_name': 'Black', 'department': 'Engineering', 'salary': 92000, 'hire_date': '2022-06-15'}" JSON: "{'id': 5, 'first_name': 'Ella', 'last_name': 'Black', 'department': 'Engineering', 'salary': 92000, 'hire_date': '2022-06-15'}"

1. Insert a row into the "employees" table with values from a SELECT statement:

Interchange: "0957" Python: "new_employees = employees[employees['department'] == 'Engineering'][['first_name', 'last_name', 'department', 'salary']].to_dict('records')" JSON: "{'first_name': list, 'last_name': list, 'department': list, 'salary': list}"

1. Insert multiple rows into the "employees" table with values from a SELECT statement:

Interchange: "0958" Python: "new_employees = employees[employees['department'] == 'Sales'][['first_name', 'last_name', 'department', 'salary']].to_dict('records')" JSON: "{'first_name': list, 'last_name': list, 'department': list, 'salary': list}"

1. Insert a row into the "employees" table with values from a subquery:

Interchange: "0959" Python: "new_employees = employees[employees['department'] == 'Marketing'][['first_name', 'last_name']].to_dict('records')" JSON: "{'first_name': list, 'last_name': list}"

1. Insert a row into the "employees" table with values from a VALUES clause:

SQL: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (6, 'Frank', 'Gray', 'Engineering', 93000, '2022-07-20')" MySQL: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (6, 'Frank', 'Gray', 'Engineering', 93000, '2022-07-20')" Postgres: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (6, 'Frank', 'Gray', 'Engineering', 93000, '2022-07-20')" Oracle: "INSERT INTO employees (id, first_name, last_name, department, salary, hire_date) VALUES (6, 'Frank', 'Gray', 'Engineering', 93000, TO_DATE('2022-07-20', 'YYYY-MM-DD'))" Interchange: "0960" Python: "employees.append({'id': 6, 'first_name': 'Frank', 'last_name': 'Gray', 'department': 'Engineering', 'salary': 93000, 'hire_date': '2022-07-20'})" JSON: "{'id': 6, 'first_name': 'Frank', 'last_name': 'Gray', 'department': 'Engineering', 'salary': 93000, 'hire_date': '2022-07-20'}"

These examples cover a wide range of insertion scenarios and are adaptable to various database management systems and programming environments.