Sales Analysis III
<p>Table: <code>Product</code></p>

<pre>
+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| product_id   | int     |
| product_name | varchar |
| unit_price   | int     |
+--------------+---------+
product_id is the primary key (column with unique values) of this table.
Each row of this table indicates the name and the price of each product.
</pre>

<p>Table: <code>Sales</code></p>

<pre>
+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| seller_id   | int     |
| product_id  | int     |
| buyer_id    | int     |
| sale_date   | date    |
| quantity    | int     |
| price       | int     |
+-------------+---------+
This table can have duplicate rows.
product_id is a foreign key (reference column) to the Product table.
Each row of this table contains some information about one sale.
</pre>

<p>&nbsp;</p>

<p>Write a solution to&nbsp;report&nbsp;the <strong>products</strong> that were <strong>only</strong> sold in the first quarter of <code>2019</code>. That is, between <code>2019-01-01</code> and <code>2019-03-31</code> inclusive.</p>

<p>Return the result table in <strong>any order</strong>.</p>

<p>The result format is in the following example.</p>

<p>&nbsp;</p>
<p><strong class="example">Example 1:</strong></p>

<pre>
<strong>Input:</strong> 
Product table:
+------------+--------------+------------+
| product_id | product_name | unit_price |
+------------+--------------+------------+
| 1          | S8           | 1000       |
| 2          | G4           | 800        |
| 3          | iPhone       | 1400       |
+------------+--------------+------------+
Sales table:
+-----------+------------+----------+------------+----------+-------+
| seller_id | product_id | buyer_id | sale_date  | quantity | price |
+-----------+------------+----------+------------+----------+-------+
| 1         | 1          | 1        | 2019-01-21 | 2        | 2000  |
| 1         | 2          | 2        | 2019-02-17 | 1        | 800   |
| 2         | 2          | 3        | 2019-06-02 | 1        | 800   |
| 3         | 3          | 4        | 2019-05-13 | 2        | 2800  |
+-----------+------------+----------+------------+----------+-------+
<strong>Output:</strong> 
+-------------+--------------+
| product_id  | product_name |
+-------------+--------------+
| 1           | S8           |
+-------------+--------------+
<strong>Explanation:</strong> 
The product with id 1 was only sold in the spring of 2019.
The product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019.
The product with id 3 was sold after spring 2019.
We return only product 1 as it is the product that was only sold in the spring of 2019.
</pre>

['sales-analysis-ii']
['Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)', 'Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)', 'Truncate table Product', "insert into Product (product_id, product_name, unit_price) values ('1', 'S8', '1000')", "insert into Product (product_id, product_name, unit_price) values ('2', 'G4', '800')", "insert into Product (product_id, product_name, unit_price) values ('3', 'iPhone', '1400')", 'Truncate table Sales', "insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '1', '1', '2019-01-21', '2', '2000')", "insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '2', '2', '2019-02-17', '1', '800')", "insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('2', '2', '3', '2019-06-02', '1', '800')", "insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('3', '3', '4', '2019-05-13', '2', '2800')"]
[{"value": "mysql", "text": "MySQL", "defaultCode": "# Write your MySQL query statement below\n"}, {"value": "mssql", "text": "MS SQL Server", "defaultCode": "/* Write your T-SQL query statement below */\n"}, {"value": "oraclesql", "text": "Oracle", "defaultCode": "/* Write your PL/SQL query statement below */\n"}, {"value": "pythondata", "text": "Pandas", "defaultCode": "import pandas as pd\n\ndef sales_analysis(product: pd.DataFrame, sales: pd.DataFrame) -> pd.DataFrame:\n    "}, {"value": "postgresql", "text": "PostgreSQL", "defaultCode": "-- Write your PostgreSQL query statement below\n"}]
{"mysql": ["Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)", "Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)"], "mssql": ["Create table Product (product_id int, product_name varchar(10), unit_price int)", "Create table Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)"], "oraclesql": ["Create table Product (product_id int, product_name varchar(10), unit_price int)", "Create table Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)", "ALTER SESSION SET nls_date_format='YYYY-MM-DD'"], "database": true, "name": "sales_analysis", "pythondata": ["Product = pd.DataFrame([], columns=['product_id', 'product_name', 'unit_price']).astype({'product_id':'Int64', 'product_name':'object', 'unit_price':'Int64'})", "Sales = pd.DataFrame([], columns=['seller_id', 'product_id', 'buyer_id', 'sale_date', 'quantity', 'price']).astype({'seller_id':'Int64', 'product_id':'Int64', 'buyer_id':'Int64', 'sale_date':'datetime64[ns]', 'quantity':'Int64', 'price':'Int64'})"], "postgresql": ["Create table If Not Exists Product (product_id int, product_name varchar(10), unit_price int)\n", "Create table If Not Exists Sales (seller_id int, product_id int, buyer_id int, sale_date date, quantity int, price int)"], "database_schema": {"Product": {"product_id": "INT", "product_name": "VARCHAR(10)", "unit_price": "INT"}, "Sales": {"seller_id": "INT", "product_id": "INT", "buyer_id": "INT", "sale_date": "DATE", "quantity": "INT", "price": "INT"}}}
{"mysql": ["MySQL", "<p><code>MySQL 8.0</code>.</p>"], "mssql": ["MS SQL Server", "<p><code>mssql server 2019</code>.</p>"], "oraclesql": ["Oracle", "<p><code>Oracle Sql 11.2</code>.</p>"], "pythondata": ["Pandas", "<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4</p>"], "postgresql": ["PostgreSQL", "<p>PostgreSQL 16</p>"]}
['Database']