feat: add solutions to lc problem: No.3230 (doocs#3302)

No.3230.Customer Purchasing Behavior Analysis

Author: yanglbme

solution/3200-3299/3230.Customer Purchasing Behavior Analysis/README.md

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+---
+comments: true
+difficulty: 中等
+edit_url: https://github.com/doocs/leetcode/edit/main/solution/3200-3299/3230.Customer%20Purchasing%20Behavior%20Analysis/README.md
+---
+
+<!-- problem:start -->
+
+# [3230. Customer Purchasing Behavior Analysis 🔒](https://leetcode.cn/problems/customer-purchasing-behavior-analysis)
+
+[English Version](/solution/3200-3299/3230.Customer%20Purchasing%20Behavior%20Analysis/README_EN.md)
+
+## 题目描述
+
+<!-- description:start -->
+
+<p>Table: <code>Transactions</code></p>
+
+<pre>
++------------------+---------+
+| Column Name      | Type    |
++------------------+---------+
+| transaction_id   | int     |
+| customer_id      | int     |
+| product_id       | int     |
+| transaction_date | date    |
+| amount           | decimal |
++------------------+---------+
+transaction_id is the unique identifier for this table.
+Each row of this table contains information about a transaction, including the customer ID, product ID, date, and amount spent.
+</pre>
+
+<p>Table: <code>Products</code></p>
+
+<pre>
++-------------+---------+
+| Column Name | Type    |
++-------------+---------+
+| product_id  | int     |
+| category    | varchar |
+| price       | decimal |
++-------------+---------+
+product_id is the unique identifier for this table.
+Each row of this table contains information about a product, including its category and price.
+</pre>
+
+<p>Write a solution to analyze customer purchasing behavior. For <strong>each customer</strong>, calculate:</p>
+
+<ul>
+	<li>The total amount spent.</li>
+	<li>The number of transactions.</li>
+	<li>The number of <strong>unique</strong> product categories purchased.</li>
+	<li>The average amount spent.&nbsp;</li>
+	<li>The <strong>most frequently</strong> purchased product category&nbsp;(if there is a tie, choose the one with the most recent transaction).</li>
+	<li>A <strong>loyalty score</strong>&nbsp;defined as: (Number of transactions * 10) + (Total amount spent / 100).</li>
+</ul>
+
+<p>Round <code>total_amount</code>, <code>avg_transaction_amount</code>, and <code>loyalty_score</code> to <code>2</code> decimal places.</p>
+
+<p>Return <em>the result table ordered by</em> <code>loyalty_score</code> <em>in <strong>descending</strong> order</em>, <em>then by </em><code>customer_id</code><em> in <strong>ascending</strong> order</em>.</p>
+
+<p>The query result format is in the following example.</p>
+
+<p>&nbsp;</p>
+<p><strong class="example">Example:</strong></p>
+
+<div class="example-block">
+<p><strong>Input:</strong></p>
+
+<p><code>Transactions</code> table:</p>
+
+<pre class="example-io">
++----------------+-------------+------------+------------------+--------+
+| transaction_id | customer_id | product_id | transaction_date | amount |
++----------------+-------------+------------+------------------+--------+
+| 1              | 101         | 1          | 2023-01-01       | 100.00 |
+| 2              | 101         | 2          | 2023-01-15       | 150.00 |
+| 3              | 102         | 1          | 2023-01-01       | 100.00 |
+| 4              | 102         | 3          | 2023-01-22       | 200.00 |
+| 5              | 101         | 3          | 2023-02-10       | 200.00 |
++----------------+-------------+------------+------------------+--------+
+</pre>
+
+<p><code>Products</code> table:</p>
+
+<pre class="example-io">
++------------+----------+--------+
+| product_id | category | price  |
++------------+----------+--------+
+| 1          | A        | 100.00 |
+| 2          | B        | 150.00 |
+| 3          | C        | 200.00 |
++------------+----------+--------+
+</pre>
+
+<p><strong>Output:</strong></p>
+
+<pre class="example-io">
++-------------+--------------+-------------------+-------------------+------------------------+--------------+---------------+
+| customer_id | total_amount | transaction_count | unique_categories | avg_transaction_amount | top_category | loyalty_score |
++-------------+--------------+-------------------+-------------------+------------------------+--------------+---------------+
+| 101         | 450.00       | 3                 | 3                 | 150.00                 | C            | 34.50         |
+| 102         | 300.00       | 2                 | 2                 | 150.00                 | C            | 23.00         |
++-------------+--------------+-------------------+-------------------+------------------------+--------------+---------------+
+</pre>
+
+<p><strong>Explanation:</strong></p>
+
+<ul>
+	<li>For customer 101:
+	<ul>
+		<li>Total amount spent: 100.00 + 150.00 + 200.00 = 450.00</li>
+		<li>Number of transactions: 3</li>
+		<li>Unique categories: A, B, C (3 categories)</li>
+		<li>Average transaction amount: 450.00 / 3 = 150.00</li>
+		<li>Top category: C (Customer 101 made 1 purchase each in categories A, B, and C. Since the count is the same for all categories, we choose the most recent transaction, which is category C on 2023-02-10)</li>
+		<li>Loyalty score: (3 * 10) + (450.00 / 100) = 34.50</li>
+	</ul>
+	</li>
+	<li>For customer 102:
+	<ul>
+		<li>Total amount spent: 100.00 + 200.00 = 300.00</li>
+		<li>Number of transactions: 2</li>
+		<li>Unique categories: A, C (2 categories)</li>
+		<li>Average transaction amount: 300.00 / 2 = 150.00</li>
+		<li>Top category: C (Customer 102 made 1 purchase each in categories A and C. Since the count is the same for both categories, we choose the most recent transaction, which is category C on 2023-01-22)</li>
+		<li>Loyalty score: (2 * 10) + (300.00 / 100) = 23.00</li>
+	</ul>
+	</li>
+</ul>
+
+<p><strong>Note:</strong> The output is ordered by loyalty_score in descending order, then by customer_id in ascending order.</p>
+</div>
+
+<!-- description:end -->
+
+## 解法
+
+<!-- solution:start -->
+
+### 方法一：分组 + 窗口函数 + 连接
+
+我们首先将 `Transactions` 表和 `Products` 表连接起来，记录在临时表 `T` 中。
+
+然后，我们使用 `T` 表计算每个用户在每个类别下的交易次数以及最近的交易日期，将结果保存在临时表 `P` 中。
+
+接着，我们使用 `P` 表计算每个用户在每个类别下的交易次数的排名，将结果保存在临时表 `R` 中。
+
+最后，我们使用 `T` 表和 `R` 表计算每个用户的总交易金额、交易次数、唯一类别数、平均交易金额、最常购买的类别、忠诚度分数，并按照忠诚度分数降序、用户 ID 升序的顺序返回结果。
+
+<!-- tabs:start -->
+
+#### MySQL
+
+```sql
+# Write your MySQL query statement below
+WITH
+    T AS (
+        SELECT *
+        FROM
+            Transactions
+            JOIN Products USING (product_id)
+    ),
+    P AS (
+        SELECT
+            customer_id,
+            category,
+            COUNT(1) cnt,
+            MAX(transaction_date) max_date
+        FROM T
+        GROUP BY 1, 2
+    ),
+    R AS (
+        SELECT
+            customer_id,
+            category,
+            RANK() OVER (
+                PARTITION BY customer_id
+                ORDER BY cnt DESC, max_date DESC
+            ) rk
+        FROM P
+    )
+SELECT
+    t.customer_id,
+    ROUND(SUM(amount), 2) total_amount,
+    COUNT(1) transaction_count,
+    COUNT(DISTINCT t.category) unique_categories,
+    ROUND(AVG(amount), 2) avg_transaction_amount,
+    r.category top_category,
+    ROUND(COUNT(1) * 10 + SUM(amount) / 100, 2) loyalty_score
+FROM
+    T t
+    JOIN R r ON t.customer_id = r.customer_id AND r.rk = 1
+GROUP BY 1
+ORDER BY 7 DESC, 1;
+```
+
+<!-- tabs:end -->
+
+<!-- solution:end -->
+
+<!-- problem:end -->