update

leetcode-cn/originData/find-product-recommendation-pairs.json

@@ -12,12 +12,12 @@
             "translatedContent": "<p>表：<code>ProductPurchases</code></p>\n\n<pre>\n+-------------+------+\n| Column Name | Type | \n+-------------+------+\n| user_id     | int  |\n| product_id  | int  |\n| quantity    | int  |\n+-------------+------+\n(user_id, product_id) 是这张表的唯一主键。\n每一行代表用户以特定数量购买的产品。\n</pre>\n\n<p>表：<code>ProductInfo</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type    | \n+-------------+---------+\n| product_id  | int     |\n| category    | varchar |\n| price       | decimal |\n+-------------+---------+\nproduct_id 是这张表的唯一主键。\n每一行表示一个产品的类别和价格。\n</pre>\n\n<p>亚马逊希望根据 <strong>共同购买模式</strong> 实现 “<strong>购买此商品的用户还购买了...</strong>” 功能。编写一个解决方案以实现：</p>\n\n<ol>\n\t<li>识别 <strong>被同一客户一起频繁购买的</strong> <strong>不同</strong> 产品对（其中&nbsp;<code>product1_id</code> &lt; <code>product2_id</code>）</li>\n\t<li>对于 <strong>每个产品对</strong>，确定有多少客户购买了这两种产品</li>\n</ol>\n\n<p>如果 <strong>至少有</strong> <code>3</code> <strong>位不同的</strong> 客户同时购买了这两种产品，则认为该&nbsp;<strong>产品对&nbsp;</strong>适合推荐。</p>\n\n<p>返回结果表以<em>&nbsp;</em><strong>customer_count</strong>&nbsp; <strong>降序&nbsp;</strong>排序，并且为了避免排序持平，以&nbsp;<code>product1_id</code><em> </em><strong>升序&nbsp;</strong>排序，并以<em>&nbsp;</em><code>product2_id</code><em> </em><strong>升序 </strong>排序。</p>\n\n<p>结果格式如下所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong class=\"example\">示例：</strong></p>\n\n<div class=\"example-block\">\n<p><strong>输入：</strong></p>\n\n<p>ProductPurchases 表：</p>\n\n<pre class=\"example-io\">\n+---------+------------+----------+\n| user_id | product_id | quantity |\n+---------+------------+----------+\n| 1       | 101        | 2        |\n| 1       | 102        | 1        |\n| 1       | 103        | 3        |\n| 2       | 101        | 1        |\n| 2       | 102        | 5        |\n| 2       | 104        | 1        |\n| 3       | 101        | 2        |\n| 3       | 103        | 1        |\n| 3       | 105        | 4        |\n| 4       | 101        | 1        |\n| 4       | 102        | 1        |\n| 4       | 103        | 2        |\n| 4       | 104        | 3        |\n| 5       | 102        | 2        |\n| 5       | 104        | 1        |\n+---------+------------+----------+\n</pre>\n\n<p>ProductInfo 表：</p>\n\n<pre class=\"example-io\">\n+------------+-------------+-------+\n| product_id | category    | price |\n+------------+-------------+-------+\n| 101        | Electronics | 100   |\n| 102        | Books       | 20    |\n| 103        | Clothing    | 35    |\n| 104        | Kitchen     | 50    |\n| 105        | Sports      | 75    |\n+------------+-------------+-------+\n</pre>\n\n<p><strong>输出：</strong></p>\n\n<pre class=\"example-io\">\n+-------------+-------------+-------------------+-------------------+----------------+\n| product1_id | product2_id | product1_category | product2_category | customer_count |\n+-------------+-------------+-------------------+-------------------+----------------+\n| 101         | 102         | Electronics       | Books             | 3              |\n| 101         | 103         | Electronics       | Clothing          | 3              |\n| 102         | 104         | Books             | Kitchen           | 3              |\n+-------------+-------------+-------------------+-------------------+----------------+\n</pre>\n\n<p><strong>解释：</strong></p>\n\n<ul>\n\t<li><strong>产品对 (101, 102)：</strong>\n\n\t<ul>\n\t\t<li>被用户 1，2 和 4 购买（3 个消费者）</li>\n\t\t<li>产品 101 属于电子商品类别</li>\n\t\t<li>产品 102 属于图书类别</li>\n\t</ul>\n\t</li>\n\t<li><strong>产品对 (101, 103)：</strong>\n\t<ul>\n\t\t<li>被用户 1，3 和 4 购买（3 个消费者）</li>\n\t\t<li>产品 101 属于电子商品类别</li>\n\t\t<li>产品 103 属于服装类别</li>\n\t</ul>\n\t</li>\n\t<li><strong>产品对 (102, 104)：</strong>\n\t<ul>\n\t\t<li>被用户 2，4 和 5 购买（3 个消费者）</li>\n\t\t<li>产品 102 属于图书类别</li>\n\t\t<li>产品 104 属于厨房用品类别</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>结果以 customer_count 降序排序。对于有相同&nbsp;customer_count 的产品对，将它们以&nbsp;product1_id 升序排序，然后以 product2_id 升序排序。</p>\n</div>\n",
             "isPaidOnly": false,
             "difficulty": "Medium",
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                     "code": "import pandas as pd\n\ndef find_product_recommendation_pairs(product_purchases: pd.DataFrame, product_info: pd.DataFrame) -> pd.DataFrame:\n    ",
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