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@@ -12,12 +12,12 @@
"translatedContent": "<p>表:<code>Products</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| product_id | int |\n| store1 | int |\n| store2 | int |\n| store3 | int |\n+-------------+---------+\n在 SQL 中,这张表的主键是 product_id产品Id。\n每行存储了这一产品在不同商店 store1, store2, store3 的价格。\n如果这一产品在商店里没有出售则值将为 null。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>请你重构 <code>Products</code> 表,查询每个产品在不同商店的价格,使得输出的格式变为<code>(product_id, store, price)</code> 。如果这一产品在商店里没有出售,则不输出这一行。</p>\n\n<p>输出结果表中的 <strong>顺序不作要求</strong> 。</p>\n\n<p>查询输出格式请参考下面示例。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1</strong></p>\n\n<pre>\n<strong>输入:</strong>\nProducts table:\n+------------+--------+--------+--------+\n| product_id | store1 | store2 | store3 |\n+------------+--------+--------+--------+\n| 0 | 95 | 100 | 105 |\n| 1 | 70 | null | 80 |\n+------------+--------+--------+--------+\n<strong>输出:</strong>\n+------------+--------+-------+\n| product_id | store | price |\n+------------+--------+-------+\n| 0 | store1 | 95 |\n| 0 | store2 | 100 |\n| 0 | store3 | 105 |\n| 1 | store1 | 70 |\n| 1 | store3 | 80 |\n+------------+--------+-------+\n<strong>解释:</strong>\n产品 0 在 store1、store2、store3 的价格分别为 95、100、105。\n产品 1 在 store1、store3 的价格分别为 70、80。在 store2 无法买到。</pre>\n",
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@@ -40,6 +40,12 @@
"code": "/* Write your T-SQL query statement below */",
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@@ -51,15 +57,9 @@
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"code": "import pandas as pd\n\ndef rearrange_products_table(products: pd.DataFrame) -> pd.DataFrame:\n ",
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