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commit 13f2098086
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@@ -12,12 +12,12 @@
"translatedContent": "<p>表:<code>Prices</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| start_date | date |\n| end_date | date |\n| price | int |\n+---------------+---------+\n(product_idstart_dateend_date) 是 <code>prices</code> 表的主键(具有唯一值的列的组合)。\n<code>prices</code> 表的每一行表示的是某个产品在一段时期内的价格。\n每个产品的对应时间段是不会重叠的这也意味着同一个产品的价格时段不会出现交叉。</pre>\n\n<p>&nbsp;</p>\n\n<p>表:<code>UnitsSold</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| purchase_date | date |\n| units | int |\n+---------------+---------+\n<span style=\"white-space: pre-wrap;\">该表可能包含重复数据</span>。\n<span style=\"white-space: pre-wrap;\">该</span>表的每一行表示的是每种产品的出售日期,单位和产品 id。</pre>\n\n<p>&nbsp;</p>\n\n<p>编写解决方案以查找每种产品的平均售价。<code>average_price</code> 应该 <strong>四舍五入到小数点后两位</strong>。如果产品没有任何售出,则假设其平均售价为 0。</p>\n\n<p>返回结果表 <strong>无顺序要求</strong> 。</p>\n\n<p>结果格式如下例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1</strong></p>\n\n<pre>\n<strong>输入:</strong>\nPrices table:\n+------------+------------+------------+--------+\n| product_id | start_date | end_date | price |\n+------------+------------+------------+--------+\n| 1 | 2019-02-17 | 2019-02-28 | 5 |\n| 1 | 2019-03-01 | 2019-03-22 | 20 |\n| 2 | 2019-02-01 | 2019-02-20 | 15 |\n| 2 | 2019-02-21 | 2019-03-31 | 30 |\n+------------+------------+------------+--------+\nUnitsSold table:\n+------------+---------------+-------+\n| product_id | purchase_date | units |\n+------------+---------------+-------+\n| 1 | 2019-02-25 | 100 |\n| 1 | 2019-03-01 | 15 |\n| 2 | 2019-02-10 | 200 |\n| 2 | 2019-03-22 | 30 |\n+------------+---------------+-------+\n<strong>输出:</strong>\n+------------+---------------+\n| product_id | average_price |\n+------------+---------------+\n| 1 | 6.96 |\n| 2 | 16.96 |\n+------------+---------------+\n<strong>解释:</strong>\n平均售价 = 产品总价 / 销售的产品数量。\n产品 1 的平均售价 = ((100 * 5)+(15 * 20) )/ 115 = 6.96\n产品 2 的平均售价 = ((200 * 15)+(30 * 30) )/ 230 = 16.96</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 average_selling_price(prices: pd.DataFrame, units_sold: pd.DataFrame) -> pd.DataFrame:\n ",
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