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存量题库数据更新

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小墨
2023-12-09 18:42:21 +08:00
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leetcode-cn/originData/fill-missing-data.json
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@@ -3,13 +3,13 @@
"question": {
"questionId": "3070",
"questionFrontendId": "2887",
"categoryTitle": "Algorithms",
"categoryTitle": "pandas",
"boundTopicId": 2467496,
"title": "Fill Missing Data",
"titleSlug": "fill-missing-data",
"content": "<pre>\nDataFrame <code>products</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| name | object |\n| quantity | int |\n| price | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to fill in the missing value as <code><strong>0</strong></code> in the <code>quantity</code> column.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | 32 | 135 |\n| WirelessEarbuds | None | 821 |\n| GolfClubs | None | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<strong>Output:\n</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | 32 | 135 |\n| WirelessEarbuds | 0 | 821 |\n| GolfClubs | 0 | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<strong>Explanation:</strong> \nThe quantity for Toaster and Headphones are filled by 0.</pre>\n",
"translatedTitle": null,
"translatedContent": null,
"content": "<pre>\nDataFrame <code>products</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| name | object |\n| quantity | int |\n| price | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to fill in the missing value as <code><strong>0</strong></code> in the <code>quantity</code> column.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | None | 135 |\n| WirelessEarbuds | None | 821 |\n| GolfClubs | 779 | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<strong>Output:\n</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | 0 | 135 |\n| WirelessEarbuds | 0 | 821 |\n| GolfClubs | 779 | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<strong>Explanation:</strong> \nThe quantity for Wristwatch and WirelessEarbuds are filled by 0.</pre>\n",
"translatedTitle": "填充缺失值",
"translatedContent": "<pre>\nDataFrame <code>products</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| name | object |\n| quantity | int |\n| price | int |\n+-------------+--------+\n</pre>\n\n<p>编写一个解决方案，在 <code>quantity</code> 列中将缺失的值填充为&nbsp;<code><strong>0</strong></code>。</p>\n\n<p>返回结果如下示例所示。</p>\n\n<p>&nbsp;</p>\n<strong class=\"example\">示例 1：</strong>\n\n<pre>\n<strong>输入：\n</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | 32 | 135 |\n| WirelessEarbuds | None | 821 |\n| GolfClubs | None | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<strong>输出：\n</strong>+-----------------+----------+-------+\n| name | quantity | price |\n+-----------------+----------+-------+\n| Wristwatch | 32 | 135 |\n| WirelessEarbuds | 0 | 821 |\n| GolfClubs | 0 | 9319 |\n| Printer | 849 | 3051 |\n+-----------------+----------+-------+\n<b>解释：</b>\nToaster 和 Headphones 的数量被填充为 0。</pre>\n",
"isPaidOnly": false,
"difficulty": "Easy",
"likes": 0,
@@ -28,13 +28,13 @@
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"stats": "{\"totalAccepted\": \"11\", \"totalSubmission\": \"11\", \"totalAcceptedRaw\": 11, \"totalSubmissionRaw\": 11, \"acRate\": \"100.0%\"}",
"stats": "{\"totalAccepted\": \"1.3K\", \"totalSubmission\": \"1.8K\", \"totalAcceptedRaw\": 1276, \"totalSubmissionRaw\": 1821, \"acRate\": \"70.1%\"}",
"hints": [
"Consider using a build-in function in pandas library to fill the missing values of specified columns."
],
"solution": null,
"status": null,
"sampleTestCase": "{\"headers\":{\"products\":[\"name\",\"quantity\",\"price\"]},\"rows\":{\"products\":[[\"Wristwatch\",32,135],[\"WirelessEarbuds\",null,821],[\"GolfClubs\",null,9319],[\"Printer\",849,3051]]}}",
"sampleTestCase": "{\"headers\":{\"products\":[\"name\",\"quantity\",\"price\"]},\"rows\":{\"products\":[[\"Wristwatch\",null,135],[\"WirelessEarbuds\",null,821],[\"GolfClubs\",779,9319],[\"Printer\",849,3051]]}}",
"metaData": "{\n \"pythondata\": [\n \"products = pd.DataFrame([], columns=['name', 'quantity', 'price']).astype({'name':'object', 'quantity':'Int64', 'price':'Int64'})\"\n ],\n \"database\": true,\n \"name\": \"fillMissingValues\",\n \"languages\": [\n \"pythondata\"\n ]\n}",
"judgerAvailable": true,
"judgeType": "large",
@@ -48,7 +48,7 @@
"editorType": "CKEDITOR",
"ugcQuestionId": null,
"style": "LEETCODE",
"exampleTestcases": "{\"headers\":{\"products\":[\"name\",\"quantity\",\"price\"]},\"rows\":{\"products\":[[\"Wristwatch\",32,135],[\"WirelessEarbuds\",null,821],[\"GolfClubs\",null,9319],[\"Printer\",849,3051]]}}",
"exampleTestcases": "{\"headers\":{\"products\":[\"name\",\"quantity\",\"price\"]},\"rows\":{\"products\":[[\"Wristwatch\",null,135],[\"WirelessEarbuds\",null,821],[\"GolfClubs\",779,9319],[\"Printer\",849,3051]]}}",
"__typename": "QuestionNode"
}
}