存量题库数据更新

leetcode-cn/originData/get-the-size-of-a-dataframe.json

@@ -2,14 +2,14 @@
     "data": {
         "question": {
             "questionId": "3076",
-            "questionFrontendId": "100017",
-            "categoryTitle": "Algorithms",
+            "questionFrontendId": "2878",
+            "categoryTitle": "pandas",
             "boundTopicId": 2467483,
             "title": "Get the Size of a DataFrame",
             "titleSlug": "get-the-size-of-a-dataframe",
             "content": "<pre>\nDataFrame <code>players:</code>\n+-------------+--------+\n| Column Name | Type   |\n+-------------+--------+\n| player_id   | int    |\n| name        | object |\n| age         | int    |\n| position    | object |\n| ...         | ...    |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to calculate and display the <strong>number of rows and columns</strong> of <code>players</code>.</p>\n\n<p>Return the result as an array:</p>\n\n<p><code>[number of rows, number of columns]</code></p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>+-----------+----------+-----+-------------+--------------------+\n| player_id | name     | age | position    | team               |\n+-----------+----------+-----+-------------+--------------------+\n| 846       | Mason    | 21  | Forward     | RealMadrid         |\n| 749       | Riley    | 30  | Winger      | Barcelona          |\n| 155       | Bob      | 28  | Striker     | ManchesterUnited   |\n| 583       | Isabella | 32  | Goalkeeper  | Liverpool          |\n| 388       | Zachary  | 24  | Midfielder  | BayernMunich       |\n| 883       | Ava      | 23  | Defender    | Chelsea            |\n| 355       | Violet   | 18  | Striker     | Juventus           |\n| 247       | Thomas   | 27  | Striker     | ParisSaint-Germain |\n| 761       | Jack     | 33  | Midfielder  | ManchesterCity     |\n| 642       | Charlie  | 36  | Center-back | Arsenal            |\n+-----------+----------+-----+-------------+--------------------+<strong>\nOutput:\n</strong>[10, 5]\n<strong>Explanation:</strong>\nThis DataFrame contains 10 rows and 5 columns.\n</pre>\n",
-            "translatedTitle": null,
-            "translatedContent": null,
+            "translatedTitle": "获取 DataFrame 的大小",
+            "translatedContent": "<pre>\nDataFrame <code>players:</code>\n+-------------+--------+\n| Column Name | Type   |\n+-------------+--------+\n| player_id   | int    |\n| name        | object |\n| age         | int    |\n| position    | object |\n| ...         | ...    |\n+-------------+--------+\n</pre>\n\n<p>编写一个解决方案，计算并显示&nbsp;<code>players</code>&nbsp;的&nbsp;<strong>行数和列数</strong>。</p>\n\n<p>将结果返回为一个数组：</p>\n\n<p><code>[number of rows, number of columns]</code></p>\n\n<p>返回结果格式如下示例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><b>示例 1：</b></p>\n\n<pre>\n<strong>输入：\n</strong>+-----------+----------+-----+-------------+--------------------+\n| player_id | name     | age | position    | team               |\n+-----------+----------+-----+-------------+--------------------+\n| 846       | Mason    | 21  | Forward     | RealMadrid         |\n| 749       | Riley    | 30  | Winger      | Barcelona          |\n| 155       | Bob      | 28  | Striker     | ManchesterUnited   |\n| 583       | Isabella | 32  | Goalkeeper  | Liverpool          |\n| 388       | Zachary  | 24  | Midfielder  | BayernMunich       |\n| 883       | Ava      | 23  | Defender    | Chelsea            |\n| 355       | Violet   | 18  | Striker     | Juventus           |\n| 247       | Thomas   | 27  | Striker     | ParisSaint-Germain |\n| 761       | Jack     | 33  | Midfielder  | ManchesterCity     |\n| 642       | Charlie  | 36  | Center-back | Arsenal            |\n+-----------+----------+-----+-------------+--------------------+<strong>\n输出：\n</strong>[10, 5]\n<b>解释：</b>\n这个 DataFrame 包含 10 行和 5 列。\n</pre>\n",
             "isPaidOnly": false,
             "difficulty": "Easy",
             "likes": 0,
@@ -28,7 +28,7 @@
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+            "stats": "{\"totalAccepted\": \"2.1K\", \"totalSubmission\": \"2.5K\", \"totalAcceptedRaw\": 2088, \"totalSubmissionRaw\": 2472, \"acRate\": \"84.5%\"}",
             "hints": [
                 "Consider using a built-in function in pandas library to get the size of a DataFrame."
             ],