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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/reshape-data-concatenate.json
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@@ -2,14 +2,14 @@
"data": {
"question": {
"questionId": "3064",
"questionFrontendId": "100005",
"categoryTitle": "Algorithms",
"questionFrontendId": "2888",
"categoryTitle": "pandas",
"boundTopicId": 2453767,
"title": "Reshape Data: Concatenate",
"titleSlug": "reshape-data-concatenate",
"content": "<pre>\nDataFrame <code>df1</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\nDataFrame <code>df2</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\n</pre>\n\n<p>Write a solution to concatenate these two DataFrames <strong>vertically</strong> into one DataFrame.</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:\ndf1</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n+------------+---------+-----+\n<strong>df2\n</strong>+------------+------+-----+\n| student_id | name | age |\n+------------+------+-----+\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+------+-----+\n<strong>Output:</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+---------+-----+\n<strong>Explanation:\n</strong>The two DataFramess are stacked vertically, and their rows are combined.</pre>\n",
"translatedTitle": null,
"translatedContent": null,
"translatedTitle": "重塑数据：连结",
"translatedContent": "<pre>\nDataFrame <code>df1</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\nDataFrame <code>df2</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\n</pre>\n\n<p>编写一个解决方案，将两个&nbsp;DataFrames <b>垂直 </b>连接成一个&nbsp;DataFrame。</p>\n\n<p>结果格式如下示例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong class=\"example\">示例 1：</strong></p>\n\n<pre>\n<strong>输入：\ndf1</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n+------------+---------+-----+\n<strong>df2\n</strong>+------------+------+-----+\n| student_id | name | age |\n+------------+------+-----+\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+------+-----+\n<b>输出：</b>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+---------+-----+\n<strong>解释：\n</strong>两个 DataFrame 被垂直堆叠，它们的行被合并。</pre>\n",
"isPaidOnly": false,
"difficulty": "Easy",
"likes": 0,
@@ -28,7 +28,7 @@
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"hints": [
"Consider using a built-in function in pandas library with the appropriate axis argument."
],