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        "question": {
            "questionId": "2057",
            "questionFrontendId": "1907",
            "categoryTitle": "Database",
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            "title": "Count Salary Categories",
            "titleSlug": "count-salary-categories",
            "content": "<p>Table: <code>Accounts</code></p>\n\n<pre>\n+-------------+------+\n| Column Name | Type |\n+-------------+------+\n| account_id  | int  |\n| income      | int  |\n+-------------+------+\naccount_id is the primary key (column with unique values) for this table.\nEach row contains information about the monthly income for one bank account.\n</pre>\n\n<p>&nbsp;</p>\n\n<p>Write a solution&nbsp;to calculate the number of bank accounts for each salary category. The salary categories are:</p>\n\n<ul>\n\t<li><code>&quot;Low Salary&quot;</code>: All the salaries <strong>strictly less</strong> than <code>$20000</code>.</li>\n\t<li><code>&quot;Average Salary&quot;</code>: All the salaries in the <strong>inclusive</strong> range <code>[$20000, $50000]</code>.</li>\n\t<li><code>&quot;High Salary&quot;</code>: All the salaries <strong>strictly greater</strong> than <code>$50000</code>.</li>\n</ul>\n\n<p>The result table <strong>must</strong> contain all three categories. If there are no accounts in a category,&nbsp;return&nbsp;<code>0</code>.</p>\n\n<p>Return the result table in <strong>any order</strong>.</p>\n\n<p>The&nbsp;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:</strong> \nAccounts table:\n+------------+--------+\n| account_id | income |\n+------------+--------+\n| 3          | 108939 |\n| 2          | 12747  |\n| 8          | 87709  |\n| 6          | 91796  |\n+------------+--------+\n<strong>Output:</strong> \n+----------------+----------------+\n| category       | accounts_count |\n+----------------+----------------+\n| Low Salary     | 1              |\n| Average Salary | 0              |\n| High Salary    | 3              |\n+----------------+----------------+\n<strong>Explanation:</strong> \nLow Salary: Account 2.\nAverage Salary: No accounts.\nHigh Salary: Accounts 3, 6, and 8.\n</pre>\n",
            "translatedTitle": "按分类统计薪水",
            "translatedContent": "<p>表: <code>Accounts</code></p>\n\n<pre>\n+-------------+------+\n| 列名        | 类型  |\n+-------------+------+\n| account_id  | int  |\n| income      | int  |\n+-------------+------+\n在 SQL 中，account_id&nbsp;是这个表的主键。\n每一行都包含一个银行帐户的月收入的信息。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>查询每个工资类别的银行账户数量。&nbsp;工资类别如下：</p>\n\n<ul>\n\t<li><code>\"Low Salary\"</code>：所有工资 <strong>严格低于</strong> <code>20000</code> 美元。</li>\n\t<li><code>\"Average Salary\"</code>： <strong>包含</strong> 范围内的所有工资&nbsp;<code>[$20000,&nbsp;$50000]</code> 。</li>\n\t<li>\n\t<p><code>\"High Salary\"</code>：所有工资 <strong>严格大于</strong> <code>50000</code> 美元。</p>\n\t</li>\n</ul>\n\n<p>结果表 <strong>必须</strong> 包含所有三个类别。&nbsp;如果某个类别中没有帐户，则报告&nbsp;<code>0</code> 。</p>\n\n<p>按 <strong>任意顺序</strong> 返回结果表。</p>\n\n<p>查询结果格式如下示例。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1：</strong></p>\n\n<pre>\n<b>输入：</b>\nAccounts 表:\n+------------+--------+\n| account_id | income |\n+------------+--------+\n| 3          | 108939 |\n| 2          | 12747  |\n| 8          | 87709  |\n| 6          | 91796  |\n+------------+--------+\n<strong>输出：</strong>\n+----------------+----------------+\n| category       | accounts_count |\n+----------------+----------------+\n| Low Salary     | 1              |\n| Average Salary | 0              |\n| High Salary    | 3              |\n+----------------+----------------+\n<strong>解释：</strong>\n低薪: 有一个账户 2.\n中等薪水: 没有.\n高薪: 有三个账户，他们是 3, 6和 8.</pre>\n",
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                    "code": "import pandas as pd\n\ndef count_salary_categories(accounts: pd.DataFrame) -> pd.DataFrame:\n    ",
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            "sampleTestCase": "{\"headers\":{\"Accounts\":[\"account_id\",\"income\"]},\"rows\":{\"Accounts\":[[3,108939],[2,12747],[8,87709],[6,91796]]}}",
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                "insert into Accounts (account_id, income) values ('2', '12747')",
                "insert into Accounts (account_id, income) values ('8', '87709')",
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