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"question": {
"questionId": "3071",
"questionFrontendId": "2882",
"boundTopicId": null,
"title": "Drop Duplicate Rows",
"titleSlug": "drop-duplicate-rows",
"content": "<pre>\nDataFrame customers\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| customer_id | int |\n| name | object |\n| email | object |\n+-------------+--------+\n</pre>\n\n<p>There are some duplicate rows in the DataFrame based on the <code>email</code> column.</p>\n\n<p>Write a solution to remove these duplicate rows and keep only the <strong>first</strong> occurrence.</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+-------------+---------+---------------------+\n| customer_id | name | email |\n+-------------+---------+---------------------+\n| 1 | Ella | emily@example.com |\n| 2 | David | michael@example.com |\n| 3 | Zachary | sarah@example.com |\n| 4 | Alice | john@example.com |\n| 5 | Finn | john@example.com |\n| 6 | Violet | alice@example.com |\n+-------------+---------+---------------------+\n<strong>Output: </strong> \n+-------------+---------+---------------------+\n| customer_id | name | email |\n+-------------+---------+---------------------+\n| 1 | Ella | emily@example.com |\n| 2 | David | michael@example.com |\n| 3 | Zachary | sarah@example.com |\n| 4 | Alice | john@example.com |\n| 6 | Violet | alice@example.com |\n+-------------+---------+---------------------+\n<strong>Explanation:</strong>\nAlic (customer_id = 4) and Finn (customer_id = 5) both use john@example.com, so only the first occurrence of this email is retained.\n</pre>\n",
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"difficulty": "Easy",
"likes": 9,
"dislikes": 1,
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"similarQuestions": "[]",
"exampleTestcases": "{\"headers\":{\"customers\":[\"customer_id\",\"name\",\"email\"]},\"rows\":{\"customers\":[[1,\"Ella\",\"emily@example.com\"],[2,\"David\",\"michael@example.com\"],[3,\"Zachary\",\"sarah@example.com\"],[4,\"Alice\",\"john@example.com\"],[5,\"Finn\",\"john@example.com\"],[6,\"Violet\",\"alice@example.com\"]]}}",
"categoryTitle": "Algorithms",
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{
"lang": "Pandas",
"langSlug": "pythondata",
"code": "import pandas as pd\n\ndef dropDuplicateEmails(customers: pd.DataFrame) -> pd.DataFrame:\n ",
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"hints": [
"Consider using a build-in function in pandas library to remove the duplicate rows based on specified data."
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"sampleTestCase": "{\"headers\":{\"customers\":[\"customer_id\",\"name\",\"email\"]},\"rows\":{\"customers\":[[1,\"Ella\",\"emily@example.com\"],[2,\"David\",\"michael@example.com\"],[3,\"Zachary\",\"sarah@example.com\"],[4,\"Alice\",\"john@example.com\"],[5,\"Finn\",\"john@example.com\"],[6,\"Violet\",\"alice@example.com\"]]}}",
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