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leetcode/originData/drop-missing-data.json

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+{
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+        "question": {
+            "questionId": "3075",
+            "questionFrontendId": "2883",
+            "boundTopicId": null,
+            "title": "Drop Missing Data",
+            "titleSlug": "drop-missing-data",
+            "content": "<pre>\nDataFrame students\n+-------------+--------+\n| Column Name | Type   |\n+-------------+--------+\n| student_id  | int    |\n| name        | object |\n| age         | int    |\n+-------------+--------+\n</pre>\n\n<p>There are some rows having missing values in the <code>name</code> column.</p>\n\n<p>Write a solution to remove the rows with missing values.</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| student_id | name  | age |\n+------------+-------+-----+\n| 32         | Piper | 5   |\n| 217        | Grace | 19  |\n| 779        | None  | 20  |\n| 849        | None  | 14  |\n+------------+-------+-----+\n<strong>Output:\n</strong>+------------+-------+-----+\n| student_id | name  | age |\n+------------+-------+-----+\n| 32         | Piper | 5   |\n| 217        | Grace | 19  |\n+------------+-------+-----+\n<strong>Explanation:</strong> \nStudents with ids 779 and 849 have empty values in the name column, so they will be removed.</pre>\n",
+            "translatedTitle": null,
+            "translatedContent": null,
+            "isPaidOnly": false,
+            "difficulty": "Easy",
+            "likes": 7,
+            "dislikes": 1,
+            "isLiked": null,
+            "similarQuestions": "[]",
+            "exampleTestcases": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,\"Grace\",19],[779,null,20],[849,null,14]]}}",
+            "categoryTitle": "Algorithms",
+            "contributors": [],
+            "topicTags": [],
+            "companyTagStats": null,
+            "codeSnippets": [
+                {
+                    "lang": "Pandas",
+                    "langSlug": "pythondata",
+                    "code": "import pandas as pd\n\ndef dropMissingData(students: pd.DataFrame) -> pd.DataFrame:\n    ",
+                    "__typename": "CodeSnippetNode"
+                }
+            ],
+            "stats": "{\"totalAccepted\": \"270\", \"totalSubmission\": \"295\", \"totalAcceptedRaw\": 270, \"totalSubmissionRaw\": 295, \"acRate\": \"91.5%\"}",
+            "hints": [
+                "Consider using a build-in function in pandas library to remove the rows with missing values based on specified data."
+            ],
+            "solution": {
+                "id": "2108",
+                "canSeeDetail": true,
+                "paidOnly": false,
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+            "sampleTestCase": "{\"headers\":{\"students\":[\"student_id\",\"name\",\"age\"]},\"rows\":{\"students\":[[32,\"Piper\",5],[217,\"Grace\",19],[779,null,20],[849,null,14]]}}",
+            "metaData": "{\n  \"pythondata\": [\n    \"students = pd.DataFrame([], columns=['student_id', 'name', 'age']).astype({'student_id':'Int64', 'name':'object', 'age':'Int64'})\"\n  ],\n  \"database\": true,\n  \"name\": \"dropMissingData\",\n  \"languages\": [\n    \"pythondata\"\n  ]\n}",
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+            "judgeType": "large",
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+            "envInfo": "{\"pythondata\": [\"Pandas\", \"<p>Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0</p>\"]}",
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+            "challengeQuestion": null,
+            "__typename": "QuestionNode"
+        }
+    }
+}