{ "data": { "question": { "questionId": "3076", "questionFrontendId": "2878", "boundTopicId": null, "title": "Get the Size of a DataFrame", "titleSlug": "get-the-size-of-a-dataframe", "content": "
\nDataFrame players:
\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| player_id | int |\n| name | object |\n| age | int |\n| position | object |\n| ... | ... |\n+-------------+--------+\n
\n\nWrite a solution to calculate and display the number of rows and columns of players
.
Return the result as an array:
\n\n[number of rows, number of columns]
The result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput:\n+-----------+----------+-----+-------------+--------------------+\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+-----------+----------+-----+-------------+--------------------+\nOutput:\n[10, 5]\nExplanation:\nThis DataFrame contains 10 rows and 5 columns.\n\n", "translatedTitle": null, "translatedContent": null, "isPaidOnly": false, "difficulty": "Easy", "likes": 42, "dislikes": 6, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "{\"headers\":{\"players\":[\"player_id\",\"name\",\"age\",\"position\",\"team\"]},\"rows\":{\"players\":[[846,\"Mason\",21,\"Forward\",\"RealMadrid\"],[749,\"Riley\",30,\"Winger\",\"Barcelona\"],[155,\"Bob\",28,\"Striker\",\"ManchesterUnited\"],[583,\"Isabella\",32,\"Goalkeeper\",\"Liverpool\"],[388,\"Zachary\",24,\"Midfielder\",\"BayernMunich\"],[883,\"Ava\",23,\"Defender\",\"Chelsea\"],[355,\"Violet\",18,\"Striker\",\"Juventus\"],[247,\"Thomas\",27,\"Striker\",\"ParisSaint-Germain\"],[761,\"Jack\",33,\"Midfielder\",\"ManchesterCity\"],[642,\"Charlie\",36,\"Center-back\",\"Arsenal\"]]}}", "categoryTitle": "pandas", "contributors": [], "topicTags": [], "companyTagStats": null, "codeSnippets": [ { "lang": "Pandas", "langSlug": "pythondata", "code": "import pandas as pd\n\ndef getDataframeSize(players: pd.DataFrame) -> List[int]:\n ", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"15.3K\", \"totalSubmission\": \"18.3K\", \"totalAcceptedRaw\": 15311, \"totalSubmissionRaw\": 18324, \"acRate\": \"83.6%\"}", "hints": [ "Consider using a built-in function in pandas library to get the size of a DataFrame." ], "solution": { "id": "2109", "canSeeDetail": true, "paidOnly": false, "hasVideoSolution": false, "paidOnlyVideo": true, "__typename": "ArticleNode" }, "status": null, "sampleTestCase": "{\"headers\":{\"players\":[\"player_id\",\"name\",\"age\",\"position\",\"team\"]},\"rows\":{\"players\":[[846,\"Mason\",21,\"Forward\",\"RealMadrid\"],[749,\"Riley\",30,\"Winger\",\"Barcelona\"],[155,\"Bob\",28,\"Striker\",\"ManchesterUnited\"],[583,\"Isabella\",32,\"Goalkeeper\",\"Liverpool\"],[388,\"Zachary\",24,\"Midfielder\",\"BayernMunich\"],[883,\"Ava\",23,\"Defender\",\"Chelsea\"],[355,\"Violet\",18,\"Striker\",\"Juventus\"],[247,\"Thomas\",27,\"Striker\",\"ParisSaint-Germain\"],[761,\"Jack\",33,\"Midfielder\",\"ManchesterCity\"],[642,\"Charlie\",36,\"Center-back\",\"Arsenal\"]]}}", "metaData": "{\n \"pythondata\": [\n \"players = pd.DataFrame([], columns=['player_id', 'name', 'age', 'position', 'team']).astype({'player_id':'Int64', 'name':'object', 'age':'Int64', 'position':'object', 'team':'object'})\"\n ],\n \"database\": true,\n \"name\": \"get_size\",\n \"languages\": [\n \"pythondata\"\n ],\n \"manual\": true\n}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [], "enableRunCode": true, "enableTestMode": false, "enableDebugger": false, "envInfo": "{\"pythondata\": [\"Pandas\", \"
Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0
\"]}", "libraryUrl": null, "adminUrl": null, "challengeQuestion": null, "__typename": "QuestionNode" } } }