{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"noindex","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[]}},"task_id":"0bbf393f-c8a3-5686-8120-c12d42978dcd","task_key":"default--v0~2e1~2e0~5fhf--0bbf393f-c8a3-5686-8120-c12d42978dcd","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 0bbf393f-c8a3-5686-8120-c12d42978dcd","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport regex as re\\n# Constants\\nSTOPWORDS = [\\\"a\\\", \\\"an\\\", \\\"the\\\", \\\"in\\\", \\\"is\\\", \\\"are\\\"]\\ndef task_func(text):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport regex as re\\n\\n# Constants\\nSTOPWORDS = [\\\"a\\\", \\\"an\\\", \\\"the\\\", \\\"in\\\", \\\"is\\\", \\\"are\\\"]\\n\\n\\ndef task_func(text):\\n    \\\"\\\"\\\"\\n    Count the frequency of each word in a text after removing specific stopwords.\\n\\n    Parameters:\\n    text (str): The text to analyze.\\n\\n    Returns:\\n    Series: A pandas Series with word frequencies excluding the words in STOPWORDS list.\\n\\n    Requirements:\\n    - pandas\\n    - regex\\n\\n    Example:\\n    >>> text = \\\"This is a sample text. This text contains sample words.\\\"\\n    >>> word_counts = task_func(text)\\n    >>> print(word_counts)\\n    this        2\\n    sample      2\\n    text        2\\n    contains    1\\n    words       1\\n    dtype: int64\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Count the frequency of each word in a text after removing specific stopwords.\\nThe function should output with:\\n    Series: A pandas Series with word frequencies excluding the words in STOPWORDS list.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport regex as re\\n# Constants\\nSTOPWORDS = [\\\"a\\\", \\\"an\\\", \\\"the\\\", \\\"in\\\", \\\"is\\\", \\\"are\\\"]\\ndef task_func(text):\\n```\",\"libs\":\"['regex', 'pandas']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}