{"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":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"6d2127f9-c0dc-5859-b166-1b30b8f91ce2","task_key":"default--v0~2e1~2e0~5fhf--6d2127f9-c0dc-5859-b166-1b30b8f91ce2","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 6d2127f9-c0dc-5859-b166-1b30b8f91ce2","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import seaborn as sns\\nimport time\\ndef task_func(df, letter):\\n\",\"complete_prompt\":\"import seaborn as sns\\nimport time\\n\\ndef task_func(df, letter):\\n    \\\"\\\"\\\"\\n    Filters rows in a DataFrame based on the starting letter of the values in the 'Word' column.\\n    It then calculates the lengths of these words and returns a box plot representing the distribution\\n    of these lengths.\\n\\n    Parameters:\\n    - df (pd.DataFrame): The input DataFrame containing a 'Word' column with string values.\\n    - letter (str): A lowercase letter to filter words in the 'Word' column.\\n\\n    Returns:\\n    - Axes: A box plot visualizing the distribution of the word lengths for words starting\\n                   with the specified letter. If the DataFrame is empty or the 'Word' column is missing,\\n                   returns None.\\n\\n    Requirements:\\n    - seaborn\\n    - time\\n\\n    Example:\\n    >>> import pandas as pd\\n    >>> words = ['apple', 'banana', 'cherry', 'date', 'apricot', 'blueberry', 'avocado']\\n    >>> df = pd.DataFrame({'Word': words})\\n    >>> _ = task_func(df, 'apple')\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Filters rows in a DataFrame based on the starting letter of the values in the 'Word' column. It then calculates the lengths of these words and returns a box plot representing the distribution of these lengths.\\nThe function should output with:\\n    Axes: A box plot visualizing the distribution of the word lengths for words starting\\n    with the specified letter. If the DataFrame is empty or the 'Word' column is missing,\\n    returns None.\\nYou should write self-contained code starting with:\\n```\\nimport seaborn as sns\\nimport time\\ndef task_func(df, letter):\\n```\",\"libs\":\"['time', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}