{"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":"932f2954-980b-5da7-8890-c34638663b4d","task_key":"default--v0~2e1~2e0~5fhf--932f2954-980b-5da7-8890-c34638663b4d","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 932f2954-980b-5da7-8890-c34638663b4d","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from random import sample\\nimport seaborn as sns\\nimport pandas as pd\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n\",\"complete_prompt\":\"from random import sample\\nimport seaborn as sns\\nimport pandas as pd\\n\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\n\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n    '''\\n    Remove rows from a dataframe based on values of multiple columns, \\n    and then create n random joint plots of two columns against each other if the DataFrame is not empty.\\n    \\n    Parameters:\\n    df (DataFrame): The pandas DataFrame.\\n    tuples (list): A list of tuples, where each tuple represents a row to be removed.\\n    n_plots (int): The number of jointplots to be generated.\\n    \\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: The modified DataFrame.\\n        - list: A list of generated joint plots (sns.JointGrid objects) if the DataFrame is not empty, otherwise an empty list.\\n    \\n    Requirements:\\n    - pandas\\n    - seaborn\\n    - random\\n    \\n    Example:\\n    >>> import numpy as np\\n    >>> df = pd.DataFrame(np.random.randint(0,100,size=(100, 5)), columns=list('ABCDE'))\\n    >>> tuples = [(10, 20, 30, 40, 50), (60, 70, 80, 90, 100)]\\n    >>> modified_df, plots = task_func(df, tuples, 3)\\n    '''\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Remove rows from a dataframe based on values of multiple columns, and then create n random joint plots of two columns against each other if the DataFrame is not empty.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: The modified DataFrame.\\n    list: A list of generated joint plots (sns.JointGrid objects) if the DataFrame is not empty, otherwise an empty list.\\nYou should write self-contained code starting with:\\n```\\nfrom random import sample\\nimport seaborn as sns\\nimport pandas as pd\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n```\",\"libs\":\"['pandas', 'random', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}