{"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":"3cfe558e-745c-5cd5-9825-c4f0cd2daa6b","task_key":"default--v0~2e1~2e0~5fhf--3cfe558e-745c-5cd5-9825-c4f0cd2daa6b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 3cfe558e-745c-5cd5-9825-c4f0cd2daa6b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom random import sample\\n# Constants for column names to use in plots\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom random import sample\\n\\n# Constants for column names to use in plots\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\n\\n\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n    '''\\n    Remove rows from a dataframe based on column values and generate random scatter plots.\\n\\n    Parameters:\\n    - df (pd.DataFrame): The input DataFrame to be modified.\\n    - tuples (list): A list of tuples, each representing a row's values for removal.\\n    - n_plots (int): Number of scatter plots to generate from random pairs of columns.\\n\\n    Returns:\\n    - pd.DataFrame: The DataFrame after removal of specified rows.\\n    - list: A list containing matplotlib Axes objects of the generated plots.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib.pyplot\\n    - random\\n\\n    Example:\\n    >>> df = pd.DataFrame(np.random.randint(0,100,size=(100, 5)), columns=COLUMNS)\\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 column values and generate random scatter plots.\\nThe function should output with:\\n    pd.DataFrame: The DataFrame after removal of specified rows.\\n    list: A list containing matplotlib Axes objects of the generated plots.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom random import sample\\n# Constants for column names to use in plots\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df: pd.DataFrame, tuples: list, n_plots: int) -> (pd.DataFrame, list):\\n```\",\"libs\":\"['pandas', 'random', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}