{"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":"890ac286-b056-500f-baf3-d1647c818601","task_key":"default--v0~2e1~2e0~5fhf--890ac286-b056-500f-baf3-d1647c818601","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 890ac286-b056-500f-baf3-d1647c818601","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from random import sample\\nimport matplotlib.pyplot as plt\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df, tuples, n_plots):\\n\",\"complete_prompt\":\"from random import sample\\nimport matplotlib.pyplot as plt\\n\\n\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\n\\n\\ndef task_func(df, tuples, n_plots):\\n    \\\"\\\"\\\"\\n    Removes rows from a DataFrame based on values of multiple columns, \\n    and then create n random line plots of two columns against each other.\\n\\n    Parameters:\\n    - df (pd.DataFrame): The input pandas DataFrame.\\n    - tuples (list of tuple): A list of tuples, each tuple represents values in a row to be removed.\\n    - n_plots (int): The number of line plots to generate.\\n\\n    Returns:\\n    - (pd.DataFrame, list): A tuple containing the modified DataFrame and a list of plot details.\\n      Each entry in the plot details list is a tuple containing the two columns plotted against each other.\\n\\n    Requirements:\\n    - matplotlib.pyplot\\n    - random\\n\\n    Example:\\n    >>> import numpy as np, pandas as pd\\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, plot_details = task_func(df, tuples, 3)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Removes rows from a DataFrame based on values of multiple columns, and then create n random line plots of two columns against each other.\\nThe function should output with:\\n    (pd.DataFrame, list): A tuple containing the modified DataFrame and a list of plot details.\\n    Each entry in the plot details list is a tuple containing the two columns plotted against each other.\\nYou should write self-contained code starting with:\\n```\\nfrom random import sample\\nimport matplotlib.pyplot as plt\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df, tuples, n_plots):\\n```\",\"libs\":\"['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":[]}