{"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":"1409f23a-b52e-5896-82c3-72fffefa1983","task_key":"default--v0~2e1~2e0~5fhf--1409f23a-b52e-5896-82c3-72fffefa1983","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 1409f23a-b52e-5896-82c3-72fffefa1983","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import seaborn as sns\\nfrom random import sample\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df, tuples, n_plots):\\n\",\"complete_prompt\":\"import seaborn as sns\\nfrom random import sample\\n\\n\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\n\\ndef task_func(df, tuples, n_plots):\\n    \\\"\\\"\\\"\\n    Remove rows from a dataframe based on values of multiple columns, and then create n random pairs of two columns \\n    against each other to generate pairplots.\\n\\n    Parameters:\\n    df (DataFrame): The pandas DataFrame.\\n    tuples (list of tuple): A list of tuples, where each tuple represents a row to be removed based on its values.\\n    n_plots (int): The number of pairplots to be generated using randomly selected column pairs.\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: The modified DataFrame after removing specified rows.\\n        - list of Axes: A list containing the generated pairplots.\\n\\n    Requirements:\\n    - seaborn\\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, 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 pairs of two columns against each other to generate pairplots.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: The modified DataFrame after removing specified rows.\\n    list of Axes: A list containing the generated pairplots.\\nYou should write self-contained code starting with:\\n```\\nimport seaborn as sns\\nfrom random import sample\\n# Constants\\nCOLUMNS = ['A', 'B', 'C', 'D', 'E']\\ndef task_func(df, tuples, n_plots):\\n```\",\"libs\":\"['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":[]}