{"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":"d3f13a45-d6d0-51ce-a2d0-09246b817257","task_key":"default--v0~2e1~2e0~5fhf--d3f13a45-d6d0-51ce-a2d0-09246b817257","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf d3f13a45-d6d0-51ce-a2d0-09246b817257","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from itertools import combinations\\nfrom random import sample\\ndef task_func(df, tuples, n_plots):\\n\",\"complete_prompt\":\"from itertools import combinations\\nfrom random import sample\\n\\n\\ndef task_func(df, tuples, n_plots):\\n    \\\"\\\"\\\"\\n    Removes rows from a DataFrame based on a list of tuples, each representing row values to match and remove.\\n    Generates up to 'n_plots' scatter plots for random combinations of two columns from the remaining DataFrame.\\n\\n    Parameters:\\n    - df (pd.DataFrame): The input DataFrame.\\n    - tuples (list): A list of tuples, where each tuple contains values that, if matched, should result in the row being removed.\\n    - n_plots (int): The maximum number of scatter plots to generate from the remaining data.\\n\\n    Returns:\\n    - pd.DataFrame: The DataFrame after specified rows have been removed.\\n    - list: A list of tuples, each containing a pair of column names used for the plot and the corresponding plot object.\\n\\n    Requirements:\\n    - random\\n    - itertools\\n\\n    Example:\\n    >>> import numpy as np, pandas as pd\\n    >>> df = pd.DataFrame(np.random.rand(10, 5), columns=['A', 'B', 'C', 'D', 'E'])\\n    >>> tuples = [(0.1, 0.2, 0.3, 0.4, 0.5)]\\n    >>> modified_df, plots = task_func(df, tuples, 3)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Removes rows from a DataFrame based on a list of tuples, each representing row values to match and remove. Generates up to 'n_plots' scatter plots for random combinations of two columns from the remaining DataFrame.\\nThe function should output with:\\n    pd.DataFrame: The DataFrame after specified rows have been removed.\\n    list: A list of tuples, each containing a pair of column names used for the plot and the corresponding plot object.\\nYou should write self-contained code starting with:\\n```\\nfrom itertools import combinations\\nfrom random import sample\\ndef task_func(df, tuples, n_plots):\\n```\",\"libs\":\"['random', 'itertools']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}