{"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":"1f89136b-e89c-5f0e-85d3-67dcf49f66d8","task_key":"default--v0~2e1~2e0~5fhf--1f89136b-e89c-5f0e-85d3-67dcf49f66d8","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 1f89136b-e89c-5f0e-85d3-67dcf49f66d8","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import MinMaxScaler\\n# Constants\\nPLOT_TITLE = \\\"Scaled Values\\\"\\ndef task_func(data_dict):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import MinMaxScaler\\n\\n# Constants\\nPLOT_TITLE = \\\"Scaled Values\\\"\\n\\n\\ndef task_func(data_dict):\\n    \\\"\\\"\\\"\\n    Scales the values in a given dictionary using MinMaxScaler and plots the scaled data.\\n\\n    Parameters:\\n    - data_dict (dict): A dictionary where keys represent column names and values are lists of numerical data.\\n                        The values may contain missing data (None), which are handled by dropping them before scaling.\\n\\n    Returns:\\n    - pandas.DataFrame containing the scaled data.\\n    - matplotlib Axes object that displays the plot of the scaled data.\\n\\n    Requirements:\\n    - pandas\\n    - scikit-learn\\n    - matplotlib\\n\\n    Example:\\n    >>> data = {'a': [1, 2, None, 4], 'b': [5, None, 7, 8]}\\n    >>> scaled_df, plot_ax = task_func(data)\\n    >>> scaled_df\\n         a    b\\n    0  0.0  0.0\\n    1  1.0  1.0\\n    >>> plot_ax.get_title()\\n    'Scaled Values'\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Scales the values in a given dictionary using MinMaxScaler and plots the scaled data.\\nThe function should output with:\\n    pandas.DataFrame containing the scaled data.\\n    matplotlib Axes object that displays the plot of the scaled data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import MinMaxScaler\\n# Constants\\nPLOT_TITLE = \\\"Scaled Values\\\"\\ndef task_func(data_dict):\\n```\",\"libs\":\"['pandas', 'matplotlib', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}