{"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":"noindex","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[]}},"task_id":"2e25ccdb-b50e-5deb-af2c-44ae3529cf49","task_key":"default--v0~2e1~2e0~5fhf--2e25ccdb-b50e-5deb-af2c-44ae3529cf49","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2e25ccdb-b50e-5deb-af2c-44ae3529cf49","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom itertools import cycle\\ndef task_func(df, groups=['A', 'B', 'C', 'D', 'E']):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom itertools import cycle\\n\\ndef task_func(df, groups=['A', 'B', 'C', 'D', 'E']):\\n    \\\"\\\"\\\"\\n    Analyzes the groups in a DataFrame by plotting a scatter plot of the ordinals against the values for each group.\\n\\n    Parameters:\\n    df (DataFrame): The DataFrame with columns 'group', 'date', and 'value'.\\n    groups (list, optional): List of group identifiers. Defaults to ['A', 'B', 'C', 'D', 'E'].\\n\\n    Returns:\\n    matplotlib.axes.Axes: The Axes object with the scatter plot.\\n    The Axes object will have a title 'Scatterplot of Values for Each Group Over Time', \\n               x-axis labeled as 'Date (ordinal)', and y-axis labeled as 'Value'.\\n\\n\\n    Raises:\\n    ValueError: If 'df' is not a DataFrame or lacks required columns.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib.pyplot\\n    - itertools\\n\\n    Example:\\n    >>> df = pd.DataFrame({\\n    ...     \\\"group\\\": [\\\"A\\\", \\\"A\\\", \\\"A\\\", \\\"B\\\", \\\"B\\\"],\\n    ...     \\\"date\\\": pd.to_datetime([\\\"2022-01-02\\\", \\\"2022-01-13\\\", \\\"2022-02-01\\\", \\\"2022-02-23\\\", \\\"2022-03-05\\\"]),\\n    ...     \\\"value\\\": [10, 20, 16, 31, 56],\\n    ...     })\\n    >>> ax = task_func(df)\\n    >>> ax.figure.show()  # This will display the plot\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Analyzes the groups in a DataFrame by plotting a scatter plot of the ordinals against the values for each group.\\nThe function should raise the exception for: ValueError: If 'df' is not a DataFrame or lacks required columns.\\nThe function should output with:\\n    matplotlib.axes.Axes: The Axes object with the scatter plot.\\n    The Axes object will have a title 'Scatterplot of Values for Each Group Over Time',\\n    x-axis labeled as 'Date (ordinal)', and y-axis labeled as 'Value'.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom itertools import cycle\\ndef task_func(df, groups=['A', 'B', 'C', 'D', 'E']):\\n```\",\"libs\":\"['pandas', 'itertools', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}