{"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":"0a649d71-a231-5627-a7a9-bddfb70fe151","task_key":"default--v0~2e1~2e0~5fhf--0a649d71-a231-5627-a7a9-bddfb70fe151","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 0a649d71-a231-5627-a7a9-bddfb70fe151","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\ndef task_func(df, items=None, locations=None):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(df, items=None, locations=None):\\n    \\\"\\\"\\\"\\n    Generates a bar chart representing the distribution of specified items across given locations.\\n    \\n    The function takes a DataFrame with 'Item' and 'Location' columns and plots the count of each item\\n    per location. If lists of items and locations are provided, the chart will only include those specified,\\n    otherwise it defaults to a predefined list.\\n\\n    Parameters:\\n    - df (pandas.DataFrame): DataFrame containing 'Item' and 'Location' columns.\\n    - items (list of str, optional): Specific items to include in the chart. Defaults to a predefined list\\n      ['apple', 'banana', 'grape', 'orange', 'pineapple'] if None.\\n    - locations (list of str, optional): Specific locations to include in the chart. Defaults to a predefined\\n      list ['store1', 'store2', 'store3', 'store4', 'store5'] if None.\\n\\n    Returns:\\n    - matplotlib.axes.Axes: Axes object with the plotted bar chart.\\n\\n    Raises:\\n    - ValueError: If 'df' is not a DataFrame, or if 'Item' or 'Location' columns are missing.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> df = pd.DataFrame({\\n    ...     'Item': ['apple', 'banana', 'apple', 'orange'],\\n    ...     'Location': ['store1', 'store2', 'store3', 'store1']\\n    ... })\\n    >>> ax = task_func(df)\\n    >>> ax.get_title()\\n    'Item Distribution by Location'\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a bar chart representing the distribution of specified items across given locations. The function takes a DataFrame with 'Item' and 'Location' columns and plots the count of each item per location. If lists of items and locations are provided, the chart will only include those specified, otherwise it defaults to a predefined list.\\nThe function should raise the exception for: ValueError: If 'df' is not a DataFrame, or if 'Item' or 'Location' columns are missing.\\nThe function should output with:\\n    matplotlib.axes.Axes: Axes object with the plotted bar chart.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\ndef task_func(df, items=None, locations=None):\\n```\",\"libs\":\"['pandas', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}