{"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":"53cdcc94-1f81-5e6e-b494-7e6ef2e24789","task_key":"default--v0~2e1~2e0~5fhf--53cdcc94-1f81-5e6e-b494-7e6ef2e24789","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 53cdcc94-1f81-5e6e-b494-7e6ef2e24789","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import statistics\\nimport matplotlib.pyplot as plt\\ndef task_func(sales_data):\\n\",\"complete_prompt\":\"import statistics\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(sales_data):\\n    \\\"\\\"\\\"\\n    Plot sales trends for five products over a year, highlighting variability with standard deviation shading\\n    with 'Month' on x-axis and 'Sales' on y-axis.\\n\\n    Parameters:\\n    - sales_data (pd.DataFrame): DataFrame with sales data, expected columns: 'Month', 'Product A' to 'Product E'.\\n\\n    Returns:\\n    - ax (matplotlib.axes.Axes): Axes object with the sales trends plot.\\n\\n    Requirements:\\n    - matplotlib.pyplot\\n    - statistics\\n\\n    Example:\\n    >>> import pandas as pd, numpy as np\\n    >>> sales_data = pd.DataFrame({\\n    ...     'Month': range(1, 13),\\n    ...     'Product A': np.random.randint(100, 200, size=12),\\n    ...     'Product B': np.random.randint(150, 250, size=12),\\n    ...     'Product C': np.random.randint(120, 220, size=12),\\n    ...     'Product D': np.random.randint(130, 230, size=12),\\n    ...     'Product E': np.random.randint(140, 240, size=12)\\n    ... })\\n    >>> ax = task_func(sales_data)\\n    >>> plt.show()  # Displays the plot\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Plot sales trends for five products over a year, highlighting variability with standard deviation shading with 'Month' on x-axis and 'Sales' on y-axis.\\nThe function should output with:\\n    ax (matplotlib.axes.Axes): Axes object with the sales trends plot.\\nYou should write self-contained code starting with:\\n```\\nimport statistics\\nimport matplotlib.pyplot as plt\\ndef task_func(sales_data):\\n```\",\"libs\":\"['statistics', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}