{"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":"cf2e71c0-3f38-57f9-99e5-537077a65336","task_key":"default--v0~2e1~2e0~5fhf--cf2e71c0-3f38-57f9-99e5-537077a65336","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf cf2e71c0-3f38-57f9-99e5-537077a65336","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\ndef task_func(s1, s2):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(s1, s2):\\n    \\\"\\\"\\\"\\n    Visualize two Series using a swarm plot with a highlight on their intersecting data points.\\n\\n    This function creates a swarm plot to visually compare two pandas Series. \\n    It highlights the intersection points between these two series by drawing red dashed lines at the intersecting data points.\\n\\n    Parameters:\\n    - s1 (pd.Series): The first series of data. This series must have a unique name that identifies it in the plot.\\n    - s2 (pd.Series): The second series of data. Similar to s1, this series must also have a unique name.\\n\\n    Returns:\\n    - ax (matplotlib.Axes): The Axes object of the plotted swarm chart. This object can be used for further customization of the plot if required.\\n    intersection_count (int): The number of unique intersecting data points between s1 and s2. \\n    This count gives a quick numerical summary of the overlap between the two series.\\n\\n    Requirements:\\n    - pandas\\n    - seaborn\\n    - matplotlib\\n\\n    Example:\\n    >>> s1 = pd.Series([1, 2, 3, 4, 5], name='Series1')\\n    >>> s2 = pd.Series([4, 5, 6, 7, 8], name='Series2')\\n    >>> ax, count = task_func(s1, s2)\\n    >>> ax.get_title()\\n    'Overlap Between Series1 and Series2'\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Visualize two Series using a swarm plot with a highlight on their intersecting data points. This function creates a swarm plot to visually compare two pandas Series. It highlights the intersection points between these two series by drawing red dashed lines at the intersecting data points.\\nThe function should output with:\\n    ax (matplotlib.Axes): The Axes object of the plotted swarm chart. This object can be used for further customization of the plot if required.\\n    intersection_count (int): The number of unique intersecting data points between s1 and s2.\\n    This count gives a quick numerical summary of the overlap between the two series.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\ndef task_func(s1, s2):\\n```\",\"libs\":\"['pandas', 'matplotlib', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}