{"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":"0b5041a1-860c-5389-9581-21c6154aa74d","task_key":"default--v0~2e1~2e0~5fhf--0b5041a1-860c-5389-9581-21c6154aa74d","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 0b5041a1-860c-5389-9581-21c6154aa74d","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import requests\\nimport json\\nimport pandas as pd\\nimport seaborn as sns\\n# Constants\\nHEADERS = {\\n    'accept': 'application/json'\\n}\\ndef task_func(url, parameters):\\n\",\"complete_prompt\":\"import requests\\nimport json\\nimport pandas as pd\\nimport seaborn as sns\\n\\n# Constants\\nHEADERS = {\\n    'accept': 'application/json'\\n}\\n\\ndef task_func(url, parameters):\\n    \\\"\\\"\\\"\\n    Retrieve data from a specific API endpoint with the provided parameters, \\n    convert the data into a pandas dataframe, and draw a heatmap to show \\n    the correlation between numerical characteristics. The heatmap is \\n    displayed and also returned for further use or testing.\\n\\n    Parameters:\\n    url (str): The API endpoint URL.\\n    parameters (dict): The parameters to be sent with the GET request.\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: The pandas DataFrame containing the data.\\n        - Axes: The matplotlib Axes object of the heatmap.\\n\\n    Raises:\\n    - Thif function will raise a general Expection if the url is invalid, empty data, invalid data, and url cannot be accessed.\\n\\n    Requirements:\\n    - requests\\n    - json\\n    - pandas\\n    - seaborn\\n\\n    Example:\\n    >>> df, ax = task_func('https://api.example.com/data', {'param1': 'value1'})\\n    >>> df.iloc[0]['data']\\n    1\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Retrieve data from a specific API endpoint with the provided parameters, convert the data into a pandas dataframe, and draw a heatmap to show the correlation between numerical characteristics. The heatmap is displayed and also returned for further use or testing.\\nThe function should raise the exception for: Thif function will raise a general Expection if the url is invalid, empty data, invalid data, and url cannot be accessed.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: The pandas DataFrame containing the data.\\n    Axes: The matplotlib Axes object of the heatmap.\\nYou should write self-contained code starting with:\\n```\\nimport requests\\nimport json\\nimport pandas as pd\\nimport seaborn as sns\\n# Constants\\nHEADERS = {\\n    'accept': 'application/json'\\n}\\ndef task_func(url, parameters):\\n```\",\"libs\":\"['pandas', 'json', 'requests', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}