{"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":"42e6cc02-317f-51c5-bdf0-842ca9f4a5f9","task_key":"default--v0~2e1~2e0~5fhf--42e6cc02-317f-51c5-bdf0-842ca9f4a5f9","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 42e6cc02-317f-51c5-bdf0-842ca9f4a5f9","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import MinMaxScaler\\ndef task_func(file_name: str) -> pd.DataFrame:\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import MinMaxScaler\\n\\n\\ndef task_func(file_name: str) -> pd.DataFrame:\\n    \\\"\\\"\\\"Normalize data in a csv file using MinMaxScaler from sklearn.\\n    Only numeric columns are normalized. Columns with other dtypes are left as\\n    they are.\\n    \\n    Parameters:\\n    file_name (str): The name of the csv file.\\n    \\n    Returns:\\n    DataFrame: A pandas DataFrame with normalized data.\\n\\n    Raises:\\n    ValueError: If input does not have numeric columns.\\n\\n    Requirements:\\n    - pandas\\n    - sklearn.preprocessing.MinMaxScaler\\n    \\n    Example:\\n    >>> normalized_data = task_func(\\\"sample.csv\\\")\\n    >>> print(normalized_data.head())\\n    Name\\tAge\\tSalary\\n    0\\tAlex Anderson\\t0.304651\\t0.122298\\n    1\\tMr. Leslie Casey\\t0.28140\\t0.598905\\n    2\\tAnthony George\\t0.996744\\t0.216552\\n    3\\tBrian Washington\\t0.126279\\t0.459948\\n    4\\tElias Lawrence\\t0.337239\\t0.124185\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Normalize data in a csv file using MinMaxScaler from sklearn. Only numeric columns are normalized. Columns with other dtypes are left as they are.\\nThe function should raise the exception for: ValueError: If input does not have numeric columns.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with normalized data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom sklearn.preprocessing import MinMaxScaler\\ndef task_func(file_name: str) -> pd.DataFrame:\\n```\",\"libs\":\"['pandas', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}