{"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":"f9952138-48f6-5890-a570-93b5377a0e38","task_key":"default--v0~2e1~2e0~5fhf--f9952138-48f6-5890-a570-93b5377a0e38","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf f9952138-48f6-5890-a570-93b5377a0e38","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import collections\\nimport pandas as pd\\ndef task_func(my_tuple, path_csv_files):\\n\",\"complete_prompt\":\"import collections\\nimport pandas as pd\\n\\ndef task_func(my_tuple, path_csv_files):\\n    \\\"\\\"\\\"\\n    Count the occurrences of each value in the specified columns in multiple CSV files.\\n\\n    Parameters:\\n    my_tuple (tuple): The tuple of column names.\\n    path_csv_files (list of string): The list of csv files to read.\\n\\n    Returns:\\n    dict: A dictionary where keys are column names and values are dictionaries \\n        with unique values in the column as keys and their counts as values.\\n\\n    Requirements:\\n    - collections\\n    - pandas\\n\\n    Example:\\n    >>> from unittest.mock import MagicMock\\n    >>> import pandas as pd\\n    >>> df1 = pd.DataFrame({'Country': ['USA', 'Canada', 'USA'], 'Gender': ['Male', 'Female', 'Male']})\\n    >>> df2 = pd.DataFrame({'Country': ['UK', 'USA', 'Germany'], 'Gender': ['Male', 'Male', 'Female']})\\n    >>> pd.read_csv = MagicMock(side_effect=[df1, df2])\\n    >>> result = task_func(('Country', 'Gender'), ['file1.csv', 'file2.csv'])\\n    >>> print(result['Country'])\\n    Counter({'USA': 3, 'Canada': 1, 'UK': 1, 'Germany': 1})\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Count the occurrences of each value in the specified columns in multiple CSV files.\\nThe function should output with:\\n    dict: A dictionary where keys are column names and values are dictionaries\\n    with unique values in the column as keys and their counts as values.\\nYou should write self-contained code starting with:\\n```\\nimport collections\\nimport pandas as pd\\ndef task_func(my_tuple, path_csv_files):\\n```\",\"libs\":\"['pandas', 'collections']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}