{"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":"noindex","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[]}},"task_id":"e88fafd7-f6f9-552e-97f5-05f7f5f7d858","task_key":"default--v0~2e1~2e0~5fhf--e88fafd7-f6f9-552e-97f5-05f7f5f7d858","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf e88fafd7-f6f9-552e-97f5-05f7f5f7d858","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport sqlite3\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport ast\\ndef task_func(db_file):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport sqlite3\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport ast\\n\\ndef task_func(db_file):\\n    \\\"\\\"\\\"\\n    Load e-mail data from an SQLite database and convert it into a Pandas DataFrame. \\n    Calculate the sum, mean, and variance of the list associated with each e-mail and then record these values.\\n\\n    - The function expects the SQLite database to have a table named \\\"EmailData\\\" with columns 'email' and 'list'.\\n    - The column 'list' contains a string representation of the list. It should be converted before usage.\\n    - The function will return a DataFrame with additional columns 'sum', 'mean', and 'var' representing the calculated sum, mean, and variance respectively for each e-mail.\\n\\n    Parameters:\\n    - db_file (str): The path to the SQLite database file.\\n\\n    Returns:\\n    - tuple: A tuple containing:\\n      - DataFrame: A pandas DataFrame with email data including the calculated sum, mean, and variance.\\n      - Axes: A matplotlib Axes object representing the plotted bar chart of sum, mean, and variance.\\n\\n    Requirements:\\n    - pandas\\n    - sqlite3\\n    - numpy\\n    - matplotlib.pyplot\\n    - ast\\n\\n    Example:\\n    >>> df, ax = task_func('data/task_func/db_1.db')\\n    >>> print(df)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Load e-mail data from an SQLite database and convert it into a Pandas DataFrame. Calculate the sum, mean, and variance of the list associated with each e-mail and then record these values. - The function expects the SQLite database to have a table named \\\"EmailData\\\" with columns 'email' and 'list'. - The column 'list' contains a string representation of the list. It should be converted before usage. - The function will return a DataFrame with additional columns 'sum', 'mean', and 'var' representing the calculated sum, mean, and variance respectively for each e-mail.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: A pandas DataFrame with email data including the calculated sum, mean, and variance.\\n    Axes: A matplotlib Axes object representing the plotted bar chart of sum, mean, and variance.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport sqlite3\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nimport ast\\ndef task_func(db_file):\\n```\",\"libs\":\"['ast', 'pandas', 'matplotlib', 'numpy', 'sqlite3']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}