{"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":"814e6b46-337a-5596-a258-9c5b908ec066","task_key":"default--v0~2e1~2e0~5fhf--814e6b46-337a-5596-a258-9c5b908ec066","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 814e6b46-337a-5596-a258-9c5b908ec066","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(rows=100, columns=3):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(rows=100, columns=3):\\n    \\\"\\\"\\\"\\n    Create a Pandas DataFrame with random alphabets in each cell.\\n    The DataFrame will have a specified number of rows and columns.\\n    Each column is named with a string from the list ['a', 'b', 'c', ...]\\n    depending on the number of columns specified.\\n\\n    Parameters:\\n    - rows (int, optional): Number of rows in the DataFrame. Defaults to 100.\\n    - columns (int, optional): Number of columns in the DataFrame. Defaults to 3.\\n\\n    Returns:\\n    DataFrame: A pandas DataFrame with random alphabets.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Example:\\n    >>> np.random.seed(0)\\n    >>> df = task_func(5, 3)\\n    >>> print(df)\\n       a  b  c\\n    0  m  p  v\\n    1  a  d  d\\n    2  h  j  t\\n    3  v  s  e\\n    4  x  g  y\\n    >>> df['a'].value_counts()\\n    a\\n    m    1\\n    a    1\\n    h    1\\n    v    1\\n    x    1\\n    Name: count, dtype: int64\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Create a Pandas DataFrame with random alphabets in each cell. The DataFrame will have a specified number of rows and columns. Each column is named with a string from the list ['a', 'b', 'c', ...] depending on the number of columns specified.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with random alphabets.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(rows=100, columns=3):\\n```\",\"libs\":\"['pandas', 'numpy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}