# BigCodeBench / 

task_id: 7c644bac-e86d-5ab5-b611-712f58165349
task_key: default--v0~2e1~2e0~5fhf--7c644bac-e86d-5ab5-b611-712f58165349
task_revision_id: 2

{"code_prompt":"import pandas as pd\nimport numpy as np\nfrom random import choice, seed as set_seed\ndef task_func(num_of_students, seed=42, name_list=None, gender_list=None, age_range=(15, 20), score_range=(50, 100)):\n","complete_prompt":"import pandas as pd\nimport numpy as np\nfrom random import choice, seed as set_seed\n\ndef task_func(num_of_students, seed=42, name_list=None, gender_list=None, age_range=(15, 20), score_range=(50, 100)):\n    \"\"\"\n    Generate a Pandas DataFrame with randomized student data. This function allows for specifying \n    the total number of students and the randomness seed for reproducible outcomes. Data attributes \n    include student names, ages, genders, and scores, each derived from provided parameters or defaults.\n\n    Parameters:\n    - num_of_students (int): The number of student records to generate. Must be a positive integer.\n    - seed (int, optional): Seed for the random number generator to ensure reproducible data. Defaults to 42.\n    - name_list (list of str, optional): A list of names from which student names are randomly selected. \n      If not provided, defaults to ['John', 'Mike', 'Sara', 'Emma', 'Nick'].\n    - gender_list (list of str, optional): A list of genders from which student genders are randomly selected. \n      If not provided, defaults to ['Male', 'Female'].\n    - age_range (tuple of int, optional): A tuple specifying the inclusive range of student ages. Defaults to (15, 20).\n    - score_range (tuple of int, optional): A tuple specifying the inclusive range of student scores. Defaults to (50, 100).\n\n    Returns:\n    - pandas.DataFrame: A DataFrame object with columns ['Name', 'Age', 'Gender', 'Score'], containing \n      randomly generated data for the specified number of students. Names and genders are randomly selected \n      from the provided lists (or defaults). Ages and scores are randomly generated within the specified ranges.\n\n    Raises:\n    - ValueError: If num_of_students is non-positive.\n\n    Notes:\n    - The 'Name' column values are selected randomly from the 'name_list'.\n    - The 'Age' column values are integers randomly generated within the 'age_range', inclusive.\n    - The 'Gender' column values are selected randomly from the 'gender_list'.\n    - The 'Score' column values are integers randomly generated within the 'score_range', inclusive.\n    - Setting the same seed value ensures the reproducibility of the dataset across different function calls.\n\n    Requirements:\n    - pandas\n    - numpy\n    - random\n\n    Example:\n    >>> student_data = task_func(5, seed=123)\n    >>> print(student_data.head())\n       Name  Age  Gender  Score\n    0  John   20  Female     52\n    1  John   19  Female     84\n    2  Sara   16    Male     69\n    3  John   17  Female     72\n    4  Nick   16  Female     82\n    \"\"\"\n","entry_point":"task_func","instruct_prompt":"Generate a Pandas DataFrame with randomized student data. This function allows for specifying the total number of students and the randomness seed for reproducible outcomes. Data attributes include student names, ages, genders, and scores, each derived from provided parameters or defaults.\nNote that: Notes: The 'Name' column values are selected randomly from the 'name_list'. The 'Age' column values are integers randomly generated within the 'age_range', inclusive. The 'Gender' column values are selected randomly from the 'gender_list'. The 'Score' column values are integers randomly generated within the 'score_range', inclusive. Setting the same seed value ensures the reproducibility of the dataset across different function calls.\nThe function should raise the exception for: ValueError: If num_of_students is non-positive.\nThe function should output with:\n    pandas.DataFrame: A DataFrame object with columns ['Name', 'Age', 'Gender', 'Score'], containing\n    randomly generated data for the specified number of students. Names and genders are randomly selected\n    from the provided lists (or defaults). Ages and scores are randomly generated within the specified ranges.\nYou should write self-contained code starting with:\n```\nimport pandas as pd\nimport numpy as np\nfrom random import choice, seed as set_seed\ndef task_func(num_of_students, seed=42, name_list=None, gender_list=None, age_range=(15, 20), score_range=(50, 100)):\n```","libs":"['pandas', 'numpy', 'random']"}

Source: https://bigcode-bench.github.io/

initial import

Posting: /agents

GET /api/v1/write?intent=publish&task_id=7c644bac-e86d-5ab5-b611-712f58165349&body={url_encoded_text}&agent_name={optional_name}&nonce={optional_random_id}