{"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":"2a51e3b0-29ab-5f8f-ba5d-82cfb93dc342","task_key":"default--v0~2e1~2e0~5fhf--2a51e3b0-29ab-5f8f-ba5d-82cfb93dc342","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2a51e3b0-29ab-5f8f-ba5d-82cfb93dc342","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(test_scores, student):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(test_scores, student):\\n    \\\"\\\"\\\"\\n    Convert a dictionary of test results into a pandas DataFrame and\\n    Calculate the average test score and the standard deviation for a particular student from this DataFrame.\\n    \\n    Parameters:\\n    test_scores (dictionary): The dictionary containing keys 'Student' and 'Score'.\\n        The Student values are of dtype int and contain student IDs. The Score \\n        values are of dtype float.\\n    student (int): The specific student ID for which the average score needs to be calculated.\\n    \\n    Returns:\\n    np.array([float, float]): A numpy array containing the average score and the standard deviation for the student.\\n    DataFrame: the converted dictionary.\\n\\n    Raises:\\n    ValueError: student is not present in the test_scores dataframe\\n                \\n    Requirements:\\n    - pandas\\n    - numpy\\n    \\n    Example:\\n    >>> STUDENTS = range(1, 101)\\n    >>> np.random.seed(10)\\n    >>> scores = {'Student': list(np.random.choice(STUDENTS, 50, replace=True)), \\n    ...                        'Score': np.random.randint(50, 101, size=50)}\\n    >>> task_func(scores, 10)\\n    (array([70.        ,  7.07106781]),     Student  Score\\n    0        10     65\\n    1        16     68\\n    2        65     66\\n    3        29     57\\n    4        90     74\\n    5        94     61\\n    6        30     67\\n    7         9     96\\n    8        74     57\\n    9         1     61\\n    10       41     78\\n    11       37     83\\n    12       17     70\\n    13       12     82\\n    14       55     74\\n    15       89     94\\n    16       63     55\\n    17       34     54\\n    18       73     57\\n    19       79     74\\n    20       50     74\\n    21       52    100\\n    22       55     94\\n    23       78     84\\n    24       70     90\\n    25       14     65\\n    26       26     63\\n    27       14     74\\n    28       93     65\\n    29       87     56\\n    30       31     71\\n    31       31     92\\n    32       90     72\\n    33       13     61\\n    34       66     98\\n    35       32     62\\n    36       58     78\\n    37       37     82\\n    38       28     99\\n    39       19     65\\n    40       94     94\\n    41       78     90\\n    42       23     92\\n    43       24     95\\n    44       95     93\\n    45       12     83\\n    46       29    100\\n    47       75     95\\n    48       89     90\\n    49       10     75)\\n\\n    >>> scores = {'Student': [1, 2, 1, 1], 'Score': [10, 1, 1, 1]}\\n    >>> task_func(scores, 1)\\n    (array([4.        , 5.19615242]),    Student  Score\\n    0        1     10\\n    1        2      1\\n    2        1      1\\n    3        1      1)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Convert a dictionary of test results into a pandas DataFrame and Calculate the average test score and the standard deviation for a particular student from this DataFrame. >>> scores = {'Student': [1, 2, 1, 1], 'Score': [10, 1, 1, 1]} >>> task_func(scores, 1) (array([4.        , 5.19615242]),    Student  Score 0        1     10 1        2      1 2        1      1 3        1      1)\\nThe function should raise the exception for: ValueError: student is not present in the test_scores dataframe\\nThe function should output with:\\n    np.array([float, float]): A numpy array containing the average score and the standard deviation for the student.\\n    DataFrame: the converted dictionary.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(test_scores, student):\\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":[]}