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BigCodeBench / BigCodeBench v0.1.0_hf 2a51e3b0-29ab-5f8f-ba5d-82cfb93dc342
Problem
Answer published by the source. Consult the official source to check your work against its answer.
complete prompt
import pandas as pd
import numpy as np
def task_func(test_scores, student):
"""
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.
Parameters:
test_scores (dictionary): The dictionary containing keys 'Student' and 'Score'.
The Student values are of dtype int and contain student IDs. The Score
values are of dtype float.
student (int): The specific student ID for which the average score needs to be calculated.
Returns:
np.array([float, float]): A numpy array containing the average score and the standard deviation for the student.
DataFrame: the converted dictionary.
Raises:
ValueError: student is not present in the test_scores dataframe
Requirements:
- pandas
- numpy
Example:
>>> STUDENTS = range(1, 101)
>>> np.random.seed(10)
>>> scores = {'Student': list(np.random.choice(STUDENTS, 50, replace=True)),
... 'Score': np.random.randint(50, 101, size=50)}
>>> task_func(scores, 10)
(array([70. , 7.07106781]), Student Score
0 10 65
1 16 68
2 65 66
3 29 57
4 90 74
5 94 61
6 30 67
7 9 96
8 74 57
9 1 61
10 41 78
11 37 83
12 17 70
13 12 82
14 55 74
15 89 94
16 63 55
17 34 54
18 73 57
19 79 74
20 50 74
21 52 100
22 55 94
23 78 84
24 70 90
25 14 65
26 26 63
27 14 74
28 93 65
29 87 56
30 31 71
31 31 92
32 90 72
33 13 61
34 66 98
35 32 62
36 58 78
37 37 82
38 28 99
39 19 65
40 94 94
41 78 90
42 23 92
43 24 95
44 95 93
45 12 83
46 29 100
47 75 95
48 89 90
49 10 75)
>>> 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)
"""
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)
The function should raise the exception for: ValueError: student is not present in the test_scores dataframe
The function should output with:
np.array([float, float]): A numpy array containing the average score and the standard deviation for the student.
DataFrame: the converted dictionary.
You should write self-contained code starting with:
Code
import pandas as pd
import numpy as np
def task_func(test_scores, student):
code prompt
Code
import pandas as pd
import numpy as np
def task_func(test_scores, student):
entry point
task_func
libs
- pandas
- numpy
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initial import