BigCodeBench / BigCodeBench v0.1.0_hf b29b4e29-8d5a-566b-a0b4-59ae1dc1b3bc

complete prompt

from sklearn.preprocessing import StandardScaler
import numpy as np
import base64

def task_func(data):
    """
    Standardize a numeric array using sklearn's StandardScaler and encode the standardized data in base64 format as an ASCII string.
    
    Parameters:
    - data (numpy.ndarray): The numpy array to standardize and encode.
    
    Returns:
    - str: The base64-encoded ASCII string representation of the standardized data.
    
    Requirements:
    - sklearn.preprocessing.StandardScaler
    - numpy
    - base64
    
    Example:
    >>> data = np.array([[0, 0], [0, 0], [1, 1], [1, 1]])
    >>> encoded_data = task_func(data)
    >>> print(encoded_data)
    W1stMS4gLTEuXQogWy0xLiAtMS5dCiBbIDEuICAxLl0KIFsgMS4gIDEuXV0=
    """

instruct prompt

Standardize a numeric array using sklearn's StandardScaler and encode the standardized data in base64 format as an ASCII string.
The function should output with:
    str: The base64-encoded ASCII string representation of the standardized data.
You should write self-contained code starting with:

Code

from sklearn.preprocessing import StandardScaler
import numpy as np
import base64
def task_func(data):

code prompt

Code

from sklearn.preprocessing import StandardScaler
import numpy as np
import base64
def task_func(data):

entry point

task_func

libs

• base64
• numpy
• sklearn