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BigCodeBench / BigCodeBench v0.1.0_hf 244b2b50-c634-5442-b612-60acb7a145a7

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats

# Constants
TARGET_VALUE = '332'
ARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])


def task_func(target_value=TARGET_VALUE, array=ARRAY):
    """
    Finds the row indices in a numpy array where the first cell matches target_value "332"
    Performs statistical analysis on these indices and plots their distribution.
    Return 'N/A' for all stats if no target value found.

    Parameters:
    - target_value (str): The target value. Default value is '332'
    - array (np.ndarray): The input array

    Returns:
    tuple: A tuple with mean, variance, skewness, and kurtosis of the indices, or
           'N/A' if statistical analysis cannot be performed.

    Requirements:
    - numpy
    - scipy.stats
    - matplotlib.pyplot

    Example:
    >>> task_func()
    (2.0, 'N/A', 'N/A', 'N/A')
    """

instruct prompt

Finds the row indices in a numpy array where the first cell matches target_value "332" Performs statistical analysis on these indices and plots their distribution. Return 'N/A' for all stats if no target value found.
The function should output with:
    tuple: A tuple with mean, variance, skewness, and kurtosis of the indices, or
    'N/A' if statistical analysis cannot be performed.
You should write self-contained code starting with:

Code

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
# Constants
TARGET_VALUE = '332'
ARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])
def task_func(target_value=TARGET_VALUE, array=ARRAY):

code prompt

Code

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
# Constants
TARGET_VALUE = '332'
ARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])
def task_func(target_value=TARGET_VALUE, array=ARRAY):

entry point

task_func

libs

  • numpy
  • matplotlib
  • scipy

Discussion

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Source and history

task_id
244b2b50-c634-5442-b612-60acb7a145a7
task_key
default--v0~2e1~2e0~5fhf--244b2b50-c634-5442-b612-60acb7a145a7
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import