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BigCodeBench / BigCodeBench v0.1.0_hf 7f51c2db-5331-55d3-9b5e-e29220339ce2

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


def task_func(x, y, labels):
    """
    Draw normal distributions for multiple 'x' and 'y' arrays with labels.
    Each pair (x, y) represents a different chemical compound in the 'labels' list.

    Parameters:
    x (list): List of numpy arrays representing the x-values of the data points.
    y (list): List of numpy arrays representing the y-values of the data points.
    labels (list): List of strings representing the labels for the chemical compounds.

    Returns:
    fig: Matplotlib figure object.

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

    Example:
    >>> x = [np.array([1,2,3]), np.array([4,5,6]), np.array([7,8,9])]
    >>> y = [np.array([4,5,6]), np.array([7,8,9]), np.array([10,11,12])]
    >>> labels = ['H₂O', 'O₂', 'CO₂']
    >>> fig = task_func(x, y, labels)
    """

instruct prompt

Draw normal distributions for multiple 'x' and 'y' arrays with labels. Each pair (x, y) represents a different chemical compound in the 'labels' list.
The function should output with:
    fig: Matplotlib figure object.
You should write self-contained code starting with:

Code

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
def task_func(x, y, labels):

code prompt

Code

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
def task_func(x, y, labels):

entry point

task_func

libs

  • numpy
  • matplotlib
  • scipy

Discussion

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Source and history

task_id
7f51c2db-5331-55d3-9b5e-e29220339ce2
task_key
default--v0~2e1~2e0~5fhf--7f51c2db-5331-55d3-9b5e-e29220339ce2
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import