BigCodeBench / BigCodeBench v0.1.0_hf 7c148ef9-f9a5-5cb1-ab3c-ef067b2f7082

complete prompt

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np


def task_func(num_labels=5, data_range=(0, 1)):
    """
    Generate random numeric data across a specified range for a given number of categories and visualize it with
     a stacked bar chart.

    Parameters:
    num_labels (int): Specifies the number of distinct categories or labels to generate data for. Defaults to 5.
    data_range (tuple): Defines the lower and upper bounds for the random data values. Defaults to (0, 1).

    Returns:
    matplotlib.figure.Figure: A Figure object containing the stacked bar chart of the generated data.

    Requirements:
    - pandas
    - matplotlib
    - numpy

    Example:
    >>> fig = task_func()
    >>> fig.show()  # This will display the figure with default parameters

    >>> fig = task_func(num_labels=3, data_range=(1, 10))
    >>> fig.show()  # This will display the figure with three labels and data range from 1 to 10
    """

instruct prompt

Generate random numeric data across a specified range for a given number of categories and visualize it with a stacked bar chart. >>> fig = task_func(num_labels=3, data_range=(1, 10)) >>> fig.show()  # This will display the figure with three labels and data range from 1 to 10
The function should output with:
    matplotlib.figure.Figure: A Figure object containing the stacked bar chart of the generated data.
You should write self-contained code starting with:

Code

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
def task_func(num_labels=5, data_range=(0, 1)):

code prompt

Code

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
def task_func(num_labels=5, data_range=(0, 1)):

entry point

task_func

libs

• pandas
• numpy
• matplotlib