BigCodeBench / BigCodeBench v0.1.0_hf 6241e9be-6da4-5637-9828-bda1701e1526

complete prompt

import pandas as pd
from random import randint, uniform, seed

def task_func(categories=None, months=None, random_seed=42):
    """
    Generates a DataFrame with simulated monthly sales data for various product categories, ensuring reproducibility through the use of a random seed.

    Parameters:
        categories (list of str, optional): A list specifying the product categories to include in the report. If not provided, defaults to ['Electronics', 'Clothing', 'Home & Kitchen', 'Books', 'Beauty & Personal Care'].
        months (list of str, optional): A list specifying the months to include in the report. If not provided, defaults to ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'].
        random_seed (int, optional): The seed value for the random number generator to ensure the reproducibility of the sales data. Defaults to 42.

    Returns:
        pandas.DataFrame: A DataFrame with three columns: 'Month', 'Category', and 'Sales'. The 'Sales' values are floating-point numbers in the range [100, 501), generated by the formula: randint(100, 500) + uniform(0, 1), ensuring sales values are diverse yet consistent upon repeated executions with the same seed.

    Raises:
        ValueError: If either 'categories' or 'months' is not provided as a list or if either is an empty list.

    Notes:
        - The function sets the random seed at the beginning of execution to ensure that the generated sales data is the same for any given seed value.
        - The sales data for each category is generated for each month, creating a comprehensive report that spans all specified categories and months.

    Requirements:
    - pandas 
    - random

    Example:
        >>> report = task_func()
        >>> print(report.head())
             Month                Category       Sales
        0  January             Electronics  427.111331
        1  January                Clothing  479.275029
        2  January          Home & Kitchen  214.139538
        3  January                   Books  152.676699
        4  January  Beauty & Personal Care  379.086939
    """

instruct prompt

Generates a DataFrame with simulated monthly sales data for various product categories, ensuring reproducibility through the use of a random seed.
Note that: Notes: The function sets the random seed at the beginning of execution to ensure that the generated sales data is the same for any given seed value. The sales data for each category is generated for each month, creating a comprehensive report that spans all specified categories and months.
The function should raise the exception for: ValueError: If either 'categories' or 'months' is not provided as a list or if either is an empty list.
The function should output with:
    pandas.DataFrame: A DataFrame with three columns: 'Month', 'Category', and 'Sales'. The 'Sales' values are floating-point numbers in the range [100, 501), generated by the formula: randint(100, 500) + uniform(0, 1), ensuring sales values are diverse yet consistent upon repeated executions with the same seed.
You should write self-contained code starting with:

Code

import pandas as pd
from random import randint, uniform, seed
def task_func(categories=None, months=None, random_seed=42):

code prompt

Code

import pandas as pd
from random import randint, uniform, seed
def task_func(categories=None, months=None, random_seed=42):

entry point

task_func

libs

• pandas
• random