BigCodeBench / BigCodeBench v0.1.0_hf c3d6f133-900b-509a-992a-73606f3a4460

complete prompt

import pandas as pd
import numpy as np
import itertools
from datetime import datetime, timedelta
import seaborn as sns

def task_func(df, fruits=None, days=None, seed=None, sales_lower_bound=1, sales_upper_bound=50):
    """
    Appends randomly generated sales data for specified fruits over a given range of days to a DataFrame, 
    and returns a seaborn boxplot of the sales.

    Parameters:
    - df (pd.DataFrame): Initial Empty DataFrame to append sales data to. Must be empty. 
    - fruits (List[str], optional): List of fruits for sales data. Defaults to ['Apple', 'Banana', 'Cherry', 'Date', 'Elderberry'].
    - days (List[datetime], optional): List of days for sales data. Defaults to the range from January 1, 2024, to January 7, 2024.
    - seed (int, optional): Seed for the random number generator. Defaults to None.
    - sales_lower_bound (int, optional): Lower bound for random sales values. Defaults to 1.
    - sales_upper_bound (int, optional): Upper bound for random sales values. Defaults to 50.

    Returns:
    Tuple[pd.DataFrame, sns.axisgrid.FacetGrid]: Updated DataFrame with sales data and a seaborn boxplot of the sales.

    Raises:
    TypeError: If 'df' is not a pandas DataFrame.
    ValueError: If 'df' is not empty or  If 'sales_lower_bound' is not less than 'sales_upper_bound'.

    Requirements:
    - pandas 
    - numpy
    - itertools
    - datetime
    - seaborn

    Example:
    >>> initial_df = pd.DataFrame()
    >>> report_df, plot = task_func(initial_df, seed=42)
    >>> print(report_df.head())
       Fruit        Day  Sales
    0  Apple 2024-01-01     39
    1  Apple 2024-01-02     29
    2  Apple 2024-01-03     15
    3  Apple 2024-01-04     43
    4  Apple 2024-01-05      8
    >>> plot.figure.show()

    """

instruct prompt

Appends randomly generated sales data for specified fruits over a given range of days to a DataFrame, and returns a seaborn boxplot of the sales.
The function should raise the exception for: TypeError: If 'df' is not a pandas DataFrame. ValueError: If 'df' is not empty or  If 'sales_lower_bound' is not less than 'sales_upper_bound'.
The function should output with:
    Tuple[pd.DataFrame, sns.axisgrid.FacetGrid]: Updated DataFrame with sales data and a seaborn boxplot of the sales.
You should write self-contained code starting with:

Code

import pandas as pd
import numpy as np
import itertools
from datetime import datetime, timedelta
import seaborn as sns
def task_func(df, fruits=None, days=None, seed=None, sales_lower_bound=1, sales_upper_bound=50):

code prompt

Code

import pandas as pd
import numpy as np
import itertools
from datetime import datetime, timedelta
import seaborn as sns
def task_func(df, fruits=None, days=None, seed=None, sales_lower_bound=1, sales_upper_bound=50):

entry point

task_func

libs

• pandas
• itertools
• numpy
• seaborn
• datetime