BigCodeBench / BigCodeBench v0.1.0_hf e3841028-f1ab-55de-8e1c-b17e0c226465

complete prompt

import pandas as pd
import seaborn as sns


def task_func(data):
    """
    Analyze a dataset by calculating the average of values across each row and visualizing the correlation matrix as a
    heatmap.

    Parameters:
    data (numpy.array): 2D array where each row represents a record and each column represents a feature

    Returns:
    tuple: A tuple containing:
        - DataFrame: A pandas DataFrame enhanced with an 'Average' column that represents the mean across each row.
        - Axes: The matplotlib Axes object showing the heatmap of the correlations.

    Requirements:
    - pandas
    - numpy
    - seaborn

    Raises:
    ValueError: If the input data is not a 2D array or if it contains non-numeric data.

    Example:
    >>> data = np.array([[1, 2, 3, 4, 5, 6, 7, 8], [8, 7, 6, 5, 4, 3, 2, 1]])
    >>> df, ax = task_func(data)
    >>> print(df['Average'].to_string(index=False))
    4.5
    4.5
    """

instruct prompt

Analyze a dataset by calculating the average of values across each row and visualizing the correlation matrix as a heatmap.
The function should raise the exception for: ValueError: If the input data is not a 2D array or if it contains non-numeric data.
The function should output with:
    tuple: A tuple containing:
    DataFrame: A pandas DataFrame enhanced with an 'Average' column that represents the mean across each row.
    Axes: The matplotlib Axes object showing the heatmap of the correlations.
You should write self-contained code starting with:

Code

import pandas as pd
import seaborn as sns
def task_func(data):

code prompt

Code

import pandas as pd
import seaborn as sns
def task_func(data):

entry point

task_func

libs

• pandas
• seaborn