BigCodeBench / BigCodeBench v0.1.0_hf 670b3a27-c567-5af3-b221-ad2fac34aa83

complete prompt

import pandas as pd
import matplotlib.pyplot as plt

# Constants
COLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']


def task_func(data):
    """
    Computes the average of each row in a provided 2D array and appends these averages as a new column.
    Additionally, it plots the averages against their respective row indices.

    Parameters:
    data (numpy.array): A 2D numpy array with exactly eight columns, corresponding to 'A' through 'H'.

    Returns:
    tuple: A tuple containing:
        - DataFrame: A pandas DataFrame which includes the original data and an additional 'Average' column.
        - Axes: A matplotlib Axes object with the plot of row averages.

    Requirements:
    - pandas
    - matplotlib

    Example:
    >>> import numpy as np
    >>> data = np.array([[1, 2, 3, 4, 4, 3, 7, 1], [6, 2, 3, 4, 3, 4, 4, 1]])
    >>> df, ax = task_func(data)
    >>> print(df.to_string(index=False))
     A  B  C  D  E  F  G  H  Average
     1  2  3  4  4  3  7  1    3.125
     6  2  3  4  3  4  4  1    3.375
    """

instruct prompt

Computes the average of each row in a provided 2D array and appends these averages as a new column. Additionally, it plots the averages against their respective row indices.
The function should output with:
    tuple: A tuple containing:
    DataFrame: A pandas DataFrame which includes the original data and an additional 'Average' column.
    Axes: A matplotlib Axes object with the plot of row averages.
You should write self-contained code starting with:

Code

import pandas as pd
import matplotlib.pyplot as plt
# Constants
COLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']
def task_func(data):

code prompt

Code

import pandas as pd
import matplotlib.pyplot as plt
# Constants
COLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']
def task_func(data):

entry point

task_func

libs

• pandas
• matplotlib