BigCodeBench / BigCodeBench v0.1.0_hf 3b816f85-dedd-53ed-b1c0-60354b5fdc38

complete prompt

import pandas as pd
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt


def task_func(data):
    """
    Normalizes a given dataset using MinMax scaling and calculates the average of each row. This average is then
    added as a new column 'Average' to the resulting DataFrame. The function also visualizes these averages in a plot.

    Parameters:
    data (numpy.array): A 2D array where each row represents a sample and each column a feature, with a
    shape of (n_samples, 8).

    Returns:
    DataFrame: A pandas DataFrame where data is normalized, with an additional column 'Average' representing the
    mean of each row.
    Axes: A matplotlib Axes object showing a bar subplot of the average values across the dataset.

    Requirements:
    - pandas
    - sklearn
    - 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.round(2))
         A    B    C    D    E    F    G    H  Average
    0  0.0  0.0  0.0  0.0  1.0  0.0  1.0  0.0     0.25
    1  1.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0     0.25
    """

instruct prompt

Normalizes a given dataset using MinMax scaling and calculates the average of each row. This average is then added as a new column 'Average' to the resulting DataFrame. The function also visualizes these averages in a plot.
The function should output with:
    DataFrame: A pandas DataFrame where data is normalized, with an additional column 'Average' representing the
    mean of each row.
    Axes: A matplotlib Axes object showing a bar subplot of the average values across the dataset.
You should write self-contained code starting with:

Code

import pandas as pd
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt
def task_func(data):

code prompt

Code

import pandas as pd
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt
def task_func(data):

entry point

task_func

libs

• pandas
• matplotlib
• sklearn