BigCodeBench / BigCodeBench v0.1.0_hf a1a1c822-df52-5584-9e5f-c9f7ab5cc1dd

complete prompt

import re
import matplotlib.pyplot as plt
from sklearn.feature_extraction.text import TfidfVectorizer
import numpy as np


def task_func(df):
    """
    Analyzes a given DataFrame containing article titles and content to identify articles with titles that include
    the words "how" or "what". It calculates the TF-IDF scores for the words in the content of these articles and
    visualizes these scores in a bar plot.

    Parameters:
    df (DataFrame): A DataFrame containing at least two columns: 'Title' and 'Content'.

    Returns:
    Axes: A matplotlib Axes object displaying a bar plot of the TF-IDF scores.

    Note:
    - If the DataFrame does not contain 'Title' and 'Content' columns, the function returns an empty plot.
    - If no articles have titles containing "how" or "what," the function also returns an empty plot.
    - Set the name of the y-axis to 'TF-IDF Score'.
    - Set xticks to display the feature names vertically.

    Requirements:
    - re
    - matplotlib
    - sklearn
    - numpy

    Example:
    >>> import pandas as pd
    >>> data = {'Title': ['How to make pancakes', 'News update'], 'Content': ['Pancakes are easy to make.', 'Today’s news is about politics.']}
    >>> df = pd.DataFrame(data)
    >>> ax = task_func(df)
    >>> type(ax)
    <class 'matplotlib.axes._axes.Axes'>
    """

instruct prompt

Analyzes a given DataFrame containing article titles and content to identify articles with titles that include the words "how" or "what". It calculates the TF-IDF scores for the words in the content of these articles and visualizes these scores in a bar plot.
Note that: If the DataFrame does not contain 'Title' and 'Content' columns, the function returns an empty plot. If no articles have titles containing "how" or "what," the function also returns an empty plot. Set the name of the y-axis to 'TF-IDF Score'. Set xticks to display the feature names vertically.
The function should output with:
    Axes: A matplotlib Axes object displaying a bar plot of the TF-IDF scores.
You should write self-contained code starting with:

Code

import re
import matplotlib.pyplot as plt
from sklearn.feature_extraction.text import TfidfVectorizer
import numpy as np
def task_func(df):

code prompt

Code

import re
import matplotlib.pyplot as plt
from sklearn.feature_extraction.text import TfidfVectorizer
import numpy as np
def task_func(df):

entry point

task_func

libs

• numpy
• matplotlib
• re
• sklearn