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BigCodeBench / BigCodeBench v0.1.0_hf fa8ee0db-b754-5b36-b428-d2ce0059c14a

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler


def task_func(df):
    """
    Plots the correlation matrix from numeric columns in a DataFrame and returns a DataFrame
    where the numeric columns are standardized to have mean 0 and variance 1.

    Parameters:
    df (pandas.DataFrame): Input DataFrame with columns of numeric data.

    Returns:
    pandas.DataFrame: Standardized DataFrame.
    matplotlib.figure.Figure: Figure object containing the heatmap of the correlation matrix.

    Requirements:
    - pandas
    - numpy
    - seaborn
    - matplotlib
    - sklearn

    Raises:
    - ValueError: If the DataFrame is empty or if no numeric columns are present.

    Notes:
    - Only numeric columns are considered for the heatmap. Non-numeric columns are ignored.

    Examples:
    >>> import pandas as pd
    >>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
    >>> standardized_df, fig = task_func(df)
    >>> standardized_df
              A         B
    0 -1.224745 -1.224745
    1  0.000000  0.000000
    2  1.224745  1.224745
    >>> type(fig)
    <class 'matplotlib.figure.Figure'>
    """

instruct prompt

Plots the correlation matrix from numeric columns in a DataFrame and returns a DataFrame where the numeric columns are standardized to have mean 0 and variance 1.
Note that: Notes: Only numeric columns are considered for the heatmap. Non-numeric columns are ignored.
The function should raise the exception for: ValueError: If the DataFrame is empty or if no numeric columns are present.
The function should output with:
    pandas.DataFrame: Standardized DataFrame.
    matplotlib.figure.Figure: Figure object containing the heatmap of the correlation matrix.
You should write self-contained code starting with:

Code

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
def task_func(df):

code prompt

Code

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
def task_func(df):

entry point

task_func

libs

  • sklearn
  • numpy
  • matplotlib
  • seaborn

Discussion

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Source and history

task_id
fa8ee0db-b754-5b36-b428-d2ce0059c14a
task_key
default--v0~2e1~2e0~5fhf--fa8ee0db-b754-5b36-b428-d2ce0059c14a
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import