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BigCodeBench / BigCodeBench v0.1.0_hf dc927588-5737-52db-8779-3f83076e534b

Problem

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

complete prompt

import pandas as pd
import seaborn as sns
from sklearn.preprocessing import StandardScaler


def task_func(df1, df2):
    """
    Merge two dataframes on the 'id' column and then scale the numeric features.

    This function merges two dataframes via outer join on the 'id' column, and scales the merged dataframe's
    numeric features from df1 to have a mean of 0 and standard deviation of 1. It also returns a pair plot of
    the scaled features from df1.

    Parameters:
    - df1 (pd.DataFrame): Left dataframe to merge into.
    - df2 (pd.DataFrame): Right dataframe to merge from.

    Returns:
    - merged_df (pd.DataFrame): The partially scaled and merged dataframe.
    - pair_plot (seaborn.axisgrid.PairGrid): Pair plot of the scaled dataframe.

    Requirements:
    - pandas
    - sklearn
    - seaborn

    Example:
    >>> df1 = pd.DataFrame({'id': [1, 2, 3], 'feature1': [1.2, 3.4, 5.6], 'feature2': [2.3, 4.5, 6.7]})
    >>> df2 = pd.DataFrame({'id': [1, 2, 3], 'feature4': [4.5, 6.7, 8.9], 'feature5': [5.6, 7.8, 9.0]})
    >>> scaled_df, plot = task_func(df1, df2)
    >>> scaled_df
       id  feature1  feature2  feature4  feature5
    0   1 -1.224745 -1.224745       4.5       5.6
    1   2  0.000000  0.000000       6.7       7.8
    2   3  1.224745  1.224745       8.9       9.0
    >>> type(scaled_df)
    <class 'pandas.core.frame.DataFrame'>
    >>> type(plot)
    <class 'seaborn.axisgrid.PairGrid'>
    """

instruct prompt

Merge two dataframes on the 'id' column and then scale the numeric features. This function merges two dataframes via outer join on the 'id' column, and scales the merged dataframe's numeric features from df1 to have a mean of 0 and standard deviation of 1. It also returns a pair plot of the scaled features from df1.
The function should output with:
    merged_df (pd.DataFrame): The partially scaled and merged dataframe.
    pair_plot (seaborn.axisgrid.PairGrid): Pair plot of the scaled dataframe.
You should write self-contained code starting with:

Code

import pandas as pd
import seaborn as sns
from sklearn.preprocessing import StandardScaler
def task_func(df1, df2):

code prompt

Code

import pandas as pd
import seaborn as sns
from sklearn.preprocessing import StandardScaler
def task_func(df1, df2):

entry point

task_func

libs

  • pandas
  • sklearn
  • seaborn

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Source and history

task_id
dc927588-5737-52db-8779-3f83076e534b
task_key
default--v0~2e1~2e0~5fhf--dc927588-5737-52db-8779-3f83076e534b
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import