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BigCodeBench / BigCodeBench v0.1.0_hf f23fe38e-665d-52a9-ace5-66a649a3215b

Problem

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

complete prompt

import pandas as pd
from sklearn.linear_model import LinearRegression

def task_func(d, target='z'):
    """
    Perform linear regression to "x," "y," against "z" from a list of dictionaries "d."

    Parameters:
    d (list): A list of dictionaries.
    target (str): The target variable for the regression.

    Returns:
    LinearRegression: A LinearRegression model.

    Requirements:
    - pandas
    - sklearn.linear_model.LinearRegression

    Examples:
    >>> data = [{'x': 1, 'y': 10, 'z': 5}, {'x': 3, 'y': 15, 'z': 6}, {'x': 2, 'y': 1, 'z': 7}]
    >>> model = task_func(data)
    >>> isinstance(model, LinearRegression)
    True

    >>> data = [{'x': 4, 'y': 20, 'z': 10}, {'x': 5, 'y': 25, 'z': 15}, {'x': 6, 'y': 5, 'z': 20}]
    >>> model = task_func(data, target='y')
    >>> isinstance(model, LinearRegression)
    True
    """

instruct prompt

Perform linear regression to "x," "y," against "z" from a list of dictionaries "d." >>> data = [{'x': 4, 'y': 20, 'z': 10}, {'x': 5, 'y': 25, 'z': 15}, {'x': 6, 'y': 5, 'z': 20}] >>> model = task_func(data, target='y') >>> isinstance(model, LinearRegression) True
The function should output with:
    LinearRegression: A LinearRegression model.
You should write self-contained code starting with:

Code

import pandas as pd
from sklearn.linear_model import LinearRegression
def task_func(d, target='z'):

code prompt

Code

import pandas as pd
from sklearn.linear_model import LinearRegression
def task_func(d, target='z'):

entry point

task_func

libs

  • pandas
  • sklearn

Discussion

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Source and history

task_id
f23fe38e-665d-52a9-ace5-66a649a3215b
task_key
default--v0~2e1~2e0~5fhf--f23fe38e-665d-52a9-ace5-66a649a3215b
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import