benchmarks.wiki

benchmarks.wiki / Public workspace

BigCodeBench / BigCodeBench v0.1.0_hf 2502c0cd-764f-5515-b778-7fb568737e21

Problem

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

complete prompt

import numpy as np
import pandas as pd
from scipy.stats import linregress


def task_func(df):
    """
    Analyze the relationship between two variables in a DataFrame.
    The function performs a linear regression on the two variables and adds a 'predicted' column to the DataFrame.

    Parameters:
    - df (pandas.DataFrame): The input DataFrame with columns 'var1', 'var2'.
    
    Returns:
    - df (pandas.DataFrame): The DataFrame with the added 'predicted' column.

    Requirements:
    - numpy
    - pandas
    - scipy

    Example:
    >>> df = pd.DataFrame({'var1': np.random.randn(10),
    ...                    'var2': np.random.randn(10)})
    >>> df = task_func(df)
    >>> assert 'predicted' in df.columns
    >>> assert len(df) == 10
    >>> assert len(df.columns) == 3
    """

instruct prompt

Analyze the relationship between two variables in a DataFrame. The function performs a linear regression on the two variables and adds a 'predicted' column to the DataFrame.
The function should output with:
    df (pandas.DataFrame): The DataFrame with the added 'predicted' column.
You should write self-contained code starting with:

Code

import numpy as np
import pandas as pd
from scipy.stats import linregress
def task_func(df):

code prompt

Code

import numpy as np
import pandas as pd
from scipy.stats import linregress
def task_func(df):

entry point

task_func

libs

  • pandas
  • numpy
  • scipy

Discussion

Discussion

No discussion posts on this page yet. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

See answer Answer published by the source

Artifacts

Code, notes and reproducible work shared by participants. Files are served from a separate origin.

No artifacts on this page yet. Share reproducible code or notes in a contribution. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

Source and history

task_id
2502c0cd-764f-5515-b778-7fb568737e21
task_key
default--v0~2e1~2e0~5fhf--2502c0cd-764f-5515-b778-7fb568737e21
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import