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BigCodeBench / BigCodeBench v0.1.0_hf b57c8aa3-8ba5-5286-8f2b-e4eeafdc2d13

Problem

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

complete prompt

import pandas as pd
import numpy as np

# Constants
COLUMNS = ['column1', 'column2', 'column3', 'column4', 'column5']

def task_func(df, dct):
    """
    Replace certain values in a DataFrame with a dictionary mapping and calculate the Pearson correlation coefficient between each pair of columns.

    Parameters:
    df (DataFrame): The input DataFrame, containing numeric or categorical data.
    dct (dict): A dictionary for replacing values in df, where keys are existing values and values are new values.

    Returns:
    DataFrame: A DataFrame with the correlation coefficients between each pair of columns. The format of the DataFrame is a square matrix with column and index labels matching the columns of the input DataFrame.
    
    Requirements:
    - pandas
    - numpy
    
    Note:
    - This function operates on DataFrames containing numeric or categorical data that can be replaced with numeric values, as correlation calculations require numeric data.
    - This function using pearson method to calculate the correlation matrix.
    
    Raises:
    - This function will raise a ValueError is input df is not a DataFrame.
        
    Example:
    >>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
    >>> dct = {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60}
    >>> correlation_matrix = task_func(df, dct)
    >>> correlation_matrix.shape == (2, 2)
    True
    >>> np.allclose(correlation_matrix, np.array([[1.0, 1.0], [1.0, 1.0]]))
    True
    """

instruct prompt

Replace certain values in a DataFrame with a dictionary mapping and calculate the Pearson correlation coefficient between each pair of columns.
Note that: This function operates on DataFrames containing numeric or categorical data that can be replaced with numeric values, as correlation calculations require numeric data. This function using pearson method to calculate the correlation matrix.
The function should raise the exception for: This function will raise a ValueError is input df is not a DataFrame.
The function should output with:
    DataFrame: A DataFrame with the correlation coefficients between each pair of columns. The format of the DataFrame is a square matrix with column and index labels matching the columns of the input DataFrame.
You should write self-contained code starting with:

Code

import pandas as pd
import numpy as np
# Constants
COLUMNS = ['column1', 'column2', 'column3', 'column4', 'column5']
def task_func(df, dct):

code prompt

Code

import pandas as pd
import numpy as np
# Constants
COLUMNS = ['column1', 'column2', 'column3', 'column4', 'column5']
def task_func(df, dct):

entry point

task_func

libs

  • pandas
  • numpy

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Source and history

task_id
b57c8aa3-8ba5-5286-8f2b-e4eeafdc2d13
task_key
default--v0~2e1~2e0~5fhf--b57c8aa3-8ba5-5286-8f2b-e4eeafdc2d13
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import