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BigCodeBench / BigCodeBench v0.1.0_hf 941bb0d7-9785-5cce-aa71-2e59c6284d9f

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


def task_func(column, data):
    """
    Analyzes a list of stock data and calculates the sum, mean, minimum, and maximum
    values for a specified column.

    Parameters:
    - column (str): The name of the column to analyze. Valid options are 'Date', 'Open', 'High',
                    'Low', 'Close', and 'Volume'.
    - data (list of lists): A list where each element is a list representing stock data for a single day.
                            Each inner list should contain values in the following order:
                            'Date', 'Open', 'High', 'Low', 'Close', 'Volume'.
    Returns:
    - dict: A dictionary containing the calculated 'sum', 'mean', 'min' (minimum), and 'max' (maximum)
            for the specified column. If the input data is empty, 'sum' will be 0, and 'mean', 'min', and
            'max' will be NaN.

    Requirements:
    - pandas
    - numpy

    Raises:
    - ValueError: If the specified column name is not valid.
    
    Example:
    >>> data = [[datetime(2022, 1, 1), 100, 105, 95, 102, 10000]]
    >>> results = task_func('Open', data)
    >>> results
    {'sum': 100, 'mean': 100.0, 'min': 100, 'max': 100}
    >>> type(results)
    <class 'dict'>
    """

instruct prompt

Analyzes a list of stock data and calculates the sum, mean, minimum, and maximum values for a specified column.
The function should raise the exception for: ValueError: If the specified column name is not valid.
The function should output with:
    dict: A dictionary containing the calculated 'sum', 'mean', 'min' (minimum), and 'max' (maximum)
    for the specified column. If the input data is empty, 'sum' will be 0, and 'mean', 'min', and
    'max' will be NaN.
You should write self-contained code starting with:

Code

import pandas as pd
import numpy as np
def task_func(column, data):

code prompt

Code

import pandas as pd
import numpy as np
def task_func(column, data):

entry point

task_func

libs

  • pandas
  • numpy

Discussion

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Source and history

task_id
941bb0d7-9785-5cce-aa71-2e59c6284d9f
task_key
default--v0~2e1~2e0~5fhf--941bb0d7-9785-5cce-aa71-2e59c6284d9f
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import