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BigCodeBench / BigCodeBench v0.1.0_hf 91cd72b2-b479-5a45-8711-eb5b15175f84

Problem

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

complete prompt

import json
import numpy as np
from collections import defaultdict
import matplotlib.pyplot as plt


def task_func(input_file):
    """
    Reads a JSON file containing a list of dictionaries. For each key across all dictionaries,
    calculates the mean and median of its values using numpy. Visualizes the mean and median
    using bar charts. Returns the results and plots.

    Parameters:
        - input_file (str): Path to the input JSON file containing a list of dictionaries.

    Returns:
        - result (dict): each key corresponds to those in the input dictionaries, and the corresponding
          value is another dict with keys 'mean' and 'median', representing the calculated statistics.
        - plots  (list[matplotlib.axes._axes.Axes]): A list of bar charts, one for
          each key in the dictionaries, visualizing the mean and median values.

    Requirements:
        - json
        - numpy
        - collections.defaultdict
        - matplotlib.pyplot

    Example:
    >>> results, plots = task_func("sample_data.json")
    >>> type(plots[0])
    <class 'matplotlib.axes._axes.Axes'>
    >>> results
    {'a': {'mean': 3.0, 'median': 3.0}, 'b': {'mean': 6.0, 'median': 6.0}}
    """

instruct prompt

Reads a JSON file containing a list of dictionaries. For each key across all dictionaries, calculates the mean and median of its values using numpy. Visualizes the mean and median using bar charts. Returns the results and plots.
The function should output with:
    result (dict): each key corresponds to those in the input dictionaries, and the corresponding
    value is another dict with keys 'mean' and 'median', representing the calculated statistics.
    plots  (list[matplotlib.axes._axes.Axes]): A list of bar charts, one for
    each key in the dictionaries, visualizing the mean and median values.
You should write self-contained code starting with:

Code

import json
import numpy as np
from collections import defaultdict
import matplotlib.pyplot as plt
def task_func(input_file):

code prompt

Code

import json
import numpy as np
from collections import defaultdict
import matplotlib.pyplot as plt
def task_func(input_file):

entry point

task_func

libs

  • collections
  • numpy
  • matplotlib
  • json

Discussion

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Source and history

task_id
91cd72b2-b479-5a45-8711-eb5b15175f84
task_key
default--v0~2e1~2e0~5fhf--91cd72b2-b479-5a45-8711-eb5b15175f84
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import