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BigCodeBench / BigCodeBench v0.1.0_hf d0437431-3569-5ba0-b795-7eb04d1ebc67

Problem

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

complete prompt

import pandas as pd
from matplotlib import pyplot as plt


def task_func(arr):
    """
    Calculate the sum of each row in a 2D numpy array and plot these sums as a time series.

    This function takes a 2D numpy array and computes the sum of elements in each row. It
    then creates a Pandas DataFrame with these row sums and plots them as a time series,
    using dates starting from January 1, 2020, for each row.

    Parameters:
    arr (numpy.ndarray): A 2D numpy array.

    Returns:
    matplotlib.axes._axes.Axes: A plot representing the time series of row sums.

    Requirements:
    - pandas
    - matplotlib

    Handling Scenarios:
    - For non-empty arrays: The function computes the sum of elements for each row, 
    stores these sums in a Pandas DataFrame, and then plots them. Each row in the plot represents 
    the sum for a specific day, starting from January 1, 2020.
    - For empty arrays: The function creates an empty plot with the 
    title 'Time Series of Row Sums' but without data. This is achieved by checking if the array size 
    is zero (empty array) and if so, creating a subplot without any data.
    
    Note: 
    - The function uses 'pandas' for DataFrame creation and 'matplotlib.pyplot' for plotting. 
    The dates in the plot start from January 1, 2020, and each subsequent row represents the next day.
    
    Example:
    >>> arr = np.array([[i + j for i in range(3)] for j in range(5)])
    >>> ax = task_func(arr)
    >>> ax.get_title()
    'Time Series of Row Sums'
    """

instruct prompt

Calculate the sum of each row in a 2D numpy array and plot these sums as a time series. This function takes a 2D numpy array and computes the sum of elements in each row. It then creates a Pandas DataFrame with these row sums and plots them as a time series, using dates starting from January 1, 2020, for each row. Handling Scenarios: - For non-empty arrays: The function computes the sum of elements for each row, stores these sums in a Pandas DataFrame, and then plots them. Each row in the plot represents the sum for a specific day, starting from January 1, 2020. - For empty arrays: The function creates an empty plot with the title 'Time Series of Row Sums' but without data. This is achieved by checking if the array size is zero (empty array) and if so, creating a subplot without any data.
Note that: The function uses 'pandas' for DataFrame creation and 'matplotlib.pyplot' for plotting. The dates in the plot start from January 1, 2020, and each subsequent row represents the next day.
The function should output with:
    matplotlib.axes._axes.Axes: A plot representing the time series of row sums.
You should write self-contained code starting with:

Code

import pandas as pd
from matplotlib import pyplot as plt
def task_func(arr):

code prompt

Code

import pandas as pd
from matplotlib import pyplot as plt
def task_func(arr):

entry point

task_func

libs

  • pandas
  • matplotlib

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Source and history

task_id
d0437431-3569-5ba0-b795-7eb04d1ebc67
task_key
default--v0~2e1~2e0~5fhf--d0437431-3569-5ba0-b795-7eb04d1ebc67
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import