benchmarks.wiki

benchmarks.wiki / Public workspace

BigCodeBench / BigCodeBench v0.1.0_hf 7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1

Problem

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

complete prompt

from sklearn.decomposition import PCA
import numpy as np
import matplotlib.pyplot as plt

# Constants
N_COMPONENTS = 2


def task_func(L):
    """
    Convert a list of lists 'L' into a 2D numeric array, apply PCA to it and return the PCA result and scatter plot.
    
    Requirements:
    - numpy
    - sklearn.decomposition
    - matplotlib.pyplot

    Parameters:
    L (list of lists): A list of lists where each sublist contains integers.
    
    Returns:
    tuple: A tuple containing the PCA result (numpy array) and the scatter plot (matplotlib Axes object).

    Example:
    >>> pca_result, plot = task_func([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    >>> type(pca_result)
    <class 'numpy.ndarray'>
    """

instruct prompt

Convert a list of lists 'L' into a 2D numeric array, apply PCA to it and return the PCA result and scatter plot.
The function should output with:
    tuple: A tuple containing the PCA result (numpy array) and the scatter plot (matplotlib Axes object).
You should write self-contained code starting with:

Code

from sklearn.decomposition import PCA
import numpy as np
import matplotlib.pyplot as plt
# Constants
N_COMPONENTS = 2
def task_func(L):

code prompt

Code

from sklearn.decomposition import PCA
import numpy as np
import matplotlib.pyplot as plt
# Constants
N_COMPONENTS = 2
def task_func(L):

entry point

task_func

libs

  • numpy
  • matplotlib
  • sklearn

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
7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1
task_key
default--v0~2e1~2e0~5fhf--7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import