benchmarks.wiki

benchmarks.wiki / Public workspace

BigCodeBench / BigCodeBench v0.1.0_hf ab132fb0-e879-5306-b784-cfbf80f9b374

Problem

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

complete prompt

import pandas as pd
from sklearn.model_selection import train_test_split


def task_func(df, target_column, column_to_remove="c", test_size=0.2):
    """
    Split the data into train and test datasets after removing a specified column if it exists.

    Parameters:
    - df (dict): The input dataframe.
    - target_column (str): The name of the target column.
    - column_to_remove (str): The name of the column to remove. Defaults to 'c'.
    - test_size (float): The ratio of test data in split output. Defaults to .2.

    Returns:
    - X_train (pd.DataFrame): Split features for training.
    - X_test  (pd.DataFrame): Split features for testing.
    - y_train    (pd.Series): Split target values for training.
    - y_test     (pd.Series): Split target values for testing.

    Requirements:
    - pandas
    - sklearn

    Examples:
    >>> data = {
    ... 'a': [1, 2, 3, 4],
    ... 'b': [5, 6, 7, 8],
    ... 'c': [9, 10, 11, 12],
    ... 'target': [0, 1, 0, 1]
    ... }
    >>> X_train, _, _, _ = task_func(data, 'target')
    >>> type(X_train), X_train.shape
    (<class 'pandas.core.frame.DataFrame'>, (3, 2))
    >>> data = {
    ... 'x1': [10, 20, 30, 40],
    ... 'x2': [50, 60, 70, 80],
    ... 'x3': [90, 100, 110, 120],
    ... 'outcome': [1, 2, 3, 4]
    ... }
    >>> df2 = pd.DataFrame(data)
    >>> _, _, _, y_test = task_func(df2, 'outcome', 'x3', .25)
    >>> type(y_test), y_test.shape
    (<class 'pandas.core.series.Series'>, (1,))
    """

instruct prompt

Split the data into train and test datasets after removing a specified column if it exists.
The function should output with:
    X_train (pd.DataFrame): Split features for training.
    X_test  (pd.DataFrame): Split features for testing.
    y_train    (pd.Series): Split target values for training.
    y_test     (pd.Series): Split target values for testing.
You should write self-contained code starting with:

Code

import pandas as pd
from sklearn.model_selection import train_test_split
def task_func(df, target_column, column_to_remove="c", test_size=0.2):

code prompt

Code

import pandas as pd
from sklearn.model_selection import train_test_split
def task_func(df, target_column, column_to_remove="c", test_size=0.2):

entry point

task_func

libs

  • pandas
  • 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
ab132fb0-e879-5306-b784-cfbf80f9b374
task_key
default--v0~2e1~2e0~5fhf--ab132fb0-e879-5306-b784-cfbf80f9b374
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import