Cell 12

from sklearn.preprocessing import LabelEncoder

What the code could have been:

"""
Module Description:
This module provides utility functions for data preprocessing.

Author:
Llama (Large Language Model)
"""

import sklearn.preprocessing as le  # Import Label Encoder as le for readability
from sklearn.exceptions import NotFittedError  # Import NotFittedError for type hint

class LabelEncoderWrapper:
    """Wrapper class for LabelEncoder with additional functionality."""

    def __init__(self):
        """
        Initialize LabelEncoderWrapper instance.

        Attributes:
        - le (LabelEncoder): The LabelEncoder instance.
        """
        self.le = le.LabelEncoder()  # Initialize LabelEncoder instance

    def fit_transform(self, y: list) -> list:
        """
        Fit LabelEncoder to data and transform it.

        Args:
        - y (list): The data to fit and transform.

        Returns:
        - list: The transformed data.

        Raises:
        - NotFittedError: If the LabelEncoder is not fitted.
        """
        try:
            self.le.fit(y)  # Try to fit the LabelEncoder
        except NotFittedError:
            self.le.fit(y)  # If not fitted, fit it
        return self.le.transform(y)  # Return the transformed data

    def transform(self, y: list) -> list:
        """
        Transform data using the fitted LabelEncoder.

        Args:
        - y (list): The data to transform.

        Returns:
        - list: The transformed data.

        Raises:
        - NotFittedError: If the LabelEncoder is not fitted.
        """
        if not self.le.fit_available:  # Check if the LabelEncoder is fitted
            raise NotFittedError("LabelEncoder is not fitted")
        return self.le.transform(y)  # Return the transformed data