This code snippet uses Label Encoding to transform categorical data in the 'label' column of the 'train' and 'test' datasets into numerical representations. The transformation is performed using the transform() method, assuming that a LabelEncoder instance named le has been initialized elsewhere in the code.

Cell 14

y_train = le.transform(train['label'])
y_test = le.transform(test['label'])

from sklearn.preprocessing import LabelEncoder
import pandas as pd

def transform_labels(train: pd.DataFrame, test: pd.DataFrame) -> tuple:
    """
    Transform categorical labels into numerical labels.

    Args:
    - train (pd.DataFrame): Training dataset with categorical labels.
    - test (pd.DataFrame): Testing dataset with categorical labels.

    Returns:
    - train_labels (pd.Series): Numerical labels for the training dataset.
    - test_labels (pd.Series): Numerical labels for the testing dataset.
    """
    # Initialize LabelEncoder
    label_encoder = LabelEncoder()

    # Create a copy to avoid modifying the original data
    train_copy = train.copy()
    test_copy = test.copy()

    # Transform labels
    train_labels = label_encoder.fit_transform(train_copy['label'])
    test_labels = label_encoder.transform(test_copy['label'])

    # Return the transformed labels
    return train_labels, test_labels

Code Breakdown

Purpose

This code snippet is used to transform categorical data in the 'label' column of train and test datasets into numerical representations using Label Encoding (le).

Code Explanation

1. y_train = le.transform(train['label']):

   • le is an instance of LabelEncoder from scikit-learn library, used for encoding categorical values into numerical values.
   • train['label'] is the column in the train dataset that needs to be encoded.
   • The transform() method is called on le to perform the encoding. The resulting encoded values are stored in y_train.

2. y_test = le.transform(test['label']):

   • Similar to the first line, but for the test dataset.

Note

This code assumes that the le variable has been initialized elsewhere in the code, and it is an instance of LabelEncoder.