normscaler 0.0.2

A data normalization package

normscalers

A package for data normalization including the methods of MinMaxScaler, MaxAbsScaler, RobustScaler, StandardScaler and Normalizer in Scikit-learning, and DecimalScaler. The package can automatically detect the one-hot encoded variables and skip them to be normalized.

Install

pip install normscaler

use

(1) import one or more scalers by their names

• MinMaxScaler
• MaxAbsScaler
• RobustScaler
• StandardScaler
• Normalizer
• DecimalScaler

For example, import DecimalScaler by

from normascaler.scaler import DecimalScaler

(2) Use Decimal scaling method

X_train_scaled, X_train_scaled = DecimalScaler(X_train, X-test)

(3) Display the normalized X_train data in Pandas DataFrame

X_train_scaled

(4) Display the normalized X_test data in Pandas DataFrame

X_test_scaled

Documentation

Examples of a Jupyter note in GitHub: https://github.com/shoukewei/normscaler/blob/main/docs/examples.ipynb