Maxabs scaler full code

#Import Libraries
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import OrdinalEncoder
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import MaxAbsScaler


#Data Processing
df=pd.read_csv("https://archive.ics.uci.edu/ml/machine-learning-databases/00542/log2.csv")

ordinalencoder=OrdinalEncoder()
df['Action']=ordinalencoder.fit_transform(np.reshape(df['Action'].values,(-1,1)))

y=df.pop("Action")
X_train, X_test, y_train, y_test = train_test_split(df, y, random_state=42,test_size=0.1)


# Feature Scaling
pipe_maxabs = make_pipeline(MaxAbsScaler(), LogisticRegression(max_iter=2000))
pipe_maxabs.fit(X_train, y_train)
pipe_maxabs.score(X_test, y_test)