Data Preprocessing in Machine Learning using Python - SimpleImputer, OneHotEncoder, train_test_split

Data Preprocessing in Machine Learning using Python 2023

#SimpleImputer #OneHotEncoder #train_test_split #StandardScaler #LabelEncoder

//Import Library:
import pandas as pd
import numpy as np

//Import Dataset:
print(dataset)

//Split dataset into X and y i.e. independent and dependent model
print(X)

print(y)

//Handling missing data:

print(X)

//Encoding categorical data:

ct = ColumnTransformer(transformers=[('encoder', OneHotEncoder(), [0])] , remainder= 'passthrough')

print(X)

le = LabelEncoder()
print(y)

//Splitting data into training and testing model:

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)

print(X_train)
print(y_train)
print(y_test)
print(X_test)

//Feature Scaling:

ss = StandardScaler()

print(X_train)
print(X_test)