PYTHON

sklearn standardscaler to selected column only

# PYTHON

cols_to_scale= ['Alcohol','Gdp','Population', 'Percentage expenditure', 'Schooling']

X_train[cols_to_scale]=scaler.fit_transform(X_train[cols_to_scale])
X_test[cols_to_scale]=scaler.transform(X_test[cols_to_scale])

sklearn standardscaler for numerical columns

# Author: Pedro Morales <part.morales@gmail.com>
#
# License: BSD 3 clause

import numpy as np

from sklearn.compose import ColumnTransformer
from sklearn.datasets import fetch_openml
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split, GridSearchCV

np.random.seed(0)

# Load data from https://www.openml.org/d/40945
X, y = fetch_openml("titanic", version=1, as_frame=True, return_X_y=True)