#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 21 13:06:25 2022

@author: tanu
"""
X_train
scaler = preprocessing.MinMaxScaler()
scaler.fit(X_train)

x_train_scaled = scaler.transform(X_train)
x_train_scaled


foo = scaler.fit(X_train)

x_train_scaled2  = foo.transform(X_train)
x_train_scaled2

(x_train_scaled == x_train_scaled2).all()


toy = pd.DataFrame({
'numeric': [1., 2., 3., 4., 5.],
'category': ['a', 'a', 'b', 'c', 'b']
})
numeric_features = ['numeric']
categorical_features = ['category']
preprocessor = ColumnTransformer(transformers=[('num', StandardScaler(), numeric_features),
('cat', OneHotEncoder(), categorical_features)
])
preprocessor.fit(toy)
bar = preprocessor.transform(toy)
bar
#############
toy2 = pd.DataFrame({
'numeric': [1., 2., 3., 4., 5.],
'numeric2': [1., 2., 3., 4., 6.],
'category': ['a', 'a', 'b', 'c', 'b'],
'category2': ['b', 'a', 'b', 'e', 'f']
})
numeric_features = ['numeric', 'numeric2']
categorical_features = ['category', 'category2']
preprocessor = ColumnTransformer(transformers=[
('num', StandardScaler(), numeric_features),
('cat', OneHotEncoder(), categorical_features)
])

preprocessor.fit(toy2)
bar2 = preprocessor.transform(toy2)
bar2

####
import pandas as pd
from pandas import DataFrame
import numpy as np

from sklearn.decomposition import PCA
from pandas import DataFrame
pca = PCA(n_components = 2)
pca.fit(toy2.iloc[:, 0:2])

columns = ['pca_%i' % i for i in range(2)]
df_pca = DataFrame(pca.transform(toy2.iloc[:, 0:2])
                   , columns=columns
                   , index=toy2.index)
df_pca.head()