Python for Machine Learning | Preprocessing | fit, transform and fit_transform - P83

""" Python for Machine Learning - Session # 83 Topic to be covered - How fit(), transform() and fit_transform() works ? OR Difference between fit(), transform() and fit_transform() """ import pandas as pd from sklearn.preprocessing import Imputer, LabelEncoder df = pd.read_csv('Datapreprocessing.csv') imputer = Imputer(missing_values='NaN',strategy='mean',axis=0) imputer.fit(df[['Age','Salary']]) X = imputer.transform(df[['Age','Salary']]) imputer.fit_transform(df[['Age','Salary']]) ############################################################################### encode = LabelEncoder() encode.fit(df['Country']) encode.transform(df['Country']) encode.fit_transform(df['Country']) ############################################################################### import numpy as np from sklearn.preprocessing import StandardScaler x1 = np.array([[1,2,3], [4,5,6], [7,8,9]]) standscaler = StandardScaler() x_scaler = standscaler.fit_transform(x1) print(x_scaler) ''' (Xi - Xmean) / (standard Deviation of that feature) ''' standscaler.fit(x1) standscaler.transform(x1)