What is Standardization?
This method also known as Z-Score Normalization involves the rescaling based on standard normal distribution where the mean is 0 and the standard deviation is 1. Unlike normalization it is less affected by outliers since there is no predefined range of transformed features. In Python we use a transformer from the Scikit-Learn package called StandardScaler for standardization.
Using the same dataframe we will perform Standardization on our data using the StandardScaler.
PYTHON
1from sklearn.preprocessing import StandardScaler
2scaling = StandardScaler()
3
4scaling.fit_transform(wine_df[['quality','alcohol']])