Center and scale with StandardScaler()

We've loaded the same dataset named data. Now your goal will be to center and scale them with StandardScaler from sklearn library.

Libraries pandas, numpy, seaborn and matplotlib.pyplot have been loaded as pd, np, sns and plt respectively. We have also imported the StandardScaler.

Feel free to explore the dataset in the console.

This exercise is part of the course

Customer Segmentation in Python

View Course

Exercise instructions

Initialize StandardScaler instance as scaler and fit it to the data
Transform the data by scaling and centering it with scaler.
Create a pandas DataFrame from data_normalized by adding index and column names from data.
Print summary statistics to make sure average is zero and standard deviation is one, and round the results to 2 decimals.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Initialize a scaler
scaler = ____()

# Fit the scaler
____.____(data)

# Scale and center the data
data_normalized = ____.____(data)

# Create a pandas DataFrame
data_normalized = pd.DataFrame(____, index=data.index, columns=data.columns)

# Print summary statistics
print(data_normalized.____().round(____))

Edit and Run Code