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.

Este exercício faz parte do curso

Customer Segmentation in Python

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Instruções do exercício

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.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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(____))

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