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.

Questo esercizio fa parte del corso

Customer Segmentation in Python

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Istruzioni dell'esercizio

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.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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(____))

Modifica ed esegui il codice