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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.

Cet exercice fait partie du cours

Customer Segmentation in Python

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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.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de 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(____))
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