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
Exercise instructions
- Initialize
StandardScaler
instance asscaler
and fit it to thedata
- Transform the
data
by scaling and centering it withscaler
. - Create a pandas DataFrame from
data_normalized
by adding index and column names fromdata
. - 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(____))