Center and scale manually
We've loaded the same dataset named data
. Now your goal will be to center and scale them manually.
Libraries pandas
, numpy
, seaborn
and matplotlib.pyplot
have been loaded as pd
, np
, sns
and plt
respectively. Feel free to explore the dataset in the console.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Center the data by subtracting average values from each entry.
- Scale the data by dividing each entry by standard deviation.
- Combine two above actions and normalize the data by applying both centering and scaling.
- Print summary statistics to make sure average is zero and standard deviation is one, and round the output to 2 decimals.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Center the data by subtracting average values from each entry
data_centered = data - data.____()
# Scale the data by dividing each entry by standard deviation
data_scaled = ____ / ____.____()
# Normalize the data by applying both centering and scaling
data_normalized = (____ - data.____()) / data.____()
# Print summary statistics to make sure average is zero and standard deviation is one
print(data_normalized.____().round(____))