Pre-process data
First step in the segmentation process is to pre-process the data. You will apply log transformation, and then normalize the data to prepare it for clustering.
We have loaded the dataset with RFMT values as datamart_rfmt. Also, the pandas library is loaded as pd, and numpy as np.
Please feel free to explore the expanded RFMT dataset in the console.
Cet exercice fait partie du cours
Customer Segmentation in Python
Instructions
- Import StandardScaler, initialize it, ad store as
scaler. - Apply log transformation to the raw RFMT data.
- Initialize the scaler and fit it on the log-transformed data.
- Transform and store the scaled data as
datamart_rfmt_normalized.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Import StandardScaler
from ____.____ import ____
# Apply log transformation
datamart_rfmt_log = ____.____(____)
# Initialize StandardScaler and fit it
scaler = ____(); ____.fit(____)
# Transform and store the scaled data as datamart_rfmt_normalized
datamart_rfmt_normalized = ____.____(____)