customer_history_df[feature_vectoras_matrix(scaler preprocessing standardscaler(fit(xx_scaled scaler transform(xthe previous code snippet will create log valued and mean centered version of our dataset we can visualize the results of our preprocessing by inspecting the variable with the widest range of values the following code snippet will help us visualize this in [ ] customer_history_df amount_log nbinspatches plt hist( facecolor='green'alpha= plt xlabel('log of sales amount'plt ylabel('probability'plt title( '$\mathrm{histogramoflogtransformedcustomermonetaryvalue}$'plt grid(trueplt show(the resulting graph is distribution resembling normal distribution with mean and variance of as clearly depicted in figure - figure - scaled and log transformed sales amount