Numeric variables

Feature Engineering for Machine Learning in Python

Robert O'Callaghan

Director of Data Science, Ordergroove

Types of numeric features

  • Age
  • Price
  • Counts
  • Geospatial data
Feature Engineering for Machine Learning in Python

Does size matter?

Feature Engineering for Machine Learning in Python

Binarizing numeric variables

df['Binary_Violation'] = 0

df.loc[df['Number_of_Violations'] > 0, 
       'Binary_Violation'] = 1
Feature Engineering for Machine Learning in Python

Binarizing numeric variables

Feature Engineering for Machine Learning in Python

Binning numeric variables

import numpy as np
df['Binned_Group'] = pd.cut(
    df['Number_of_Violations'], 
    bins=[-np.inf, 0, 2, np.inf],
    labels=[1, 2, 3]
)
Feature Engineering for Machine Learning in Python

Binning numeric variables

Feature Engineering for Machine Learning in Python

Lets start practicing!

Feature Engineering for Machine Learning in Python

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