Python Feature Engineering Cookbook

How to do it...

Let's begin by importing the libraries and getting the dataset ready:

1. Import the required Python libraries, methods, and classes:

import numpy as npimport pandas as pdimport matplotlib.pyplot as pltimport scipy.stats as statsfrom sklearn.datasets import load_bostonfrom sklearn.preprocessing import FunctionTransformerfrom feature_engine.variable_transformers import ReciprocalTransformer

2. Let's load the Boston House Prices dataset:

boston_dataset = load_boston()data = pd.DataFrame(boston_dataset.data, columns=boston_dataset.feature_names)

3. To evaluate the effect of the transformation on the variable distribution, we'll create a function that takes a dataframe and a variable name as inputs and plots a histogram next to a Q-Q ...