Technical requirements

In this chapter, we will use the Matplotlib, pandas, NumPy, scikit-learn, and feature-engine Python libraries. If you need to install Python, the free Anaconda Python distribution (https://www.anaconda.com/) comes with most numerical computing libraries out of the box.

Feature-engine can be installed with pip:

pip install feature-engine

If you use Anaconda, you can install feature-engine with conda:

conda install -c conda-forge feature_engine

We will use the Credit Approval dataset from the UCI Machine Learning Repository (https://archive.ics.uci.edu/). To prepare the dataset, follow these steps:

1. Visit https://archive.ics.uci.edu/ml/machine-learning-databases/credit-screening/.
2. Click on crx.data to download the data.

Figure 1.1 – Screenshot of the dataset download page

3. Save crx.data to the folder where you will run the following commands.

Open a Jupyter notebook and run the following...