Python for Finance Cookbook

How to do it...

Execute the following steps to build the project's pipeline.

1. Import the libraries:

import pandas as pdfrom sklearn.model_selection import train_test_splitfrom sklearn.impute import SimpleImputerfrom sklearn.preprocessing import OneHotEncoderfrom sklearn.compose import ColumnTransformerfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.pipeline import Pipelinefrom chapter_8_utils import performance_evaluation_report

2. Load the data, separate the target, and create the stratified train-test split:

df = pd.read_csv('credit_card_default.csv', index_col=0,                   na_values='')X = df.copy()y = X.pop('default_payment_next_month')X_train, X_test, y_train, y_test = train_test_split(X, y,                                                     test_size=0.2,                                                     stratify=y) 

3. Store lists ...