evidently_data_drift_report_and_quality_test_suite.py

1import pandas as pd
2from sklearn import datasets
3
4from library.report import Report
5from library.metric_preset import DataDriftPreset
6from library.test_suite import TestSuite
7from library.test_preset import DataQualityTestPreset
8
9# Load sample data
10iris_data = datasets.load_iris(as_frame=True)
11iris_frame = iris_data.frame
12
13# Split data into reference (training) and current (production)
14reference_data = iris_frame[:75]
15current_data = iris_frame[75:]
16
17# 1. Create a Report with a specific Preset (Data Drift)
18report = Report(metrics=[
19    DataDriftPreset(),
20])
21
22report.run(reference_data=reference_data, current_data=current_data)
23report.save_html("report.html")
24
25# 2. Create a Test Suite with a specific Preset (Data Quality)
26test_suite = TestSuite(tests=[
27    DataQualityTestPreset(),
28])
29
30test_suite.run(reference_data=reference_data, current_data=current_data)
31test_suite.save_html("test_suite.html")