This package contains some developmental tools to detect and compare statistical differences between 2 structurally similar pandas dataframes. The intended purpose is to detect data drift - where the statistical properties of an input variable change over time.
We provide a class DataDriftDetector which takes in 2 pandas dataframes and provides a few useful methods to compare and analyze the differences between the 2 datasets.
Install the package with pip
pip install data-drift-detectorTo compare 2 datasets:
from data_drift_detector import DataDriftDetector
# initialize detector
detector = DataDriftDetector(df_prior = df_1, df_post = df_2)
# methods to compare and analyze differences
detector.calculate_drift()
detector.plot_numeric_to_numeric()
detector.plot_categorical_to_numeric()
detector.plot_categorical()
detector.compare_ml_efficacy(target_column="some_target_column")You may also view an example notebook in the following directory examples/example_usage.ipynb to explore how it may be used.