Compare differences between 2 datasets to identify data drift
Project description
Data Drift Detector
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.
Installation
Install the package with pip
pip install data-drift-detector
Example Usage
To 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for data-drift-detector-0.0.13.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 17b26f9b8d533f1b42f86bae437954eea54a2381befbc5b21111ef73fd8a685f |
|
MD5 | e8bcd0b144d0d578e2fdb9315637000c |
|
BLAKE2b-256 | 634764389a04a72a2428ba32d4f3d83fe09c603ad57010e9fcdc2b3cb1dcfc1f |