badgers is a python library for generating bad data (more precisely to augment existing data with data quality deficits such as outliers, missing values, noise, etc.). It is based upon a simple API and provides a set of generators object that can generate data quality deficits from existing data.
A word of caution: badgers is still in an early development stage. Although the core structure of the package and the generate(X,y) signature are not expected to change, some API details (like attributes names) are likely to change.
The full documentation is hosted here: https://fraunhofer-iese.github.io/badgers/.
For a quick-start, you can install badgers with pip:
pip install badgersImport badgers as any other library and start using it:
from sklearn.datasets import make_blobs
from badgers.generators.tabular_data.noise import GaussianNoiseGenerator
X, y = make_blobs()
trf = GaussianNoiseGenerator(noise_std=0.5)
Xt, yt = trf.generate(X,y)More examples are available in the tutorials section.
The API documentation is also available in the API section.
Interested developers will find relevant information in the CONTRIBUTING.md page.