A/B tests (a.k.a. Randomized Controlled Trials or Experiments) have been widely applied in different industries to optimize business processes and user experience. ExpAn (Experiment Analysis) is a Python library developed for the statistical analysis of such experiments and to standardise the data structures used.
The data structures and functionality of ExpAn are generic such that they can be used by both data scientists optimizing a user interface and biologists running wet-lab experiments. The library is also standalone and can be imported and used from within other projects and from the command line.
Major statistical functionalities include:
- feature check
- delta
- subgroup analysis
- trend
To install ExpAn, run this command in your terminal:
$ pip install expanTo use ExpAn in a project:
import expan
Some mock-up data:
from expan.core.experiment import Experiment
from tests.tests_core.test_data import generate_random_data
exp = Experiment('B', *generate_random_data())
exp.delta()
The latest stable version is 0.4.5.
ExpAn Description - details about the concept of the library and data structures.
ExpAn Introduction - a full jupyter (iPython) notebook. You can view it as slides with jupyter:
sh serve_intro_slides
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