le AB is a Python library for AB testing analysis.
Before launching your AB test, you can compute the needed sample size per variation :
from leab import before
ab_test = before.leSample(conversion_rate=20, ... min_detectable_effect=2) ab_test.get_size_per_variation()
After reaching the needed sample size, you can compare means obtained from A VS B :
from leab import after from leab import leDataset
data = leDataset.SampleLeAverage()
ab_test = after.leAverage(data.A, data.B) teab_testst.get_verdict()
'Sample A mean is greater' ```
:snake: You need to install Python 3.6 or above.
Installation can be done by using
There are wheels available for Linux, MacOS, and Windows.
pip install leab
You can also install the latest development version as so:
```bash pip install git+https://github.com/tlentali/leab
pip install git+ssh://[email protected]/tlentali/leab.git ```
"Life is a sum of all our choices."
Get ready to take a decision !
AB testing has never been more popular, especially on Internet based companies.
Even if each test is unique, some questions seem to be asked again and again :
Strong statistical knowledge are required to handle it from start to end correctly.
To answer those questions in a simple and robust way, we built
Lets Python do AB testing analysis !
Here are some benefits of using
Le AB :
Next release features :
This project takes its inspiration from Evan Miller great work, especially the following :
Thank you so much Evan M. for your work, it saved our lives so many times !
A big thanks to Max Halford too, who inspired us in the structure of this project, particularly for docs and tests.
Have a look at Creme-ml, it's just amazingly done !
To finish, thanks to all of you who use or are going to use this lib, hope it helps !
Feel free to contribute in any way you like, we're always open to new ideas and approaches. If you want to contribute to the code base please check out the CONTRIBUTING.md file. Also take a look at the issue tracker and see if anything takes your fancy.
This project follows the all-contributors specification. Again, contributions of any kind are welcome!
le AB is free and open-source software licensed under the 3-clause BSD license.
Bumps ipython from 7.16.3 to 8.10.0.
Sourced from ipython's releases.
We do not use GitHub release anymore. Please see PyPI https://pypi.org/project/ipython/
560ad10DOC: Update what's new for 8.10 (#13939)
7557adeDOC: Update what's new for 8.10
385d693Merge pull request from GHSA-29gw-9793-fvw7
e548ee2Swallow potential exceptions from showtraceback() (#13934)
0694b08MAINT: mock slowest test. (#13885)
8655912MAINT: mock slowest test.
a011765Isolate the attack tests with setUp and tearDown methods
c7a9470Add some regression tests for this change
fd34cf5Swallow potential exceptions from showtraceback()
Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting
Content addition :
- Colab notebook
- get size by variation and get total size in
summarymethods are rename
leReportfor before module is added
Data Scientist @betclic | [email protected] @BIGDATALABCARTEGIEGitHub Repository Homepage
python data-science data-analysis ab-testing analysis analytics statistics abtest