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توضیحات

BAyesian Beta-Binomial AB testing (BABBAB), is an implementation

ویژگی	مقدار
سیستم عامل	-
نام فایل	babbab-0.3.1
نام	babbab
نسخه کتابخانه	0.3.1
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	-
ایمیل نویسنده	Juan González-Vallinas <juan@multilayer.io>
آدرس صفحه اصلی	-
آدرس اینترنتی	https://pypi.org/project/babbab/
مجوز	-

# babbab The two purposes of `babbab` are: 1. To be the *simplest* tool for Data Analysts/Statisticians to **analyze** A/B tests. 2. To return the *simplest* results for Stakeholders/Non-Statisticians to **understand**. `babbab` an acronym of **BA**yesian **B**eta-**B**inomial **A**/**B** testing (`BaBBAB`), but it's spelled in lowercase (`babbab`) because it doesn't like shouting. ## Install This should work in vanilla Python +3.8. ```bash pip install babbab ``` ## A quick example Lets assume we are testing changing the background color of our app from grey to green. Lets say we sell subscriptions to a paper magazine. We want to know if changing the background color will increase sales. To do so, we assign 50% of our users to the new app design with a green background (The Variant Group), while other 50% stay in the old grey design (the Control group). We managed to pull these 4 numbers out our tracking into Python: ```python control_sold_subscriptions = 200 control_users = 40316 variant_sold_subscriptions = 250 variant_users = 40567 ``` Because `babbab` is awesome you can just run: ```python import babbab as bab plot, statement, trace = bab.quick_analysis(control_sold_subscriptions, control_users, variant_sold_subscriptions, variant_users) ``` And get [everything you need](https://github.com/multilayer-io/babbab/blob/main/notebooks/should_be_pytest.ipynb). 1. In `plot` you will find a matplotlib figure. You can change the title and labels in the `quick_analysis` function. 2. In `statement`, you will get a string that is intended to be interpreted verbatim by Non-Statisticians. 3. In `trace`, you will get an [arviz InferenceData](https://python.arviz.org/en/latest/api/generated/arviz.InferenceData.html) object, in case you want to explore the run further. In the signature of `quick_analysis` you can configure the statistics and the aesthetics of most of this. ## Motivation A/B tests (or controlled experiments) are an increasingly popular way of incrementally improving websites, desktop, and mobile apps. At [Multilayer](https://multilayer.io) we have analyzed probably hundreds, with a miriad of different tools and statistical methodologies. In our experience, when companies A/B tests, the biggest problems they encounter are around interpreting the results and acting appropiately on them. There are plenty of statistical libraries out there that do A/B testing right (babbab actually uses [PyMC](https://www.pymc.io/welcome.html) in the background). However, sharing statistics (like p-values) with non-statisticians can lead to confusion and [misuse](https://en.wikipedia.org/w/index.php?title=Misuse_of_p-values&oldid=1064797942) of results. What `babbab` tries to cover is the "last mile" of the A/B test analysis: Interpreting and communicating the results for them to be actionable. ### In other words - Why `babbab` is awesome - Get 4 numbers in, get a statistically valid statement that you can repeat to your manager verbatim, and a plot you can understand. - Get 4 numbers in + some labels, and you will get the above *and* a plot you can share *and* a statement you can C&P in the company chat. - Add a bit more work, and you have your own custom built AB testing dashboard/tool. Stop worrying about your peers and yourself misinterpreting stats. ## TODO list - Soft Launch This project is currently soft launched, which means that while you should feel free to use it and share it with friends, please let us know you are using it and please don't discuss it in social media as it's not ready and it's kind of a shy piece of software. Tasks to get out of this phase: - Add example results (plot, statement) to the README - Add example with labels to README - Add docstrings Maybe? - Sphinx or RTD Documentation

نیازمندی

مقدار	نام
-	matplotlib>=3.5.2
-	pymc>=4.1.2
-	arviz>=0.12.1
-	pytest>=6.2.5
-	jupyter>=1.0.0
-	jupyterlab>=3.1.14
-	black>=21.9b0
-	flake8>=3.9.2
-	isort>=5.9.3

نحوه نصب

نصب پکیج whl babbab-0.3.1:

pip install babbab-0.3.1.whl

نصب پکیج tar.gz babbab-0.3.1:

pip install babbab-0.3.1.tar.gz