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ab-testing-analysis-1.2.7


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توضیحات

AB test analysis toolbox for analyzing and reporting the results of an ab test experiment. It provides the functions to analyze the ab test result of an experiment.
ویژگی مقدار
سیستم عامل -
نام فایل ab-testing-analysis-1.2.7
نام ab-testing-analysis
نسخه کتابخانه 1.2.7
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Mihir Deo
ایمیل نویسنده <mihirdeo16@gmail.com>
آدرس صفحه اصلی -
آدرس اینترنتی https://pypi.org/project/ab-testing-analysis/
مجوز -
# A/B-testing ![ab-testing-logo](https://raw.githubusercontent.com/mihir-workspace/ab-testing/main/assets/logo.png) [![Pypi](https://img.shields.io/pypi/v/ab-testing-analysis?color=blue&logo=PyPI)](https://pypi.org/project/ab-testing-analysis/) [![Read the Docs](https://img.shields.io/readthedocs/ab-testing-analysis?logo=Read%20the%20Docs&logoColor=blue)](https://ab-testing-analysis.readthedocs.io/en/latest/) [![PyPI - Downloads](https://img.shields.io/pypi/dm/ab-testing-analysis?color=orange)](https://pypi.org/project/ab-testing-analysis/) [![release date](https://img.shields.io/github/release-date/mihirdeo16/ab-testing?color=blueviolet&logo=GitHub)](https://github.com/mihirdeo16/ab-testing/releases) [![last commit](https://img.shields.io/github/last-commit/mihirdeo16/ab-testing?logo=git)](https://github.com/mihirdeo16/ab-testing/commits/main) [![CICD](https://img.shields.io/github/workflow/status/mihirdeo16/ab-testing/Upload%20Python%20Package?color=%232088FF&label=CICD&logo=GitHub%20Actions)](https://github.com/mihirdeo16/ab-testing/actions/workflows/python-publish.yml) [![Format](https://img.shields.io/pypi/format/ab-testing-analysis)](https://github.com/mihirdeo16/ab-testing) [![License](https://img.shields.io/pypi/l/ab-testing-analysis)](https://github.com/mihirdeo16/ab-testing/blob/main/LICENSE) [![size of files](https://img.shields.io/github/repo-size/mihirdeo16/ab-testing)](https://github.com/mihirdeo16/ab-testing) --- A/B testing is process which allows developer/data scientist to analyze and evaluate, the performance of products in an experiment. In this process two or more versions of a variable (web page, page element, products etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drives business metrics. In A/B testing, **A** refers to the original testing variable. Whereas **B** refers to a new version of the original testing variable. Impact of the results can be evaluated based on, + Conversion Rate + Significance test ---- #### Documentation can be found on- [ab-testing-analysis.readthedocs.io](https://ab-testing-analysis.readthedocs.io/en/latest/) ---- ## Installation & Usage + Installing the library from [pypi](https://pypi.org/project/ab-testing-analysis/) - It has only dependency on *pandas & numpy* ```shell pip install ab-testing-analysis ``` + Usages & working sample - [Tutorial](https://colab.research.google.com/github/mihirdeo16/ab-testing/blob/main/docs/Tutorial.ipynb) + Example code, ```python from ab_testing import ABTest from ab_testing.data import Dataset df = Dataset().data() ab_obj = ABTest(df,response_column='Response',group_column='Group') print(ab_obj.conversion_rate(),'\n','-'*10) print(ab_obj.significance_test(),'\n','-'*10) print(df.head()) ``` Output: ```shell Conversion Rate Standard Deviation Standard Error A 20.20% 0.401 0.018 B 22.20% 0.416 0.0186 ---------- z statistic: -0.77 p-value: 0.439 Confidence Interval 95% for A group: 16.68% to 23.72% Confidence Interval 95% for B group: 18.56% to 25.84% The Group A fail to perform significantly different than group B. The P-Value of the test is 0.439 which is above 0.05, hence Null hypothesis Hₒ cannot be rejected. ---------- Users Response Group 0 IS36FC7AQJ 0 A 1 LZW2YNYHZG 1 A 2 9588IGN0RN 1 A 3 HSAH1TYQFF 1 A 4 5D9G147941 0 A ``` ## Contribution All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome. A detailed overview on how to contribute can be found in the [contributing guide](https://ab-testing-analysis.readthedocs.io/en/latest/Contribution.html). ## Code of Conduct As contributors and maintainers to this project, you are expected to abide by code of conduct. More information can be found at [Code of conduct](https://ab-testing-analysis.readthedocs.io/en/latest/Code_of_conduct.html) ## License [MIT ](https://ab-testing-analysis.readthedocs.io/en/latest/Licence.html)


نیازمندی

مقدار نام
- pandas
- statsmodels


نحوه نصب


نصب پکیج whl ab-testing-analysis-1.2.7:

    pip install ab-testing-analysis-1.2.7.whl


نصب پکیج tar.gz ab-testing-analysis-1.2.7:

    pip install ab-testing-analysis-1.2.7.tar.gz