Metadata-Version: 2.1
Name: uplift-analysis
Version: 0.0.3
Summary: A Python library providing analysis utilities for uplift modeling techniques.
Home-page: https://github.com/PlaytikaOSS/uplift-analysis
Author: Dvir Ben Or
Author-email: dvirb@playtika.com
Project-URL: Bug Tracker, https://github.com/PlaytikaOSS/uplift-analysis/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: develop
License-File: LICENSE
License-File: AUTHORS.rst

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uplift-analysis
================

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**uplift-analysis** is a ``Python`` library that contains implementations of methods and utilities, which can serve use
cases requiring the analysis of uplift modeling techniques.<br/>
The implemented modules include scoring utilities, analysis strategy, and relevant visualization methods.

This library works for Python 3.7 and higher.

Installation
------------
This library is distributed on [PyPi](https://pypi.org/project/uplift-analysis) and can be installed using ``pip``.

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ pip install uplift-analysis 
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The command above will automatically install all the required dependencies. Please visit the
[installation](https://PlaytikaOSS.github.io/uplift-analysis/build/html/installation.html) page for more details.



Getting started
---------------
Check out the comprehensive [tutorial](https://PlaytikaOSS.github.io/uplift-analysis/build/html/tutorials.html) for
a complete walk-through of the library.

```python
import pandas as pd
from uplift_analysis import data, evaluation

eval_set = data.EvalSet(df=pd.DataFrame({
    'observed_action': treatments,
    'responses': responses,
    'score': scores,
    'proposed_action': recommended_treatments
}))

evaluator = evaluation.Evaluator()
eval_res, summary = evaluator.eval_and_show(eval_set, specify=['uplift'],
                                            show_random=True, num_random_rep=4)
```

![uplift](./_images/uplift_curve.png)


Documentation
-------------
For more information, refer to the accompanying blogpost
["Analyzing Uplift Models"](https://www.playtika-blog.com/playtika-ai/analyzing-uplift-models/), the package's
[complete documentation](https://PlaytikaOSS.github.io/uplift-analysis),
and the walkthrough [tutorials](https://PlaytikaOSS.github.io/uplift-analysis/build/html/tutorials.html).




Info for developers
-------------------

The source code of the project is available on [GitHub](https://github.com/PlaytikaOSS/uplift-analysis).

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ git clone https://github.com/PlaytikaOSS/uplift-analysis.git
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

You can install the library and the dependencies with one of the following commands:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ pip install .                        # install library + dependencies
$ pip install ".[develop]"             # install library + dependencies + developer-dependencies
$ pip install -r requirements.txt      # install dependencies
$ pip install -r requirements-dev.txt  # install developer-dependencies
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For creating the "*pip-installable*" ``*.whl`` file, run the following command (at the root of the repository):

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ python -m build
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For creating the HTML documentation of the project, run the following commands:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ cd docs
$ make clean
$ make html
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Run tests
---------

Tests can be executed with ``pytest`` running the following commands:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
$ cd tests
$ pytest                                      # run all tests
$ pytest test_testmodule.py                   # run all tests within a module
$ pytest test_testmodule.py -k test_testname  # run only 1 test
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

License
-------

[MIT License](LICENSE)
