Metadata-Version: 2.3
Name: DEAPack
Version: 0.1.0
Summary: A Data Envelopment Analysis Package
Project-URL: Homepage, https://github.com/daopingw/DEAPack
Project-URL: Bug Tracker, https://github.com/daopingw/DEAPack/issues
Author-email: Dr Daoping Wang <daopingwang@outlook.com>
License: MIT License
        
        Copyright (c) 2024 Dr Daoping Wang (daopingwang@outlook.com)
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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License-File: LICENSE
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: numpy<2.0.0,>=1.26.0
Requires-Dist: pandas>=2.2.0
Requires-Dist: pulp>=2.6.0
Description-Content-Type: text/markdown

# DEAPack: A Data Envelopment Analysis Package

DEAPack is a Python package designed for Data Envelopment Analysis (DEA). Its comprehensive toolset allows for efficient handling of various DEA models, including those that account for undesirable outputs.

## Installation

Install the package by `pip`,

```sh
pip install DEAPack
```
Or install the package by `conda`,
```sh
conda install DEAPack
```

## Usage

A brief example is provided below. For more information, please refer to the [documentation]() and [example notebooks]().

```python
# import the module
from DEAPack.model import DEA
from DEAPack.utilities import load_example_data

# load the example dataset
data = load_example_data()

# initilise a DEA model
model = DEA()

# specify the DEA model
model.DMUs = data['region']
model.time = data['year']
model.x_vars = data[['K', 'L', 'E']]
model.y_vars = data[['Y']]
model.b_vars = data[['CO2']]

# solve the DEA model
model.solve()

# get estimated efficiencies
results = model.get_efficiency()
```

## Communication

You're very welcome to contribute to this package. We appreciate any efforts to improve this package. You can help by adding new features, reporting bugs, or extending the documentation and usage examples. Please contact us if you have any ideas.

- [Pull requests](https://github.com/daopingw/DEAPack/pulls) for pull requests.
- [Issues](https://github.com/daopingw/DEAPack/issues) for bug reports.
