Metadata-Version: 2.1
Name: Topsis-Anirudh-102283008
Version: 0.2
Summary: Topsis
Home-page: https://github.com/AnirudhBansal01/Topsis-Anirudh-102283008
Download-URL: https://github.com/AnirudhBansal01/Topsis-Anirudh-102283008/archive/refs/tags/v_01.tar.gz
Author: Anirudh Bansal
Author-email: abansal11_be21@thapar.edu
License: MIT
Keywords: Python,Topsis,Ranking
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: pandas

# TOPSIS


Submitted By: **Anirudh Bansal**

***

## Key Features:

### TOPSIS Algorithm Implementation:
This pacakge incorporates a robust and efficient implementation of the TOPSIS algorithm. It considers both positive and negative ideal solutions, calculating the relative closeness of alternatives to the ideal solution.

### The package is designed with a user-friendly interface, allowing users to input their decision matrices easily. The library handles the complexity of the TOPSIS method while providing a simple API for users.

### Customizable Weights:
This pacakge enables users to assign different weights to each criterion, allowing for flexibility in reflecting the relative importance of criteria in decision-making scenarios.

### Sensitivity Analysis:
Conduct sensitivity analyses to understand the impact of changes in criteria weights on the final decision. This pacakge provides tools for exploring various scenarios and making informed decisions.

### Result Interpretation:
The package provides intuitive result interpretation, presenting the ranked alternatives based on their closeness to the ideal solution. Detailed reports and visualizations aid in understanding the decision-making process.

### Compatibility:
This pacakge is compatible with Python 3.x and integrates seamlessly into various data science and analytics workflows. It can be easily incorporated into Jupyter notebooks, scripts, or larger applications.

## How to install this package:
```
>> pip install TOPSIS-Anirudh-102283008
```


### In Command Prompt
```
>> topsis data.csv "1,1,2,1" "+,+,-,+" result.csv
```
