Metadata-Version: 2.1
Name: Topsis-Varshini-102217252
Version: 1.0.0
Summary: TOPSIS implementation by Varshini Pallerla
Home-page: https://github.com/VarshiniPallerla/Topsis-Varshini-102217252/
Author: Varshini Pallerla
Author-email: vpallerla_be22@thapar.edu
License: MIT
Keywords: Topsis,main,Python,multiclassifier
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas

# TOPSIS Python Package

Made By: **Varshini Pallerla**  
Roll No: **102217252**

## Description

The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making method used to rank alternatives based on their similarity to an ideal solution. The TOPSIS Python Package is a library that provides an easy-to-use implementation of this method, helps in selecting the best alternative from a set of alternatives based on their performance across multiple criteria.

## Installation

You can install the package using pip:
pip install topsis-varshinipallerla

## Usage

Use the following command to perform TOPSIS analysis on a dataset:

python topsis.py data.csv "1,0,1,0,1" "+,-,+,-,+" output.csv

- topsis.py: Python file with code
- data.csv: Path to the input CSV file containing the dataset.
- "1,0,1,0,1": Weights for each criterion separated by commas.
- "+,-,+,-,+": Impacts for each criterion (either + for maximizing or - for minimizing).

The output will be saved in a file named output.csv


## Output
<img width="407" alt="Screenshot 2025-01-18 120809" src="https://github.com/user-attachments/assets/5e7ed82d-ed73-4078-8223-92a633930941" />

