Metadata-Version: 2.1
Name: topsis-anshul-102303930
Version: 1.0.1
Summary: A Python package for TOPSIS multi-criteria decision making
Author: Anshul Kaushal
Author-email: anshulkaushal27@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy

\# Topsis-Anshul-102303930



\## 📌 Description

This package implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method.

TOPSIS is a multi-criteria decision-making approach used to rank alternatives based on their distance from

an ideal best and an ideal worst solution.



---



\## ⚙️ Installation

Install the package using pip:



```bash

pip install Topsis-Anshul-102303930



\## Usage

\# After installation, the topsis command becomes available in the terminal.
topsis <input_csv> <weights> <impacts> <output_csv>

Parameters
Parameter	Description
input_csv	CSV file containing the dataset
weights	Comma-separated numerical weights
impacts	Comma-separated impacts (+ for benefit, - for cost)

Example Commands

topsis sample.csv "1,1,1,1" "+,-,+,+"


Weights and impacts can also be provided without quotes:

topsis sample.csv 1,1,1,1 +,-,+,+


Example
Input File (sample.csv)

A CSV file showing data for different mobile handsets with varying features:

Model,Storage space(in gb),Camera(in MP),Price(in $),Looks(out of 5)
M1,16,12,250,5
M2,16,8,200,3
M3,32,16,300,4
M4,32,8,275,4
M5,16,16,225,2

Weights Vector
[0.25, 0.25, 0.25, 0.25]

Impacts Vector
[+, +, -, +]

Command
topsis sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+"

Output
TOPSIS RESULTS
-----------------------------

   P-Score    Rank
1  0.534277     3
2  0.308368     5
3  0.691632     1
4  0.534737     2
5  0.401046     4
