Metadata-Version: 2.4
Name: topsis-raghav-102303580
Version: 1.0.2
Summary: TOPSIS implementation as a Python package
Author: Raghav
Author-email: raghavchhabra291984@gmail.com
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: summary

# TOPSIS Implementation (Python Package)

## Overview
This Python package provides a clear and practical implementation of the  
**TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)** method for  
**Multi-Criteria Decision Making (MCDM)**.

Using this package, users can rank multiple alternatives based on numerical criteria by
assigning **weights** and **impacts** (benefit or cost) to each criterion.  
The package is implemented as a **command-line tool** and works directly with CSV files.

---

## Project Information

| Field | Details |
|------|--------|
| Course | Project-1 |
| Author | Raghav Chhabra |
| Roll No | 102303580 |
| Group | **3C42** |

---

## Features
- Easy-to-use command-line interface
- Supports customizable weights and impacts
- Handles benefit (`+`) and cost (`-`) criteria
- Accepts CSV input and produces CSV output
- Automatically computes **TOPSIS score** and **Rank**

---

## 📌 Sample Input File (IMPORTANT)

Create a file named **`data.csv`** in the same folder as `topsis.py` and paste the following content:

```csv
Fund,P1,P2,P3,P4,P5
M1,0.71,0.50,3.9,33.8,9.73
M2,0.88,0.77,5.2,45.8,13.16
M3,0.78,0.61,3.8,40.1,11.32
M4,0.91,0.83,5.8,43.8,12.84
M5,0.76,0.58,6.4,34.8,10.6
```

---

## Installation

Install the package using pip:

```bash
pip install topsis-raghav-102303580

