Metadata-Version: 2.4
Name: topsis-decision-analysis
Version: 1.0.1
Summary: A Python implementation of the TOPSIS method for multi-criteria decision making
Author: Sartaj Singh Virdi
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: pandas
Requires-Dist: numpy
Dynamic: author
Dynamic: description
Dynamic: description-content-type
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# TOPSIS Implementation in Python

**Course:** UCS654 Predictive Analytics using Statistics  
**Assignment:** Assignment-1 (TOPSIS)  
**Author:** Sartaj Singh Virdi  
**Roll Number:** 102303259  

---

## About the Project

This project provides a Python implementation of the  
**TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)** method.

TOPSIS is a multi-criteria decision-making (MCDM) technique used to rank alternatives based on their distance from the ideal best and ideal worst solutions.

---

## Installation (User Manual)

This package requires **Python 3.7 or higher**.

### Dependencies

- pandas  
- numpy  

Package listed on PyPI: https://pypi.org/project/topsis-mcdm-tool/

Install the package using pip:
```bash
pip install topsis-mcdm-tool
```

---

## Usage

Run the following command in the Command Prompt / Terminal:
```bash
topsis <inputFile> <weights> <impacts> <outputFile>
```

### Example
```bash
topsis sample.csv "1,1,1,1" "+,+,-,+" result.csv
```

### Parameters

* inputFile: CSV or Excel file containing data
* weights: Comma-separated weights for each criterion
* impacts: + for benefit, - for cost criteria
* outputFile: Output CSV/Excel file with scores and ranks

---

## Sample Input Format
```csv
Model,Price,Performance,Camera,Battery
A,25000,8,7,4000
B,30000,9,8,4500
C,20000,7,6,3800
```

---

## Output Columns

* Topsis Score: Closeness coefficient
* Rank: Ranking of alternatives

---

## Project Structure
```
topsis-mcdm-tool/
  topsis/
    __init__.py
    topsis.py
  sample.csv
  output.csv
  setup.py
  README.md
```

---

## License

This project is released under the MIT License.
