Metadata-Version: 2.2
Name: topsis_Akshat_102203644
Version: 0.1.0
Summary: A Python package to perform TOPSIS (Technique for Order Preference by Similarity to Ideal Solution).
Home-page: https://github.com/Akshatkhurana/TOPSIS-package
Author: Akshat Khurana
Author-email: akhurana_be22@thapar.edu
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
Requires-Dist: numpy
Requires-Dist: pandas
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# TOPSIS Implementation in Python

This Python project implements the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The algorithm ranks alternatives based on multiple criteria, considering their relative importance (weights) and impacts (benefit or cost).

## Features

- **Input Validation**: Checks for correct input parameters, file format, and consistency in weights/impacts.
- **Error Handling**: Handles file-related errors, invalid data, and incorrect inputs gracefully.
- **Outputs**: Saves results including scores, rankings, and all original columns into a CSV file.

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## How to Use

1. Clone the repository and navigate to the project directory.
2. Ensure you have Python installed with the necessary packages.
3. Use the following command to run the program:
   ```bash
   python topsis.py <InputDataSet.csv> <Weights> <Impacts> <ResultFile.csv>


## Input dataset
![TOPSIS Example](images/ss1.png)

## Weights used
[1,1,1,1,1]

## Impacts used
[0,1,1,0,1]
### 1 for benifit
### 0 for cost

## Output
![Result](images/ss2.png)
