Metadata-Version: 2.2
Name: topsis_Navyaa_102203276
Version: 1.0.0
Summary: A Python package to perform TOPSIS (Technique for Order Preference by Similarity to Ideal Solution).
Home-page: https://github.com/blackangrybird/TOPSIS-package
Author: Navyaa Gupta
Author-email: ngupta_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 package implements the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It ranks alternatives based on multiple criteria while considering their weights (importance) and impacts (benefit or cost).

## Features

- **Input Validation**: Ensures the dataset, weights, and impacts are correctly formatted.
- **Error Handling**: Handles invalid data, incorrect parameters, and file-related issues gracefully.
- **Outputs**: Generates a CSV file with scores, rankings, and original data columns.

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## How to Use

1. Clone the repository and navigate to the project directory.
2. Ensure Python is installed with the required libraries.
3. Run the program using the following command:
   ```bash
   python -m topsis_Navyaa_102203376.topsis <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)

