Metadata-Version: 2.1
Name: Topsis-Pranav-102103438
Version: 0.1.0
Summary: Topsis Package
Home-page: UNKNOWN
Author: Pranav Powar
Author-email: powar.pranav29@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: os

# TOPSIS Python Implementation

## Introduction

This Python script performs the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis on a CSV file. It calculates the TOPSIS score and ranking for each alternative based on the provided weights and impacts.

## Installation

Ensure you have Python installed. You need to have the following packages installed:
-pandas
-numpy
-os

## Usage

from topsis_package import topsis_from_csv

Specify input and output file paths

input_file_path = 'input_data.csv'  # Replace with your input CSV file
output_file_path = 'output_data.csv'  # Replace with your desired output CSV file

Specify weights and impacts

weights = [0.25, 0.25, 0.25, 0.25]  # Adjust based on your criteria
impacts = ['+', '+', '+', '+']  # Adjust based on your criteria

 Perform TOPSIS and write results to CSV

topsis_from_csv(input_file_path, output_file_path, weights, impacts)

print(f"TOPSIS results have been written to '{output_file_path}'.")


## Input Format

The input csv file should contain n columns with n-1 critera where the first column refers to the names of the attributes

## Output Format

The output csv file contains the all the input columns along with two additional columns, namely, TOPSIS Score and Rank. The TOPSIS Score column contains the TOPSIS score for each alternative and the Rank column contains the rank of each alternative based on the TOPSIS score.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

