topsis-decision-analysis 1.0.1

A Python implementation of the TOPSIS method for multi-criteria decision making

TOPSIS Implementation in Python

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

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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.

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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:

pip install topsis-mcdm-tool

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Usage

Run the following command in the Command Prompt / Terminal:

topsis <inputFile> <weights> <impacts> <outputFile>

Example

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

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Sample Input Format

Model,Price,Performance,Camera,Battery
A,25000,8,7,4000
B,30000,9,8,4500
C,20000,7,6,3800

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Output Columns

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

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Project Structure

topsis-mcdm-tool/
  topsis/
    __init__.py
    topsis.py
  sample.csv
  output.csv
  setup.py
  README.md

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License

This project is released under the MIT License.