Topsis-Devansh-102317041 2.0

A Python package for TOPSIS

📊 TOPSIS-Devansh-102317041

A Python library for Multiple Criteria Decision Making (MCDM) using TOPSIS

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🎯 Overview

TOPSIS-Devansh-102317041 is a Python package that implements the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for solving Multiple Criteria Decision Making (MCDM) problems.

This package simplifies the process of ranking alternatives based on multiple criteria

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🧠 What is TOPSIS?

TOPSIS is a multi-criteria decision analysis method that:

1. Identifies the ideal best and ideal worst alternatives
2. Calculates the Euclidean distance from each alternative to both ideal solutions
3. Ranks alternatives based on their relative closeness to the ideal solution

The alternative closest to the ideal best and farthest from the ideal worst is ranked highest.

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📦 Installation

Install the package using pip:

pip install Topsis-Devansh-102317041

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🚀 Usage

Basic Syntax

topsis <input_file.csv> <weights> <impacts> <output_file.csv>

Parameters

Parameter	Description	Format
input_file.csv	Input CSV file with decision matrix	.csv file
weights	Comma-separated weights for each criterion	"w1,w2,w3,..."
impacts	Comma-separated impacts (+/-) for each criterion	"+,-,+,..."
output_file.csv	Output CSV file with rankings	.csv file

Command Examples

With quotes (recommended):

topsis data.csv "1,1,1,1" "+,+,-,+" output.csv

⚠️ Note: Use quotes if your input contains spaces to avoid errors.

Help Command

topsis --help

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💡 Example

Input File: sample.csv

A dataset comparing mobile phones based on different features:

Model	Storage (GB)	Camera (MP)	Price ($)	Looks (out of 5)
M1	16	12	250	5
M2	16	8	200	3
M3	32	16	300	4
M4	32	8	275	4
M5	16	16	225	2

Parameters

• Weights: [0.25, 0.25, 0.25, 0.25] (Equal importance)
• Impacts: [+, +, -, +]
  • + for Storage, Camera, and Looks (higher is better)
  • - for Price (lower is better)

Command

topsis sample.csv "0.25,0.25,0.25,0.25" "+,+,-,+" output.csv

Output: output.csv

Model	Storage (GB)	Camera (MP)	Price ($)	Looks (out of 5)	TOPSIS Score	Rank
M1	16	12	250	5	0.5343	3
M2	16	8	200	3	0.3084	5
M3	32	16	300	4	0.6916	1
M4	32	8	275	4	0.5347	2
M5	16	16	225	2	0.4010	4

Result: Model M3 ranks first with the highest TOPSIS score of 0.6916.

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📄 Input File Format

Requirements

✅ CSV file format
✅ First row contains column headers
✅ First column contains alternative names/IDs
✅ All criteria values must be numeric
✅ No missing values
✅ At least 3 alternatives and 2 criteria

Sample Structure

Model,Criterion1,Criterion2,Criterion3
Alt1,value1,value2,value3
Alt2,value1,value2,value3
Alt3,value1,value2,value3

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⚠️ Important Notes

1. Headers and Index: The first column and first row are treated as labels and removed before processing
2. Numeric Values Only: Ensure all criteria values are numeric (no categorical data)
3. Weights Format: Weights should be positive numbers (will be normalized automatically)
4. Impacts Format: Use only + (beneficial) or - (non-beneficial)
5. Dimension Matching: Number of weights and impacts must match the number of criteria
6. Minimum Data: At least 3 alternatives and 2 criteria required

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📜 License

This project is licensed under the MIT License.

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👨‍💻 Author

Devansh Chhabra
📧 Email: [e-mail]

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