Topsis-Vishard-102317240 1.0.1

A command-line Python package to implement the TOPSIS method.

TOPSIS-Vishard-102317240

📝 Overview

Topsis-Vishard-102317240 is a Python library for performing Multi-Criteria Decision Making (MCDM) using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) algorithm. It allows you to rank alternatives based on multiple conflicting criteria, providing a robust mathematical approach to decision-making.

This package is designed to be simple, efficient, and easy to integrate into your data analysis workflows.

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🔧 Installation

You can install the package directly from PyPI using pip:

pip install Topsis-Vishard-102317240

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🚀 Usage

The package provides a command-line interface (CLI) for ease of use.

Syntax

topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>

Parameters

• InputDataFile: Path to the input CSV file containing the data.
• Weights: Comma-separated numbers representing the importance of each criterion (e.g., 1,1,1,2).
• Impacts: Comma-separated signs (+ or -) indicating if a criterion is beneficial (+) or non-beneficial (-).
• ResultFileName: Path where the output CSV file with results will be saved.

Example

topsis data.csv "1,1,1,1,2" "+,+,-,+,+" result.csv

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📊 Input Data Format

The input CSV file should strictly follow this structure:

1. First Column: Object/Alternative Name (e.g., M1, M2, M3).
2. Subsequent Columns: Numeric values for each criterion.

Fund Name	P1	P2	P3	P4	P5
M1	0.94	0.88	6.5	38.8	11.78
M2	0.69	0.48	4.4	59.8	16.34
...	...	...	...	...	...

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📤 Output

The output file will contain the original data along with two new columns:

• Topsis Score: The calculated score for each alternative (higher is better).
• Rank: The ranking of the alternative based on the score (1 is best).

Fund Name	...	Topsis Score	Rank
M5	...	0.6988	1
M8	...	0.5955	2
...	...	...	...

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📜 License

This project is licensed under the MIT License.

👤 Author

Vishard Mehta

• Email: [e-mail]
• PyPI: Topsis-Vishard-102317240