102203236-Topsis 0.0.1

A Python package for TOPSIS multi-criteria decision making

102203236_Topsis

Overview

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making (MCDM) method used for ranking and selecting alternatives based on multiple criteria. This Python package allows users to easily apply the TOPSIS method to their datasets.

Features

• Reads data from an Excel file.
• Automatically normalizes the data.
• Applies user-defined weights and impacts to criteria.
• Computes the TOPSIS score and ranks alternatives.
• Outputs the final decision-making table with rankings.

Installation

Install the package using pip:

pip install 102203236_Topsis

Usage

Import the package

from topsis import Topsis

Example

# Importing the package
from topsis import Topsis

# Define the input parameters
filename = "data.xlsx"
impacts = ['+','+','+','-','+']
weights = [0.25, 0.25, 0.25, 0.25, 0.25]

# Run TOPSIS
result = Topsis(filename, impacts, weights).get_result()

# Print the ranked result
print(result)

Expected Input Format

The input Excel file should contain numeric data for decision-making criteria. An example format:

Fund Name	Criterion 1	Criterion 2	Criterion 3	Criterion 4	Criterion 5
Fund A	250	3.5	1200	8	85
Fund B	275	4.0	1150	7	90
Fund C	260	3.8	1250	6	88

Output Format

The output DataFrame includes the original data with additional columns:

• Score: Computed TOPSIS score.
• Rank: Final ranking based on the score.

Dependencies

This package requires:

• pandas
• numpy

These dependencies will be automatically installed when using pip install 102203236_Topsis.

License

This project is licensed under the MIT License.

Contributing

Pull requests are welcome! If you have suggestions or improvements, feel free to submit an issue or PR.

Author

• Name: Pranav Khurana
• GitHub: https://github.com/PranavKhurana117?tab=repositories
• Email: [e-mail]

---

Enjoy using the TOPSIS package! 🚀