Topsis-Devansh-102203449 0.1

A TOPSIS implementation package for Multiple Criteria Decision Making

TOPSIS-Devansh-102203449 Description This package implements the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for Multiple Criteria Decision Making (MCDM). TOPSIS is a method of compensatory aggregation that compares a set of alternatives based on their geometric distance from both the ideal best and ideal worst solutions. Installation Install the package using pip: bashCopypip install TOPSIS-Devansh-102203449 Usage Command Line Interface bashCopypython -m topsis_yourname Arguments:

InputDataFile: CSV file containing the decision matrix

First column: Object/Variable names 2nd to last columns: Numeric values only

Weights: Comma-separated weights (e.g., "1,1,1,2") Impacts: Comma-separated impacts, either + or - (e.g., "+,+,-,+") ResultFileName: Output CSV file name

Example: bashCopypython -m topsis_yourname input.csv "1,1,1,2" "+,+,-,+" output.csv Python Package Usage pythonCopyfrom topsis_yourname import topsis_score

Read your data into a pandas DataFrame

import pandas as pd df = pd.read_csv('input.csv')

Define weights and impacts

weights = [1, 1, 1, 2] impacts = ['+', '+', '-', '+']

Calculate TOPSIS scores

result = topsis_score(df, weights, impacts) result.to_csv('output.csv', index=False) Input File Format

CSV file with 3 or more columns First column: Object/Variable names All other columns: Numeric values only

Example input.csv: CopyModel,Price,Storage,Camera,Battery M1,800,256,12,4000 M2,900,512,16,4500 M3,850,256,16,4200 Output Format The output file will contain all columns from the input file plus two additional columns:

Topsis Score: The calculated TOPSIS score Rank: The rank based on the TOPSIS score

Error Handling The package handles the following errors:

Incorrect number of command-line parameters File not found Invalid file format Non-numeric values in columns Unequal number of weights, impacts, and columns Invalid impact symbols (must be + or -)

License This project is licensed under the MIT License - see the LICENSE file for details. Author [Devansh Dhir] Support For any questions or issues, please open an issue on the GitHub repository.