topsis-sachet-102203345 1.0.0

A Python package to perform TOPSIS analysis on datasets.

TOPSIS Implementation in Python

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Overview

This Python script provides an implementation of the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, a widely used technique for multi-criteria decision-making. It calculates performance scores and ranks for a dataset based on specified weights and impacts.

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How to Use

Execute the script using the following command:

python topsis.py <inputFileName> <weights> <impacts> <resultFileName>

• <inputFileName>: Path to the CSV file containing the dataset.
• <weights>: Comma-separated list of weights for the criteria (e.g., 1,2,3).
• <impacts>: Comma-separated list of impacts for the criteria (+ for benefit, - for cost).
• <resultFileName>: Name of the output file where the results will be saved.

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Input File Guidelines

1. The input file must be a .csv format with a minimum of 3 columns.
2. The first column can contain non-numeric values (e.g., identifiers).
3. All columns from the second onward must contain numeric values.

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Key Features

• Validation:
  • Ensures the correct number of command-line arguments.
  • Validates weights, impacts, and the consistency of column counts.
  • Handles missing or invalid input files.
• Error Handling:
  • Provides clear error messages for issues such as missing files, non-numeric data, or mismatched parameters.
• Output Generation:
  • Adds two columns to the dataset: Topsis Score and Rank.
  • Saves the processed results to the specified output file.

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Prerequisites

• Python 3.x
• Required libraries: pandas, math, sys

Install dependencies using the command:

pip install pandas

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License

This project is open-source and available under the MIT License.