Skip to main content

TOPSIS implementation using Python

Project description

TOPSIS Implementation in Python

Course: UCS654 – Predictive Analytics using Statistics
Assignment: Assignment-1 (TOPSIS)
Author: Raj Gupta
Roll Number: 102303324


About the Project

This project provides a Python implementation of the
TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method.

TOPSIS is a multi-criteria decision-making (MCDM) technique used to rank alternatives based on their distance from the ideal best and ideal worst solutions.


Installation (User Manual)

This package requires Python 3.7 or higher.

Dependencies

  • pandas
  • numpy

Package listed on PyPI:- https://pypi.org/project/topsis-rajgupta-102303324/

Install the package using pip:

pip install topsis-rajgupta-102303324

Usage

Run the following command in the Command Prompt / Terminal:

topsis <inputFile> <weights> <impacts> <outputFile>

Example

topsis sample.csv "1,1,1,1" "+,+,-,+" result.csv

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

topsis_rajgupta_102303324-1.0.3.tar.gz (2.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

topsis_rajgupta_102303324-1.0.3-py3-none-any.whl (3.5 kB view details)

Uploaded Python 3

File details

Details for the file topsis_rajgupta_102303324-1.0.3.tar.gz.

File metadata

File hashes

Hashes for topsis_rajgupta_102303324-1.0.3.tar.gz
Algorithm Hash digest
SHA256 a5e74be77fc6d0880dfdd4f38af933392ad2282e55698f533b54a7b3a0983929
MD5 b85d3d2292b76a6a25f01932a66659f4
BLAKE2b-256 4ec0b68fc7b0edf6ae952006b0fc379dd1466907052a28085dcde15e21899c24

See more details on using hashes here.

File details

Details for the file topsis_rajgupta_102303324-1.0.3-py3-none-any.whl.

File metadata

File hashes

Hashes for topsis_rajgupta_102303324-1.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 066d03337344c3771ffa1dfeb2f74e01d243e236d9e36afe8f09019875cf1fb0
MD5 9306627a3c56cdfed0e174e315139dbd
BLAKE2b-256 d4ad2c8595993c46432579631738f966ff232b54147e3ec11bb59fbd59b98cf0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page