Skip to main content

TOPSIS implementation by Sirisha Singla

Project description

Topsis Package

Made by Sirisha Singla (Roll Number - 102103715)

Inroduction

Topsis is a Python package that provides an implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS is a multi-criteria decision-making method that helps in selecting the best alternative from a set of alternatives based on their proximity to the ideal solution.

Installation

pip install Topsis-Sirisha-102103715

Usage

Type the following command to run the package

python Topsis.py 102103715-data.xlsx "1,1,1,1,1" "+,+,-,+,+" result.csv

Topsis.py : This is the name of the Python script file that you want to run.
102103715-data.xlsx: This is the input data file in Excel format (xlsx). It contains the data on which the Topsis analysis will be performed.
"1,1,1,1,1": These are the weights assigned to each column in the dataset.
"+,+,-,+,+": These are the impacts corresponding to each criterion.The impacts are +,+,+,-,+. The impact '+' indicates that the criterion is beneficial, and '-' indicates that the criterion is non-beneficial.
result.csv: This is the name of the output CSV file where the results of the Topsis analysis will be saved.

License

© 2024 Sirisha Singla

This repository is licensed under the MIT license. See LICENSE for details.

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-Sirisha-102103715-1.0.0.tar.gz (4.0 kB view details)

Uploaded Source

Built Distribution

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

Topsis_Sirisha_102103715-1.0.0-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file Topsis-Sirisha-102103715-1.0.0.tar.gz.

File metadata

File hashes

Hashes for Topsis-Sirisha-102103715-1.0.0.tar.gz
Algorithm Hash digest
SHA256 ad205b6265f24201d10e6889060eac683098282763ecf3d7ea49523742f271cf
MD5 ab87eca30822fc25d5f6fbe094cabcfd
BLAKE2b-256 93623b9644a67416469c121f891e9980cd3410981eb3a4b4eaea8947e9ffcba0

See more details on using hashes here.

File details

Details for the file Topsis_Sirisha_102103715-1.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for Topsis_Sirisha_102103715-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4ab8fec3f6d26fcf649b70f316a1a8e50731b29c239d604877adec8cd7766dc8
MD5 918803ea833fde9cd1b1db8a76ead28b
BLAKE2b-256 b777cfc4cbe09d2efa8e223f4e1240a1a1b837d8647546ffe1ca3e8d2e787ae9

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