Skip to main content

A Python package to implement Topsis analysis

Project description

topsis-python

Topsis analysis of a csv file

""UCS633 Project Submission""

Name - Hitesh Gupta

Roll no. - 101703235

About Topsis

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993. TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS).

Installation

pip install topsis-hitesh

Usage

Following query on terminal will provide you the topsis analysis for input csv file.

topsis-hitesh -n "dataset-name.csv" -w "w1,w2,w3,w4,..." -i "i1,i2,i3,i4,..."

w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize. Size of w and i is equal to number of features.

Note that the first row and first column of dataset is dropped

Rank 1 signifies best decision

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.

License

MIT

Project details


Release history Release notifications

Download files

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

Files for topsis-hitesh, version 1.0.0
Filename, size File type Python version Upload date Hashes
Filename, size topsis-hitesh-1.0.0.tar.gz (3.1 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page