Skip to main content

A Python package to implement Topsis

Project description

topsis-python

Topsis analysis of a csv file in python

About Topsis

It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion. An assumption of TOPSIS is that the criteria are monotonically increasing or decreasing. Normalisation is usually required as the parameters or criteria are often of incongruous dimensions in multi-criteria problems

Installation

pip install topsis33

Usage

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

topsis33 -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

License

MIT

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

topsis33-1.0.0.tar.gz (3.6 kB view hashes)

Uploaded source

Built Distribution

topsis33-1.0.0-py3-none-any.whl (4.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page