Skip to main content

THIS PACKAGE IS TO IMPLEMENT TOPSIS

Project description

TOPSIS_Shobhit_101903095

With this you can calculate the TOPSIS score and RANK of the data provided in '.csv' format.

  • Input file:
    • contain three or more columns
    • First column is the object/variable name.
    • From 2nd to last column contain numeric values only

Overview

  • it calculates the posis score and a rank based on that score

Usage

i have explained how to make use topsis yourself below

Getting it

To download TOPSIS use pip .

$ pip install TOPSIS_Shobhit_101903095

Using it

TOPSIS was programmed with ease-of-use in mind. Just, import topsis from TOPSIS_Shobhit_101903095.topsis1 import topsis topsis('inputfilename','Weights','Impacts','Outputfilename')

And you are ready to go!

Topsis

There are 5 steps in this:

  • normalized_matrix
  • weight_normalized
  • ideal_best_worst
  • euclidean_distance
  • topsis_score

License

MIT

Pre-requisite

The data should be in csv format and have more than 3 columns in it.

Result

the output(outputfilename) is saved in the project folder with extra 2 columns with topsis score and rank.

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_Shobhit_101903095-0.0.1.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

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

TOPSIS_Shobhit_101903095-0.0.1-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file TOPSIS_Shobhit_101903095-0.0.1.tar.gz.

File metadata

  • Download URL: TOPSIS_Shobhit_101903095-0.0.1.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.0

File hashes

Hashes for TOPSIS_Shobhit_101903095-0.0.1.tar.gz
Algorithm Hash digest
SHA256 a27776ee8dd53c83763cc65bde90bd7e9ad8e4db5ebc27bcf4d875a4dbe5231a
MD5 0d5aad4536cdf950b7c2e8c0aeb2381e
BLAKE2b-256 fe2b15ac6ffca6cc004a2d19a35f6ed64d355bb36f08baf19f21080e39d6605a

See more details on using hashes here.

File details

Details for the file TOPSIS_Shobhit_101903095-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: TOPSIS_Shobhit_101903095-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 4.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.11.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.0

File hashes

Hashes for TOPSIS_Shobhit_101903095-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4acbce329e51ca471374293e57f9ce43bd3cfdb49a416d3d451d7ac7ebd10df8
MD5 6429bdd3e724acbbc7a2054233d4f211
BLAKE2b-256 f93c7db9e973090b4ecc75138b616ada54db973f82df03c3535ec78b51bca885

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