Skip to main content

A python package for implementing topsis

Project description

Topsis-Tanisha-102103372

For : Assignment(UCS654)
Submitted by: Tanisha Sood
Roll no:102103372
Group:3COE14

Description

This is a python package used to implement TOPSIS(Technique of Order Preference Similarity to the Ideal Solution) for MCDA(Multiple criteria decision analysis)


How to use this package:

Installation

pip install Topsis-Tanisha-102103372

Example:

Sample dataset

Fund Name P1 P2 P3 P4 P5
M1 0.78 0.61 5.5 34.7 10.4
M2 0.88 0.77 5 58.4 16.26
M3 0.61 0.37 5.9 39.9 11.7
M4 0.76 0.58 4.2 57.7 15.81
M5 0.84 0.71 3.2 48 13.19
M6 0.76 0.58 4 68.8 18.54
M7 0.81 0.66 6.5 38.2 11.54
M8 0.81 0.66 3.2 32.8 9.37

Input

In Command Prompt

Enter filename followed by .csv or .xlsx extension, then enter values of weights separated by commas like "1,1,1,2,2",then enter values of impacts separated by commas like "+,+,-,-,+" without giving space in between comma value, then enter name of file where you want to save output followed by .csv extension

python -m Topsis_Tanisha-102103372 data.xlsx "1,1,1,2,2" "+,+,-,-,+" output.csv

Output

This will be in our Output csv file

Fund Name P1 P2 P3 P4 P5 Topsis Score Rank
M1 0.78 0.61 5.5 34.7 10.4 0.5303740545041122 4
M2 0.88 0.77 5 58.4 16.26 0.5372510220778413 3
M3 0.61 0.37 5.9 39.9 11.7 0.4715707210914604 8
M4 0.76 0.58 4.2 57.7 15.81 0.5099483054760279 6
M5 0.84 0.71 3.2 48 13.19 0.57723478293325 1
M6 0.76 0.58 4 68.8 18.54 0.49447887833737925 7
M7 0.81 0.66 6.5 38.2 11.54 0.5244107252631429 5
M8 0.81 0.66 3.2 32.8 9.37 0.5576533672285703 2

Project details


Release history Release notifications | RSS feed

This version

0.2

Download files

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

Source Distribution

Tanisha_102103372-0.2.tar.gz (3.2 kB view details)

Uploaded Source

Built Distribution

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

Tanisha_102103372-0.2-py3-none-any.whl (3.6 kB view details)

Uploaded Python 3

File details

Details for the file Tanisha_102103372-0.2.tar.gz.

File metadata

  • Download URL: Tanisha_102103372-0.2.tar.gz
  • Upload date:
  • Size: 3.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for Tanisha_102103372-0.2.tar.gz
Algorithm Hash digest
SHA256 1db28aa783031f446dbd65605b14049141d211a283cd09f976a6ea798620afa7
MD5 9290240aa3bc556c7d8b1823f2f6442a
BLAKE2b-256 876a633bbf6ceb90685a5cb1d74b956f486ac9c020df291f38d523127d06988f

See more details on using hashes here.

File details

Details for the file Tanisha_102103372-0.2-py3-none-any.whl.

File metadata

File hashes

Hashes for Tanisha_102103372-0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 f378e232edd8040a9812625520bcadf095bf80703acdd1054d1abfe9febca795
MD5 609bdeed37fb76a6fa466fd552db84d0
BLAKE2b-256 73e0cdf855ebf36d016e02ba2b09ad9cb297be94f76f5a459c46cd130450d7bd

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