A python package for implementing topsis
Project description
Topsis-LalitSingla-102383006
Assignment(UCS654)
Submitted by: Lalit Singla
Roll no: 102383006
Group: 3C14
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-LalitSingla-102383006
Example:
Sample dataset
| P1 | P2 | P3 | P4 | P5 |
|---|---|---|---|---|
| 0.84 | 0.71 | 6.7 | 42.1 | 12.59 |
| 0.91 | 0.83 | 7.0 | 31.7 | 10.11 |
| 0.79 | 0.62 | 4.8 | 46.7 | 13.23 |
| 0.78 | 0.61 | 6.4 | 42.4 | 12.55 |
| 0.94 | 0.88 | 3.6 | 62.2 | 16.91 |
| 0.88 | 0.77 | 6.5 | 51.5 | 14.91 |
| 0.66 | 0.44 | 5.3 | 48.9 | 13.83 |
| 0.93 | 0.86 | 3.4 | 37.0 | 10.55 |
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_LalitSingla_102383006 data.xlsx "1,1,1,1,1" "+,-,+,-,+" output.csv
Output
This will be in our Output csv file
| P1 | P2 | P3 | P4 | P5 | Topsis Score | Rank |
|---|---|---|---|---|---|---|
| 0.84 | 0.71 | 6.7 | 42.1 | 12.59 | 0.5945517248616172 | 2 |
| 0.91 | 0.83 | 7.0 | 31.7 | 10.11 | 0.5662461787825045 | 3 |
| 0.79 | 0.62 | 4.8 | 46.7 | 13.23 | 0.4853941230447056 | 6 |
| 0.78 | 0.61 | 6.4 | 42.4 | 12.55 | 0.6127758823558636 | 1 |
| 0.94 | 0.88 | 3.6 | 62.2 | 16.91 | 0.36155091758331526 | 8 |
| 0.88 | 0.77 | 6.5 | 51.5 | 14.91 | 0.5387640655736284 | 5 |
| 0.66 | 0.44 | 5.3 | 48.9 | 13.83 | 0.560458620506467 | 4 |
| 0.93 | 0.86 | 3.4 | 37.0 | 10.55 | 0.38966293040831607 | 7 |
Published Package on pypi.org
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