Topsis-Aparna-102016091 0.3

A python package implementing topsis

Submitted By: Aparna Sood

What is TOPSIS?

Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.

It is a package for Multiple-criteria decision-making using TOPSIS. Requires input file,weights and impacts. Returns a data frame which has score and rank of every label. This package helps improve decision-making.

Installation

pip install Topsis-Aparna-102016091

Usage

import Topsis_Aparna_102016091 as ap 
ap.topsisscore(inputfilename.csv , weights , impacts , outputfilename.csv)

• weights and impacts provided as parameters should be separated by comma(,) and equal to number of columns.
• weights should only contain numeric values
• the categorical column should either be dropped or enginnered into a numerical column

Take care of these and you are ready to go.

Result

The output (outputfilename.csv) is saved as csv file, with extra two columns of topsis score and rank. Rank 1 signifies best decision.

Contribution

Pull requests are welcome!!

Example

inputfilename.csv

Fund Name	P1	P2	P3	P4	P5
M1	0.8	0.64	6.9	44.5	13.21
M2	0.81	0.66	7	33.1	10.39
M3	0.89	0.79	4.1	49.1	13.72
M4	0.8	0.64	4.8	45.1	12.84
M5	0.79	0.62	7	65.1	18.38
M6	0.8	0.64	4.1	51.2	14.19
M7	0.61	0.37	4.2	48	13.3
M8	0.71	0.5	4.1	43.1	12.1

weights = "1,1,1,1,1"

impacts = "+,-,+,-,+"

outputfilename.csv

FIELD1	Fund Name	P1	P2	P3	P4	P5	topsis score	rank
0	M1	0.8	0.64	6.9	44.5	13.21	0.5513405258358909	1.0
1	M2	0.81	0.66	7.0	33.1	10.39	0.5474324527004779	2.0
2	M3	0.89	0.79	4.1	49.1	13.72	0.356585782293044	8.0
3	M4	0.8	0.64	4.8	45.1	12.84	0.4305717292651279	6.0
4	M5	0.79	0.62	7.0	65.1	18.38	0.5240978466600755	3.0
5	M6	0.8	0.64	4.1	51.2	14.19	0.38297613208032333	7.0
6	M7	0.61	0.37	4.2	48.0	13.3	0.5010998980377374	4.0
7	M8	0.71	0.5	4.1	43.1	12.1	0.45991281671067175	5.0