Topsis-Nimish-102017084 1.0.1

The module, topis requires pandas, math and sys modules to function This module is used to print the score and rank after using TOPSIS (Technique for Order Preference based on Similarity to Ideal Solution)

Submitted by:
Name: Nimish Lakhmani
Roll No: 102017084
Group: 3CS4

Installation

Install this package in the system using pip command.

bash pip install Topsis-Nimish-102017084

Usage

• Import the installed library using the following command.

bash import Topsis

You can import it using the first word coming before hypen (-) in library's name as shown above.

• Enter the three parameters in three lines:
  • .csv filename, followed by .csv extension
  • values of weights, each separated by comma(,)
  • values of impacts, either '+' or '-', each separated by comma(,)

bash sample.csv 0.25,0.25,0.25,0.25 -,+,+,+

Example of input & output

Input:

• sample.csv file, depicts the dataset of mobile phones having varying features.

Model	Price (in $)	Storage Space (in GB)	Camera (in MP)	Looks
M1	250	16	12	Excellent
M2	200	16	8	Average
M3	300	32	16	Good
M4	275	32	8	Good
M5	225	16	16	Below Average

• weights = [0.25,0.25,0.25,0.25]
• impacts = [-,+,+,+]

Output:

Model	Price (in $)	Storage Space (in GB)	Camera (in MP)	Looks	Topsis Score	Rank
M1	250	16	12	Excellent	0.526983	3
M2	200	16	8	Average	0.190599	5
M3	300	32	16	Good	0.809401	1
M4	275	32	8	Good	0.688168	2
M5	225	16	16	Below Average	0.422630	4

Important Points

• The first column is not considered while solving the MCDM Problem. Make sure the csv file follows the format as shown in sample.csv.
• Any column (from 2nd to last) containing categorical values is converted into numeric column .

License

MIT