topsis-arryuann-102103062 1.0.2

It returns the csv file with topsis score as well as the rank to the provided csv file.

topsis-Arryuann-102103062

for: Assignment01-Topsis (UCS633) submitted by: Arryuann Khanna Roll no: 102103062 Group: 3COE3 This Python library helps with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

Installation

pip install topsis-Arryuann-102103062

How to use it?

Open terminal and enter a valid csv filename followed by .csv extentsion, then enter the weights vector with vector values separated by commas, then impacts vector with comma separated signs (+,-) and finally the output file name in csv format.

topsis 102103062-data.csv "1,1,1,1" "+,-,+,+" 102103062-result-1.csv

Example

If you have this content inside the 102103062-data.csv-

Fund Name	P1	P2	P3	P4	P5
M1	0.88	0.77	3.0	57.7	15.59
M2	0.87	0.76	4.9	39.4	11.48
M3	0.91	0.83	5.5	59.4	16.66
M4	0.61	0.37	3.2	39.6	10.95
M5	0.60	0.36	5.6	62.3	17.22
M6	0.77	0.59	6.1	51.5	14.74
M7	0.61	0.37	4.7	43.3	12.25
M7	0.71	0.50	6.1	42.6	12.48

and you ran the command-

topsis 102103062-data.csv "1,1,1,1,1" "+,-,+,-,+" 102103062-result-1.csv

you get this as output-

 Fund Name    P1    P2   P3    P4     P5  Topsis Score  Rank
0        M1  0.88  0.77  3.0  57.7  15.59      0.626255     1
1        M2  0.87  0.76  4.9  39.4  11.48      0.535066     3
2        M3  0.91  0.83  5.5  59.4  16.66      0.460473     4
3        M4  0.61  0.37  3.2  39.6  10.95      0.559417     2
4        M5  0.60  0.36  5.6  62.3  17.22      0.363836     7
5        M6  0.77  0.59  6.1  51.5  14.74      0.353200     8
6        M7  0.61  0.37  4.7  43.3  12.25      0.455437     5
7        M8  0.71  0.50  6.1  42.6  12.48      0.378622     6

and also saved in 102103062-result-1.csv in current working directory

License

© 2024 Arryuann Khanna

This repository is licensed under the MIT license. See LICENSE for details.