Topsis-Amit-102003053

For : Assignment(UCS654)
Submitted by: Amit Kumar
Roll no:102003053 Group:3COE3

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-Amit-102003053

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 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

topsis data.csv "1,1,1,2,2" "+,+,-,-,+" out.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

Metadata

Release files for Topsis-Amit-102003053 1.0.0

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Source distribution (sdist)

Source distribution for Topsis-Amit-102003053 1.0.0
File	Size	Uploaded	Provenance
Topsis-Amit-102003053-1.0.0.tar.gz	3.7 kB	Nov 30, 2023	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for Topsis-Amit-102003053 1.0.0
File	Interpreter	ABI	Platform	Reset
Topsis_Amit_102003053-1.0.0-py3-none-any.whl 4.1 kB Nov 30, 2023 Without provenance	Python 3	none	any	Details

Total release size: 7.8 kB

Release files / Topsis-Amit-102003053-1.0.0.tar.gz

Download URL	Topsis-Amit-102003053-1.0.0.tar.gz
Size	3.7 kB
Tags	Source
SHA-256 checksum How to use checksums	`d0553bf64b5bc4abb94ba2172c3f4aa2f0c04430602fbe4881835debb2b010d3`
BLAKE2b-256 checksum How to use checksums	`4e4a0cee4d92e4454504dd5ce0fa7219ff784244b2f43df7cc3055dbf6fb0cdf`
Upload date	Nov 30, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.10.2`

Release files / Topsis_Amit_102003053-1.0.0-py3-none-any.whl

Download URL	Topsis_Amit_102003053-1.0.0-py3-none-any.whl
Size	4.1 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e70e5c319d8191e0d02d033906ef664d86c936bc974dd523a65d96f184381bab`
BLAKE2b-256 checksum How to use checksums	`63ffb321d7315a21e2505b289299069e1523823fcc151c3e60631b10045935ab`
Upload date	Nov 30, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.10.2`

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Nov 30, 2023 2 release files No provenance

Topsis-Amit-102003053 1.0.0