Name | 102003037-topsis JSON |
Version |
0.0.1
JSON |
| download |
home_page | |
Summary | Topsis |
upload_time | 2023-01-22 16:34:03 |
maintainer | |
docs_url | None |
author | Himangi Sharma |
requires_python | |
license | |
keywords |
python
topsis
|
VCS |
|
bugtrack_url |
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requirements |
No requirements were recorded.
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# 102003037 TOPSIS PACKAGE HIMANGI SHARMA
Roll Number : 102003037 <br>
Subgroup : 3COE18 <br>
The program takes csv file containing our data to be ranked, weights and impacts in the form of "+" or "-", seperated by commas as inputs and then outputs a resultant csv file with two additional columns of performance score and Ranks.
# What is TOPSIS
TOPSIS, Technique of Order Preference Similarity to the Ideal Solution, is a multi-criteria decision analysis method (MCDA). <br>
It chooses the alternative of shortest the Euclidean distance from the ideal solution and greatest distance from the negative ideal solution. <br>
## Installation
### How to install the TOPSIS package <br>
using pip install:-<br>
``` pip install 102003037-topsis-Himangi ```
## For Calculating the TOPSIS Score
Open terminal and type <br>
``` 102003037 102003037-data.csv "1,1,1,1" "+,+,-,+" 102003037-output.csv ```
The output will then be saved in a newly created CSV file whose name will be provided in the command line by the user.
## Input File [102003037-data.csv]:
Topsis mathematical operations to be performed on the input file which contains a dataset having different fields.
## Weights ["1,1,1,1"]
The weights to assigned to the different parameters in the dataset should be passed in the argument, seperated by commas.
## Impacts ["+,+,-,+"]:
The impacts are passed to consider which parameters have a positive impact on the decision and which one have the negative impact. Only '+' and '-' values should be passed and should be seperated with ',' only.
## Output File [102003037-output.csv]:
This argument is used to pass the path of the result file where we want the rank and performance score to be stored.
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"description": "\n# 102003037 TOPSIS PACKAGE HIMANGI SHARMA\nRoll Number : 102003037 <br>\nSubgroup : 3COE18 <br>\nThe program takes csv file containing our data to be ranked, weights and impacts in the form of \"+\" or \"-\", seperated by commas as inputs and then outputs a resultant csv file with two additional columns of performance score and Ranks.\n\n# What is TOPSIS\nTOPSIS, Technique of Order Preference Similarity to the Ideal Solution, is a multi-criteria decision analysis method (MCDA). <br>\nIt chooses the alternative of shortest the Euclidean distance from the ideal solution and greatest distance from the negative ideal solution. <br>\n\n## Installation\n### How to install the TOPSIS package <br>\nusing pip install:-<br>\n``` pip install 102003037-topsis-Himangi ```\n\n## For Calculating the TOPSIS Score\nOpen terminal and type <br>\n``` 102003037 102003037-data.csv \"1,1,1,1\" \"+,+,-,+\" 102003037-output.csv ```\n\nThe output will then be saved in a newly created CSV file whose name will be provided in the command line by the user.\n\n## Input File [102003037-data.csv]:\nTopsis mathematical operations to be performed on the input file which contains a dataset having different fields.\n\n## Weights [\"1,1,1,1\"]\nThe weights to assigned to the different parameters in the dataset should be passed in the argument, seperated by commas.\n\n## Impacts [\"+,+,-,+\"]:\nThe impacts are passed to consider which parameters have a positive impact on the decision and which one have the negative impact. Only '+' and '-' values should be passed and should be seperated with ',' only.\n\n## Output File [102003037-output.csv]:\nThis argument is used to pass the path of the result file where we want the rank and performance score to be stored.\n\n\n\n\n",
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