# TOPSIS Package
This package implements the `TOPSIS` technique for Multi-Criteria Decision Making Problems.
## Installation
You can install the package using `pip`. First,run:
```
pip install Topsis-Mohit-102397005
```
## Usage
After installing the package, you can use it from the command line.
## Command Line Usage
To use the TOPSIS package from the command line, run the following command:
```
python -m Topsis-Mohit-102397005 inputFileName weights impacts resultFileName
```
### Example
Suppose you have an input file `data.csv` with the following content:
```
Model,Price,Quality,Service:
M1,25000,7,8
M2,30000,8,6
M3,27500,9,7
M4,28000,6,9
```
You can run the following command:
```
python -m Topsis-Mohit-102397005 data.csv "0.25,0.25,0.5" "-,+,+" result.csv
```
This is the `result.csv` file created after running the command:
```
Model,Price,Quality,Service,TOPSIS Score,Rank
M1,25000,7,8,0.5345,2
M2,30000,8,6,0.3083,4
M3,27500,9,7,0.6912,1
M4,28000,6,9,0.4657,3
```
## Function Usage
You can also use the TOPSIS package by calling the function directly in your Python code.
### Example
```
from Topsis-Mohit-102397005 import run_topsis
inputFileName = 'data.csv'
weights = '0.25,0.25,0.5'
impacts = '-,+,+'
resultFileName = 'result.csv'
run_topsis(inputFileName, weights, impacts, resultFileName)
```
This will produce the same output as the command line example, saving the results to `result.csv`.
## Parameters
- `inputFileName`: The name of the input CSV file containing the data.
- `weights`: A string of weights separated by commas (e.g., "1,1,1").
- `impacts`: A string of impacts separated by commas, where each impact is either + or - (e.g., "+,+,-").
- `resultFileName`: The name of the output CSV file where the results will be saved.
## About
- `Author`: Mohit Bansal
- `Github`: https://github.com/Mohit-Bansal-31/Topsis-Mohit-102397005
- `Contact`: mohitbansal0031@gmail.com
- `Date`: 20-Jan-2025
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"description": "# TOPSIS Package\r\n\r\nThis package implements the `TOPSIS` technique for Multi-Criteria Decision Making Problems.\r\n\r\n## Installation\r\n\r\nYou can install the package using `pip`. First,run:\r\n```\r\npip install Topsis-Mohit-102397005\r\n```\r\n\r\n## Usage\r\nAfter installing the package, you can use it from the command line.\r\n\r\n## Command Line Usage\r\nTo use the TOPSIS package from the command line, run the following command:\r\n```\r\npython -m Topsis-Mohit-102397005 inputFileName weights impacts resultFileName\r\n```\r\n\r\n### Example\r\nSuppose you have an input file `data.csv` with the following content:\r\n```\r\nModel,Price,Quality,Service:\r\nM1,25000,7,8\r\nM2,30000,8,6\r\nM3,27500,9,7\r\nM4,28000,6,9\r\n```\r\n\r\nYou can run the following command:\r\n```\r\npython -m Topsis-Mohit-102397005 data.csv \"0.25,0.25,0.5\" \"-,+,+\" result.csv\r\n```\r\nThis is the `result.csv` file created after running the command:\r\n```\r\nModel,Price,Quality,Service,TOPSIS Score,Rank\r\nM1,25000,7,8,0.5345,2\r\nM2,30000,8,6,0.3083,4\r\nM3,27500,9,7,0.6912,1\r\nM4,28000,6,9,0.4657,3\r\n```\r\n\r\n## Function Usage\r\nYou can also use the TOPSIS package by calling the function directly in your Python code.\r\n\r\n### Example\r\n```\r\nfrom Topsis-Mohit-102397005 import run_topsis\r\n\r\ninputFileName = 'data.csv'\r\nweights = '0.25,0.25,0.5'\r\nimpacts = '-,+,+'\r\nresultFileName = 'result.csv'\r\n\r\nrun_topsis(inputFileName, weights, impacts, resultFileName)\r\n```\r\n\r\nThis will produce the same output as the command line example, saving the results to `result.csv`.\r\n\r\n## Parameters\r\n\r\n- `inputFileName`: The name of the input CSV file containing the data.\r\n- `weights`: A string of weights separated by commas (e.g., \"1,1,1\").\r\n- `impacts`: A string of impacts separated by commas, where each impact is either + or - (e.g., \"+,+,-\").\r\n- `resultFileName`: The name of the output CSV file where the results will be saved.\r\n\r\n\r\n## About\r\n- `Author`: Mohit Bansal\r\n- `Github`: https://github.com/Mohit-Bansal-31/Topsis-Mohit-102397005\r\n- `Contact`: mohitbansal0031@gmail.com\r\n- `Date`: 20-Jan-2025\r\n\r\n\r\n",
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