semvec/pypi-packages huggingface dataset:
Topsis-Taruna-102003464 0.3
This is package for topsis of version 0.3

## Topsis:-MULTIPLE-CRITERIA DECISION MAKING

# TOPSIS

Submitted By: **TARUNA JAIN 102003464**.

Date: **21-JAN-2023**.

Description: **Evaluation of alternatives based on multiple criteria using TOPSIS method.**.

---

## What is TOPSIS?

**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution
TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution,
and greatest distance from the negative-ideal solution.

<br>

## How to install this package:

```
>> pip install Topsis_Taruna_102003464
```

### In Command Prompt

```
>> topsis123 data.csv "1,1,1,1," "+,+,-,+" result.csv
```

## Input file (data.csv)

The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Price or cost, Storage Space, Camera, Looks, and many more.

| Attribute | Price or cost | Storage Space | Camera| Looks |
| -----     | -----------   | ------------- | ---- | -------|
| Mobile 1  |250$           | 16GB          | 12MP | 5      |
| Mobile 2  | 200$          | 16GB          | 8MP  | 3      |
| Mobile 3  | 300$          | 32GB          | 16MP | 4      |
| Mobile 4  |  275$         | 32GB          | 8MP  | 4      |
| Mobile 5  | 225$          | 16GB          | 16MP | 2      |

Weights (`weights`) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in `impacts`.

<br>

## Output file (result.csv)

| Attribute | Price or cost | Storage Space | Camera| Looks | Topsis_score | Rank|
| -----     | -----------   | ------------- | ---- | -------| ------------ | ----|
| Mobile 1  |250$           | 16GB          | 12MP | 5      | 0.4228       | 4   |
| Mobile 2  |200$           | 16GB          | 8MP  | 3      | 0.4635       | 3   |
| Mobile 3  |300$           | 32GB          | 16MP | 4      | 0.5097       | 2   |
| Mobile 4  |275$           | 32GB          | 8MP  | 4      | 0.3772       | 5   |
| Mobile 5  |225$           | 16GB          | 16MP | 2      | 0.6871       | 1   |


<br>
The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**
Petspackage-Ayan-123 0.0.1
It helps the user to classify according to their breeds and types
Requires Python: >=3.7


# Petspackage_Ayan_123

It helps the user to classify according to their breeds and types

## Installing the package

pip Install

## Using the package

```import Petspackage_Ayan_123 as cute```

User has to input all the seven attributes and it returns all the information about the pet.

## Function used

fun(cuddle)
Topsis-Aditya-102003706 0.1.5
Topsis, packaged for ease.
Requires Python: >=3.5

# Topsis-Package

## A simple package to implement TOPSIS .

<br/>


## Installation:

        pip install Topsis-Aditya-102003706

</br>
 
# Command Line Usage


## USAGE:

        TOPSIS <input_data_file> <weight> <impact> <output_file>

_input_data_file_ :  The path of the CSV file that contains the input data. Sample input file is available on [github.](https://github.com/adityaagg7/Topsis-Package)</br></br>

_weight_ : The comma separated weights to be assigned to all the choices. Have to be same size as the data.  
eg:

        "1,1,1,1,1"
</br>
_impact_ :  The comma separated impacts to be assigned to all the choices. Have to be same size as the data.   
eg:  

        "+,-,+,-,+"
</br>

_otuput_file_ :  The path of the CSV file that will contain the result. Sample file is available on [github.](https://github.com/adityaagg7/Topsis-Package)

Example:

        TOPSIS Sample.csv "1,1,1,1,2" "+,-,+,-,+" Result.csv
</br>

# Usage as a Library

## Import:

        from Topsis.TOPSIS import topsis

## Syntax:

        topsis( input_data_file ,weight, impact, output_file )
</br>

## Returns:
A pandas dataframe containg the original data with the columns for Topsis Score appendt and Rank appended.