semvec/pypi-packages huggingface dataset:
102203201-simrat 1.0.0
It gives the topsis analysis of your csv file with score and rankings.
License: MIT

# TOPSIS-Package Simrat(102203201)

Overview
TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making (MCDM) technique. This Python package helps you evaluate alternatives based on multiple criteria by calculating the TOPSIS score and ranking them accordingly.

With this package, you can:

1. Input your dataset in CSV format.
2. Specify weights for each criterion.
3. Define whether each criterion is beneficial (+) or non-beneficial (-).
4. Obtain a ranked CSV file as output with TOPSIS scores.

# Installation

Install the package using
` pip install 102203201-simrat`

# Input Parameters

1. Input CSV File: Path to your dataset in CSV format.
   The dataset must have at least three columns:
   The first column should contain the names of the alternatives.
   The subsequent columns should contain numeric values for criteria.
2. Weights: Comma-separated numeric values representing the weight of each criterion.
3. Impacts: Comma-separated values (+ or -) indicating whether each criterion is beneficial (+) or non-beneficial (-).
4. Output CSV File Name: Desired file name for the output CSV containing TOPSIS scores and rankings.

## License

Copyright (c) 2024 Simrat Kaur

This package is licensed under the MIT License.
Topsis-Harsh-102203215 1.4.9
A Python package for TOPSIS ranking with CLI support for CSV/Excel files
License: MIT
Requires Python: >=3.6
Keywords: topsis, multi-criteria decision making, python, pypi, csv, xlsx, cli

# Topsis-Harsh-102203215

**Topsis-Harsh-102203215** is a Python package for performing the **TOPSIS** (Technique for Order of Preference by Similarity to Ideal Solution) ranking method on decision matrices. This package allows you to rank alternatives based on multiple criteria, with support for both CLI and programmatic usage. It also provides CLI functionality for processing CSV and Excel files.

## Installation

You can install the package from PyPI using pip:

```bash
pip install Topsis-Harsh-102203215
```

# Usage
CLI Usage
After installation, you can use the package directly from the command line. The general syntax for the CLI is:

topsis <input_file> <weights> <impacts> <output_file>

input_file: The path to a CSV file containing the decision matrix (alternatives x criteria).

weights: A comma-separated list of weights corresponding to each criterion (e.g., 1,1,1,1).

impacts: A comma-separated list of impacts for each criterion, where + indicates a benefit and - indicates a cost (e.g., +,+, -, +).

output_file: The path where the output will be saved.


Example:
```bash
topsis input.csv "1,1,1,1" "+,+,-,+" output.csv
```


# Call the topsis function
rankings, scores = topsis(data, weights, impacts)

# Print the rankings and scores
print("Rankings:", rankings)
print("Scores:", scores)


# Features

TOPSIS: Perform multi-criteria decision-making using the TOPSIS method.

CLI: Command-line interface to process decision matrices in CSV files and output rankings.

Supports CSV Files: Easily read and write decision matrices in CSV format.

# Requirements

Python 3.6 or higher
numpy >= 1.21.0
pandas >= 1.3.0

# License

This project is licensed under the MIT License - see the LICENSE file for details.

# Author

Harsh Lakyan
Email: harshlakyan@gmail.com
GitHub: https://github.com/harshlakyan51