Metadata-Version: 2.2
Name: topsis-teena-102217049
Version: 1.0.2
Summary: A Python package to calculate TOPSIS rankings
Home-page: https://github.com/yourusername/topsis-package
Author: Teena Sapra
Author-email: teena.sapra13@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: pandas
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Topsis-Package

**Topsis-Package** is a Python library for implementing the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method for multi-criteria decision analysis. It simplifies ranking and decision-making based on criteria weights and performance data.

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## Installation

Install the package directly from PyPI:

```bash
pip install topsis-teena-102217049
```

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## Usage

### Input

Prepare a CSV file with the following structure:

- The first row contains column headers (criteria names).
- The first column contains the names of alternatives (e.g., products or options).
- The remaining columns are numeric values representing the performance scores for each criterion.

### Example Input CSV (data.csv):

```csv
Alternative, Criterion 1, Criterion 2, Criterion 3, Criterion 4
Option A, 250, 16, 12, 5
Option B, 200, 22, 8, 6
Option C, 300, 18, 15, 4
Option D, 275, 20, 14, 7
```

### Running the Package

To execute, you will need:

- Path to the input CSV file.
- A comma-separated string of weights (e.g., `"0.4,0.3,0.2,0.1"`).
- A comma-separated string of impacts (e.g., `"+,+,-,-"`).

### Example Code:

```bash
topsis input.csv "0.4,0.3,0.2,0.1" "+,+,-,-" result.csv
```

### Input parameters

- input_file = "data.csv"
- weights = "0.4,0.3,0.2,0.1"
- impacts = "+,+,-,-"

### Output

The package will create a new CSV file with an additional column, **"Topsis Score"**, and the final **"Rank"** for each alternative.

**Example Output:**

```csv
Alternative, Criterion 1, Criterion 2, Criterion 3, Criterion 4, Topsis Score, Rank
Option A, 250, 16, 12, 5, 0.78, 2
Option B, 200, 22, 8, 6, 0.56, 4
Option C, 300, 18, 15, 4, 0.84, 1
Option D, 275, 20, 14, 7, 0.64, 3
```

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## Features

- **Simple Input Format**: Provide your data in CSV format.
- **Customizable Weights and Impacts**: Define criteria importance and type (beneficial or non-beneficial).
- **Automated Output**: Generates scores and ranks for all alternatives.

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## Requirements

This package requires Python 3.7 or higher. Install any missing dependencies using `pip`.

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## Author

Developed by **Teena Sapra**.

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