semvec/pypi-packages huggingface dataset:
Topsis-Preet-102203748 1
A Python package for implementing TOPSIS.
Requires Python: >=3.6

# Topsis-Preet-102203748

Topsis-Preet is a Python Package implementing [Topsis]()  method used for multi-criteria decision analysis. Topsis stands for 'Technique for Order of Preference by Similarity to Ideal Solution'.

TopsisPreet intends to make the process of TOPSIS simple in python. Key features of the package are -

* Easy to use
* Numpy based
* Ideal for Students

And off course, PyTopsis code is Open Source.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Topsis-Preet.

```bash
pip install topsis-preet-102203748
```
## Usage ##
```bash
$ python [package name] [path of csv as string] [list of weights as string] [list of impaces as string] [output file name as csv]
```
ex: for sample 
```excel
$ python topsis-preet-102203748 102203748-data.csv "1,1,1,1,1" "+,+,+,+,+" 102203748-result.csv
```


## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.
topsis-ineshkumar-102203363 1.0.4
A Python package to perform TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)
Requires Python: >=3.6

# topsis_ineshkumar_102203363

`topsis_ineshkumar_102203363` is a Python package that implements the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for multi-criteria decision analysis.

## Installation

You can install the package using pip:

```bash
pip install topsis_ineshkumar_102203363
```

## Usage

### Input File Format

The input CSV file should have the following structure:

- The first column should contain the names of the models.
- The subsequent columns should contain the criteria values for each alternative.
- The first row should contain the headers for each column.

Example:

| model | Criteria 1 | Criteria 2 | Criteria 3 |
|-------------|------------|------------|------------|
| m1        | 260        | 16         | 18         |
| m2        | 208        | 13         | 10          |
| m3        | 310        | 15         | 11         |

### Command-line Usage

After installation, you can use the `topsis` command in the terminal:

```bash
topsis <input_file> <weights> <impacts> <output_file>
```

- `<input_file>`: Path to the input CSV file.
- `<weights>`: Comma-separated string of weights for the criteria.
- `<impacts>`: Comma-separated string of '+' or '-' indicating the desirability of the criteria.
- `<output_file>`: Path to the output CSV file to save the results.

## Example

```bash
topsis data.csv "0.4,0.3,0.23" "+,-,+" results.csv
```

This command will process the `data.csv` file using the specified weights and impacts and output the results to `results.csv`.

## NOTE

- Ensure that the input file has at least three columns: one for alternatives and at least two for criteria.
- All criteria columns should contain numeric values.
- The number of weights and impacts must match the number of criteria.
- Impacts should only be '+' or '-'.

## License

This project is licensed under the MIT License. See the LICENSE file for details.