A Python package for performing TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to rank the entries in a dataset.
Project description
Topsis PyPi Package (CLI)
Submitted By: Ananya Gaur 102216114
A Python package that can be used as a CLI tool for implementing Topsis method used for multi-criteria decision analysis by calculating performance and ranks. Topsis stands for 'Technique for Order of Preference by Similarity to Ideal Solution'.
Checkout the package 👉: https://pypi.org/project/topsis-ANANYA-102216114/
CLI scripts takes
csv/excelfiles as input!
Installation of the package
$ pip install topsis-ANANYA-102216114
Command Line Usage
$ topsis-ANANYA-102216114 input_filePath weights impacts output_filePath
Arguments
| Arguments | Description |
|---|---|
| input_file | Input CSV file path |
| weights | Comma separated string of numbers(weights) |
| impacts | Comma separated string of '+' or '-' |
| output_file | Output CSV file path |
Output
Creates a csv output_file, that contains the original data alongwith additional cloumns of Topsis Performance score and rank.
Example:
$topsis-ANANYA-102216114 data.csv "1,0.25,1,1" "+,-,+,-,+" output.csv
Sample dataset
1. Structure of the Decision Matrix
- The file must contain three or more columns.
- The first column contains the names or identifiers of the Model/Product alternatives (e.g., M1, M2, etc.).
- The remaining columns (from the second column onwards) contain Numeric or Nominal values representing the criteria for evaluation.
Example Decision Matrix:
| Model | Cost | Quality | Durability | Ease of use |
|---|---|---|---|---|
| M1 | 250 | 8.5 | 7.0 | 9.0 |
| M2 | 300 | 7.8 | 8.5 | 8.0 |
| M3 | 200 | 9.0 | 6.5 | 7.5 |
| M4 | 290 | 8.2 | 7.8 | 8.8 |
| M5 | 350 | 9.5 | 8.2 | 7.9 |
License
Licensed under the MIT License.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file topsis-ANANYA-102216114-1.0.3.tar.gz.
File metadata
- Download URL: topsis-ANANYA-102216114-1.0.3.tar.gz
- Upload date:
- Size: 3.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.11.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8128cc2ea474b541d543424e475723ea108f1c6df551002103d9e8bf9959f0a9
|
|
| MD5 |
8482a052f6ca0f2bcde758056a163f54
|
|
| BLAKE2b-256 |
3793a90949b02b1c1e1a84fefa0ce2383d95fa5da11005d95405673acf8633b9
|
File details
Details for the file topsis_ANANYA_102216114-1.0.3-py3-none-any.whl.
File metadata
- Download URL: topsis_ANANYA_102216114-1.0.3-py3-none-any.whl
- Upload date:
- Size: 4.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.11.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
629211c9b2c9370ec620d78554849ec0d0482239d65cbb5852da6e0ee3b310f4
|
|
| MD5 |
791673b810cbac3d8b969aadb539cc7f
|
|
| BLAKE2b-256 |
651552b70502a3dfe379c0f6abb5b41b2fd3c1c6ddb49384f2cfd69fa86b1eac
|