Command line implementation of TOPSIS method
Project description
Topsis-Sarang-102353017
This package implements the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method as a Python command-line tool. It is developed as part of an academic assignment.
Installation
pip install Topsis-Sarang-102353017
Usage
topsis <input_file> <output_file>
Example
topsis data.csv "1,1,1,1,1" "+,+,+,-,-" result.csv
Input File Requirements
- Input file must be in CSV format
- The first column should contain alternative names
- Remaining columns must contain numeric values
- Minimum three columns are required
Output
The output CSV file contains the TOPSIS score and rank for each alternative.
Dependencies
pandas
numpy
Author
Sarang Priani
Roll Number: 102353017
PyPI Link
https://pypi.org/project/Topsis-Sarang-102353017/
License
This project is created for academic purposes.
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_sarang_102353017-0.0.4.tar.gz.
File metadata
- Download URL: topsis_sarang_102353017-0.0.4.tar.gz
- Upload date:
- Size: 2.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
def076485ffb6b2ec3836ec4b0825478aaee056a543a779c5bd5470f2bf2f1bb
|
|
| MD5 |
777e8eb010bd582f0d5e2e38a07bc27f
|
|
| BLAKE2b-256 |
a59780695fea026e88e7cfd59ec2c7b7a4b95c53660788c9cdb4cc0b97a192a6
|
File details
Details for the file topsis_sarang_102353017-0.0.4-py3-none-any.whl.
File metadata
- Download URL: topsis_sarang_102353017-0.0.4-py3-none-any.whl
- Upload date:
- Size: 3.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e31525e641a0bfedd142ae498db46b8ef63f67073032e6fb697a30b3fba1f7a5
|
|
| MD5 |
efb92b4be9982cbb1b8e64c423addb4c
|
|
| BLAKE2b-256 |
f89e8675d944eadcda370d392fb78a3659c7c347c2ba1f4903b4dc6f59fc4819
|