TOPSIS Implementation
Project description
Topsis Python Package
Made By
Prarthana Samal (Roll Number 102383015)
Description
The Topsis Python Package is a Python library that provides an implementation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. TOPSIS is a multi-criteria decision-making method used to determine the best alternative among a set of alternatives based on their performance on multiple criteria.
Installation
You can install this package using pip (if published to PyPI) or clone the repository directly:
pip install topsis-prarthana
Usage
Use the following command to perform TOPSIS analysis on a dataset:
topsis.py data.csv "1,0,1,0,1" "+,-,+,-,+" output.csv
Arguments:
data.csv: Path to the input CSV file containing the dataset."1,0,1,0,1": Weights for each criterion separated by commas."+,-,+,-,+": Impacts for each criterion (either+for maximizing or-for minimizing).
Input
Output
Project details
Release history Release notifications | RSS feed
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_prarthana_102383015-1.0.0.tar.gz.
File metadata
- Download URL: topsis_prarthana_102383015-1.0.0.tar.gz
- Upload date:
- Size: 2.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f1607c5b4abdc31a81d3d3ade72c8397e3e7ef6a47fe8b2e9bf43c35cfd3c9c6
|
|
| MD5 |
feb77cd08049c3382571e7bc9b77ecbe
|
|
| BLAKE2b-256 |
a433798ae70251761743adef31cf1ec72b34fbf3b519b839485ca14cd3fbe783
|
File details
Details for the file Topsis_Prarthana_102383015-1.0.0-py3-none-any.whl.
File metadata
- Download URL: Topsis_Prarthana_102383015-1.0.0-py3-none-any.whl
- Upload date:
- Size: 2.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1530ba12284f967d3b27844e3398ea1838d717e8783b96f961db2ffb269e78ec
|
|
| MD5 |
f36001c3a4245e03d75578ebc60dfcde
|
|
| BLAKE2b-256 |
463429f4207cdf97ac14c993265d9fec448005af3c51b3f496136570a5c171ed
|