A Python package for implementing the TOPSIS method
Project description
Topsis-Nitin_Goyal-102203614
This Python library delivers a robust implementation of the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) algorithm, designed for solving multi-criteria decision-making problems.
Key Features Standardizes decision matrices for consistency. Incorporates weights to reflect the relative importance of criteria. Computes TOPSIS scores and ranks alternatives effectively. Installation You can install this package using pip:
bash Copy Edit pip install Topsis-YourName-102203614 How to Use Execute the TOPSIS method by providing:
A CSV file containing the decision matrix. A set of weights for the criteria. Positive (+) or negative (-) impacts for each criterion. Example Command: bash Copy Edit python script.py input_data.csv "1,2,3" "+,-,+,-" output_result.csv License This library is distributed under the MIT License. For more details, refer to the license.txt file included in the repository.
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_nitin_goyal_102203614-0.1.0.tar.gz.
File metadata
- Download URL: topsis_nitin_goyal_102203614-0.1.0.tar.gz
- Upload date:
- Size: 4.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ed5ea65660e45db729626e17743ee058b8453272d9bd557491c4960bdfc5ca33
|
|
| MD5 |
437cd73daac82d712aada1926c01cbd9
|
|
| BLAKE2b-256 |
db5e0e2469b7d295685fa8583829677d14e7d8799f6db69d80c720fbc64d3972
|
File details
Details for the file Topsis_Nitin_Goyal_102203614-0.1.0-py3-none-any.whl.
File metadata
- Download URL: Topsis_Nitin_Goyal_102203614-0.1.0-py3-none-any.whl
- Upload date:
- Size: 4.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d9b6757530462e73a1e4d73d813aa34da0abcceb9fcf39d74f8d552a205b932b
|
|
| MD5 |
1511015e0e36a98256a41eb2baa0fd84
|
|
| BLAKE2b-256 |
9d23267d60b8826840937e347a8213afb3c15af8dc8251abb8a39ae6d99f70a6
|