No project description provided
Project description
#TOPSIS
Code by: Parteekpal Singh
## What is TOPSIS
TOPSIS stands for ‘The Technique for Order of Preference by Similarity to the Ideal Solution’ is a multi-criteria decision analysis(MCDA) method. It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.
## How to run
#### Before running, make sure you have pandas and numpy installed on your system
Open Terminal and input the following commands
>> pip3 install Topsis-Parteek-101803190 >> python >>>from topsis.topsis import topsis >>>topsis(“input.csv”,”1,2,1,2”,”+,+,-,+”,”output.csv”)
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-parteekpal-101803190-0.3.tar.gz.
File metadata
- Download URL: TOPSIS-parteekpal-101803190-0.3.tar.gz
- Upload date:
- Size: 2.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2c75f3a93c41cec70839624016d4be9517001bbbb9a4584a0625949d68a79a31
|
|
| MD5 |
8708da3a4383788e21c392bdce5d1a34
|
|
| BLAKE2b-256 |
5101807488eef38048427d1c9536bc0e11439cc434471b621edb3cece8f9b985
|
File details
Details for the file TOPSIS_parteekpal_101803190-0.3-py3-none-any.whl.
File metadata
- Download URL: TOPSIS_parteekpal_101803190-0.3-py3-none-any.whl
- Upload date:
- Size: 3.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2725649d14b1b57462785721db096421cc756e44763336258529793e16152391
|
|
| MD5 |
120077e8e9d606d5fbda32d83098af29
|
|
| BLAKE2b-256 |
0bac0e16079442307168c5a3e2f4e9de29029326d91173b052312a7f51c3d0fc
|