Skip to main content

topsis package for decision making

Project description

Topsis

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a decision-making method based on the concept that the best solution is the one closest to the positive-ideal solution and farthest from the negative-ideal one. The alternatives are ranked using an overall index calculated from the distances to the ideal solutions.

Function Parameters

The topsis function takes four arguments:

  1. Data.csv file: The input CSV file containing the data for decision-making.
  2. Weights: A string representing the weights for each criterion, separated by commas. For example, "1,1,1,1,1".
  3. Impacts: A string representing the impacts for each criterion, specified as either '+' or '-'. For example, "+,-,+,-,+".
  4. Result file: The name of the output file that will contain Topsis Score and Rank information.

How to Use

To use the Topsis package, follow these steps:

  1. Open your terminal.

  2. Type the following command to install the Topsis package:

    pip install Topsis-Vanshika-102103484
    
  3. To get started quickly, use the following Python code:

    from topis_pckg.topsis import topsis
    topsis('inputfilename','Weights','Impacts','Outputfilename')
    

    Make sure to replace 'inputfilename', 'Weights', 'Impacts', and 'Outputfilename' with your actual file names and values. Ensure that the weights and impacts are specified in double quotes, as shown in the example.

By following these steps, you can efficiently use the Topsis package to calculate scores and ranks based on your decision-making criteria.

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

Topsis_Vanshika_102103484-0.0.1.tar.gz (3.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

Topsis_Vanshika_102103484-0.0.1-py3-none-any.whl (3.2 kB view details)

Uploaded Python 3

File details

Details for the file Topsis_Vanshika_102103484-0.0.1.tar.gz.

File metadata

File hashes

Hashes for Topsis_Vanshika_102103484-0.0.1.tar.gz
Algorithm Hash digest
SHA256 1a0fd23b133741b96c450abc7873a952a092932ddb342573f22ce9f80dbff58a
MD5 1744c2e290eb98092ede47ceedb1a022
BLAKE2b-256 1673a388628cb19a76b74a3b4b9c5899a595c17ae201275d9225700c498b85da

See more details on using hashes here.

File details

Details for the file Topsis_Vanshika_102103484-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for Topsis_Vanshika_102103484-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2f6d3b557ebab148f472a41d45e08442a2719028b6e29b03679b7483d08c7b43
MD5 68a0f7d4afaaa66d635ea4864352f407
BLAKE2b-256 ab3cc97305bb36a7a1de52dd401e1242b051d0d21fc6c5daf3dfa5344605ba18

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page