Topsis-Shubham-102067011 0.0.4

TOPSIS for MCDM(Multiple Criteria Decision Making)

Library used to calculate topsis score

TOPSIS is used for multiple Criteria Decision Making (MCDM)

TOPSIS is based on the fundamental premise that the best solution has the shortest distance from the positive-ideal solution, and the longest distance from the negative-ideal one. Alternatives are ranked with the use of an overall index calculated based on the distances from the ideal solutions.

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normalize function takes a dataframe as argument .

It normalizes columns 2nd to the last column of the dataframe.

All the values from the 2nd column to the last column should be numeric.

Outputs a dataframe.

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weightAssignment takes a dataframe(output of normalize function) and a numeric list as inputs.

weightAssignment function assigns weights to different columns .

Outputs a dataframe.

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ideal function takes a dataframe(output of weightAssignment function) and a list of string having elements either ‘+’ or ‘-‘.

Used to calculate max and minimum value of each column.

Outputs a pair of numeric lists.

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euclideanDist function takes a dataframe(output of weightAssignment function) and 2 numeric lists(output of ideal function).

Calculates the euclidean distance of each row of dataframe with the 2 numeric lists.

Outputs a pair of numeric lists.

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performance_score takes 2 numeric lists (output of euclideanDist function) as inputs.

Calculates topsis score of each row.

Outputs a numeric list.

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TOPSIS_result takes a dataframe(output of weightAssignment function or Orignal dataframe) and a numeric list(output of performance_score function) as inputs.

assigns a rank to the list.

The ranks and the list are appended to the dataframe.

Outputs a dataframe.

Change Log

0.0.1 (21/01/2023)

• First Release