Calculate Topsis score and save it in a csv file
Project description
#Project description ##TOPSIS What is TOPSIS? Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) came in the 1980s as a multi-criteria-based decision-making (MCDM) method. TOPSIS chooses the alternative of shortest the Euclidean distance from the ideal solution and greatest distance from the negative ideal solution.
##How to Install this Package? pip install Topsis-Eshita-102003522
##How to Run this Package? topsis
Eg. topsis /Users/Eshita/Desktop/102003522-data.csv "1,1,1,1,1" "+,+,-,+,+" /Users/Eshita/Desktop/result.csv
##Constraints Applied Number of parameters should be correct i.e. 5. Print error message if input file doesn't exist. The impacts and weights should be comma separated. Impacts should only have +ve or -ve symbols. Number of columns in the input csv file should be more or equal to 3. The 2nd to last columns should be in numeric data type. Number of weights, impacts and columns should be equal. Input File Fund Name P1 P2 P3 P4 P5 M1 0.75 0.56 6.3 51.1 14.68 M2 0.82 0.67 4.2 41.2 11.72 M3 0.89 0.79 6.5 40.2 12.1 M4 0.92 0.85 5.8 49.7 14.32 M6 0.72 0.52 5.3 61.1 16.91 M7 0.69 0.48 3.6 57.9 15.67 M8 0.92 0.85 5.7 31.2 9.67 Output File Fund Name P1 P2 P3 P4 P5 TOPSIS Score Rank M1 0.32 0.29 0.39 0.36 0.37 0.3655 8 M2 0.35 0.34 0.26 0.29 0.29 0.55 2 M3 0.38 0.41 0.41 0.28 0.30 0.48 5 M4 0.39 0.44 0.36 0.35 0.36 0.57 1 M5 0.33 0.30 0.41 0.39 0.39 0.39 7 M6 0.31 0.27 0.33 0.43 0.42 0.44 6 M7 0.29 0.25 0.22 0.41 0.39 0.50 4 M8 0.39 0.44 0.36 0.22 0.24 0.53 3 License MIT
##Written By Name : Eshita Arora Roll No. : 102003522
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