#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 <inputFileName> <weights> <impacts> <resultFileName>
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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"description": "#Project description\r\n##TOPSIS\r\nWhat is TOPSIS?\r\nTechnique 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.\r\n\r\n##How to Install this Package?\r\npip install Topsis-Eshita-102003522\r\n\r\n##How to Run this Package?\r\ntopsis <inputFileName> <weights> <impacts> <resultFileName>\r\n\r\nEg. topsis /Users/Eshita/Desktop/102003522-data.csv \"1,1,1,1,1\" \"+,+,-,+,+\" /Users/Eshita/Desktop/result.csv\r\n\r\n##Constraints Applied\r\nNumber of parameters should be correct i.e. 5.\r\nPrint error message if input file doesn't exist.\r\nThe impacts and weights should be comma separated.\r\nImpacts should only have +ve or -ve symbols.\r\nNumber of columns in the input csv file should be more or equal to 3.\r\nThe 2nd to last columns should be in numeric data type.\r\nNumber of weights, impacts and columns should be equal.\r\nInput File\r\nFund Name\tP1\tP2\tP3\tP4\tP5\r\nM1\t0.75\t0.56\t6.3\t51.1\t14.68\r\nM2\t0.82\t0.67\t4.2\t41.2\t11.72\r\nM3\t0.89\t0.79\t6.5\t40.2\t12.1\r\nM4\t0.92\t0.85\t5.8\t49.7\t14.32\r\nM6\t0.72\t0.52\t5.3\t61.1\t16.91\r\nM7\t0.69\t0.48\t3.6\t57.9\t15.67\r\nM8\t0.92\t0.85\t5.7\t31.2\t9.67\r\nOutput File\r\nFund Name\tP1\tP2\tP3\tP4\tP5\tTOPSIS Score\tRank\r\nM1\t0.32\t0.29\t0.39\t0.36\t0.37\t0.3655\t8\r\nM2\t0.35\t0.34\t0.26\t0.29\t0.29\t0.55\t2\r\nM3\t0.38\t0.41\t0.41\t0.28\t0.30\t0.48\t5\r\nM4\t0.39\t0.44\t0.36\t0.35\t0.36\t0.57\t1\r\nM5\t0.33\t0.30\t0.41\t0.39\t0.39\t0.39\t7\r\nM6\t0.31\t0.27\t0.33\t0.43\t0.42\t0.44\t6\r\nM7\t0.29\t0.25\t0.22\t0.41\t0.39\t0.50\t4\r\nM8\t0.39\t0.44\t0.36\t0.22\t0.24\t0.53\t3\r\nLicense\r\nMIT\r\n\r\n##Written By\r\nName : Eshita Arora\r\nRoll No. : 102003522\r\n",
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