Project description
TOPSIS-ANALYSIS
By: Sarvagy Jain
What is TOPSIS?
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.
### Installation
```bash
pip install Topsis-SARVAGY-102003553
```
### Usage
Arguments Required:
(Assumne we have 3 attributes in dataset.)
You have to required one .csv file. (102003553-data.csv)
Pass weights to each attribute. (e.g.: [1,1,1])
Pass impacts to each attribute. (e.g.: [+,-,+])
Pass the name of the file with you want to put on .csv file. (102003553-result.csv)
Enter csv filename followed by .csv extentsion, then enter the weights string with values separated by commas, followed by the impacts string with comma separated signs (+,-) and name of file followed by -.csv- extension in which the user wants the output file
## Example
#### sample.csv
```bash
Fund Name P1 P2 P3 P4 P5 Topsis Score Rank
M1 0.72 0.52 4.4 66.6 18.06 0.607089574 2
M2 0.71 0.5 4.9 48.4 13.63 0.424434575 6
M3 0.82 0.67 6.1 58.2 16.45 0.811786381 1
M4 0.67 0.45 4.3 48.9 13.58 0.346716421 8
M5 0.75 0.56 3.3 60.2 16.2 0.486990207 4
M6 0.76 0.58 6.4 33.3 10.26 0.446021381 5
M7 0.85 0.72 3.2 61.9 16.67 0.568789224 3
M8 0.73 0.53 5.8 36.5 10.89 0.397353478 7
```
### INPUT
```python
topsis 102003553-data.csv 1,1,1,1,1 +,+,-,+,+ 102003553-result.csv
```
### OUTPUT
```bash
Fund Name P1 P2 P3 P4 P5 Topsis Score Rank
M1 0.72 0.52 4.4 66.6 18.06 0.607089574 2
M2 0.71 0.5 4.9 48.4 13.63 0.424434575 6
M3 0.82 0.67 6.1 58.2 16.45 0.811786381 1
M4 0.67 0.45 4.3 48.9 13.58 0.346716421 8
M5 0.75 0.56 3.3 60.2 16.2 0.486990207 4
M6 0.76 0.58 6.4 33.3 10.26 0.446021381 5
M7 0.85 0.72 3.2 61.9 16.67 0.568789224 3
M8 0.73 0.53 5.8 36.5 10.89 0.397353478 7
```
Change Log
==========
0.0.1 (12/11/2020)
------------------
- First Release
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"description": "Project description\r\nTOPSIS-ANALYSIS\r\nBy: Sarvagy Jain\r\n\r\nWhat is TOPSIS?\r\nTechnique for Order Preference by Similarity to Ideal Solution (TOPSIS) originated in the 1980s as a multi-criteria decision making method. TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.\r\n\r\n### Installation\r\n```bash\r\npip install Topsis-SARVAGY-102003553 \r\n```\r\n\r\n\r\n### Usage\r\n\r\nArguments Required:\r\n(Assumne we have 3 attributes in dataset.)\r\n\r\nYou have to required one .csv file. (102003553-data.csv)\r\nPass weights to each attribute. (e.g.: [1,1,1])\r\nPass impacts to each attribute. (e.g.: [+,-,+])\r\nPass the name of the file with you want to put on .csv file. (102003553-result.csv)\r\n\r\n\r\nEnter csv filename followed by .csv extentsion, then enter the weights string with values separated by commas, followed by the impacts string with comma separated signs (+,-) and name of file followed by -.csv- extension in which the user wants the output file\r\n\r\n## Example\r\n#### sample.csv\r\n```bash\r\nFund Name\tP1\tP2\tP3\tP4\tP5\tTopsis Score\tRank\r\nM1\t0.72\t0.52\t4.4\t66.6\t18.06\t0.607089574\t2\r\nM2\t0.71\t0.5\t4.9\t48.4\t13.63\t0.424434575\t6\r\nM3\t0.82\t0.67\t6.1\t58.2\t16.45\t0.811786381\t1\r\nM4\t0.67\t0.45\t4.3\t48.9\t13.58\t0.346716421\t8\r\nM5\t0.75\t0.56\t3.3\t60.2\t16.2\t0.486990207\t4\r\nM6\t0.76\t0.58\t6.4\t33.3\t10.26\t0.446021381\t5\r\nM7\t0.85\t0.72\t3.2\t61.9\t16.67\t0.568789224\t3\r\nM8\t0.73\t0.53\t5.8\t36.5\t10.89\t0.397353478\t7\r\n```\r\n\r\n### INPUT\r\n```python\r\ntopsis 102003553-data.csv 1,1,1,1,1 +,+,-,+,+ 102003553-result.csv\r\n```\r\n\r\n### OUTPUT\r\n\r\n```bash\r\nFund Name\tP1\tP2\tP3\tP4\tP5\tTopsis Score\tRank\r\nM1\t0.72\t0.52\t4.4\t66.6\t18.06\t0.607089574\t2\r\nM2\t0.71\t0.5 \t4.9\t48.4\t13.63\t0.424434575\t6\r\nM3\t0.82\t0.67\t6.1\t58.2\t16.45\t0.811786381\t1\r\nM4\t0.67\t0.45\t4.3\t48.9\t13.58\t0.346716421\t8\r\nM5\t0.75\t0.56\t3.3\t60.2\t16.2\t0.486990207\t4\r\nM6\t0.76\t0.58\t6.4\t33.3\t10.26\t0.446021381\t5\r\nM7\t0.85\t0.72\t3.2\t61.9\t16.67\t0.568789224\t3\r\nM8\t0.73\t0.53\t5.8\t36.5\t10.89\t0.397353478\t7\r\n```\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nChange Log\r\n==========\r\n\r\n0.0.1 (12/11/2020)\r\n------------------\r\n- First Release\r\n",
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