>> pip install Topsis-Parv-101916073
>> 101916073.csv "1,1,1,1" "+,+,-,+" 101916073-output.csv
Fund Name,P1,P2,P3,P4,P5 M1,0.94,0.88,4.3,38.4,11.13 M2,0.91,0.83,3.8,41.2,11.69 M3,0.9,0.81,4.2,55.1,15.25 M4,0.95,0.9,6.8,41.7,12.59 M5,0.87,0.76,3.2,45.6,12.61 M6,0.74,0.55,3.8,42.7,11.95 M7,0.9,0.81,4.2,45.8,12.93 M8,0.95,0.9,5.8,66.6,18.56
Weights (weights) is not already normalised will be normalised later in the code.
Information of benefit positive(+) or negative(-) impact criteria should be provided in impacts.
Fund Name,P1,P2,P3,P4,P5,Topsis Score,Rank M1,0.3703773853298929,0.7662610281769211,0.9814214453951509,1.1328853878160308,1.4539015109686293,0.5710689895607338,6 M2,0.3585568304789389,0.7227234697577778,0.8673026726747846,1.2154916140109497,1.5270537882500697,0.6004095869971899,2 M3,0.3546166455286209,0.7053084463901206,0.9585976908510776,1.62557252262144,1.9920932652535126,0.5719171749702168,5 M4,0.3743175702802109,0.7836760515445784,1.5520153089969826,1.230242725831471,1.6446199481666703,0.4290754887375844,8 M5,0.3427960906776668,0.6617708879709773,0.7303601454103449,1.3453013980315365,1.6472325294981502,0.6376691772167611,1 M6,0.2915736863235327,0.4789131426105757,0.8673026726747846,1.2597449494725135,1.5610173455593097,0.5854706385131984,4 M7,0.3546166455286209,0.7053084463901206,0.9585976908510776,1.351201842759745,1.6890338308018307,0.5863020877858557,3 M8,0.3743175702802109,0.7836760515445784,1.32377776355625,1.9648480944934281,2.424475475613455,0.4451087354476525,7
The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**