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Sequentially Spent Score: Difference between revisions

m
(Add python code for clarity of implementation)
Line 22:
 
<source lang="python">
import pandas as pd
import numpy as np
 
#Normalize score matrix
S_wrk = pd.DataFrame(S.values/K, columns=S_inS.columns)
 
#Find number of voters
Line 51 ⟶ 54:
S_wrk = pd.DataFrame(mins, columns = S_wrk.columns)
</source>
 
 
 
==Variants==
765

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