问pandas评分系统；平局显示为"3-4“

EN

            Name  100 m  Long jump  Shot put  High jump  400 m  110 m hurdles  Discus throw  Pole vault  Javelin throw           1500 m  Total Score  Ranking
1    Edan Daniele  12.61       5.00      9.22       1.50  60.39          16.43         21.60         2.6          35.81  00:05:25.720000       3847.0        1
2      Coos Kwesi  13.75       4.84     10.12       1.50  68.44          19.18         30.85         2.8          33.88  00:06:22.750000       3127.0        2
3  Severi Eileifr  13.43       4.35      8.64       1.50  66.06          19.05         24.89         2.2          33.48  00:06:51.010000       2953.0        3
4     Lehi Poghos  13.04       4.53      7.79       1.55  64.72          18.74         24.20         2.4          28.20  00:06:50.760000       2940.0        4

import numpy as np
from os import sep
import pandas as pd
df  =   pd.read_csv("Decathlon.csv",sep=";",header=None)
df.reset_index(drop=False)
df.index = np.arange(1, len(df) + 1)
df.columns  =   ["Name","100 m","Long jump","Shot put","High jump","400 m","110 m hurdles","Discus throw","Pole vault","Javelin throw","1500 m"]

df['100m score'] =  round(25.4347*((18-df["100 m"])**1.81))
df["Long jump score"]   =   round(0.14354*(((df["Long jump"]-220)*-1)**1.4))
df["shot put score"]    =  round( 51.39*((df["Shot put"]-1.5)**1.05))
df["high jump score"]   =  round( 0.8465*(((df["High jump"]-75)*-1)**1.42))
df["400m score"]    =  round( 1.53775*((82-df["400 m"])**1.81))
df['110m hurdles score']  =  round( 5.74352*((28.5-df['110 m hurdles'])**1.92))
df['Discus throw score']  =  round( 12.91*((df['Discus throw']-4)**1.1))
df['Pole vault score']  = round(  0.2797*(((df['Pole vault']-100)*-1)*1.35))
df['Javelin throw score'] =  round( 10.14*(((df['Javelin throw']-7)**1.08)))
df['1500 m'] =  pd.to_datetime(df['1500 m'].str.strip(), format='%M.%S.%f')
df['Minute'] = pd.to_datetime(df['1500 m']).dt.minute
df['sekunde'] = pd.to_datetime(df['1500 m']).dt.second
df['milisekunde'] = pd.to_datetime(df['1500 m']).dt.microsecond
df.loc[df['milisekunde']>500000,['sekunde']]   =   df['sekunde']+1
df['Total seconds'] =   (df["Minute"]*60)   +   df["sekunde"]
df['1500 m score']  =   round(0.03768*((480-df["Total seconds"])**1.85))
df["Total Score"]   =   df['100m score']+df["Long jump score"]+df["shot put score"]+df["high jump score"]+df["400m score"]+df['110m hurdles score']+df['Discus throw score']+df['Pole vault score']+df['Javelin throw score']+df['1500 m score']
df["1500 m"]    =   pd.DatetimeIndex(df['1500 m']).time

#clean up
del df['100m score']
del df["Long jump score"] 
del df["shot put score"] 
del df["high jump score"]
del df["400m score"]
del df['110m hurdles score']
del df['Discus throw score']
del df['Pole vault score']
del df['Javelin throw score']
del df['Minute']
del df['sekunde']
del df['milisekunde']
del df["Total seconds"]
del df ["1500 m score"]
df = df.sort_values(['Total Score'], ascending  =   False)
df= df.reset_index(drop =   True)
df.index = np.arange(1, len(df) + 1)
df["Ranking"]   =   df.index
print(df)
df.to_json('Json file')