我想合并df1和df2。我合并df1和df2时遇到的当前问题是,它会产生重复的“ Fluc”列。数据帧必须合并on='Horse'
。
数据框代码:
cols1 = ['Race', 'Horse', 'Fluc 1', 'Fluc 2','Bookmaker', 'Odds']
df1 = pd.DataFrame(data=data, columns=cols1)
cols2 = ['Race', 'Horse', 'Fluc 1', 'Fluc 2', 'Bookmaker', 'AvgOdds']
df2 = pd.DataFrame(data=data, columns=cols2)
df3 = df2.groupby(by='Horse', sort=False).mean()
df3 = df3.reset_index()
df4 = round(df3,2)
dfmerge = pd.merge(df1,df4,on='Horse',how='inner')
df1的输出:
Race Horse Fluc 1 Fluc 2 Bookmaker Odds
0 Ipswich R1 Battle Through 4.2 4.22 BetEasy 4.20
1 Ipswich R1 Battle Through 4.2 4.22 Neds 4.20
2 Ipswich R1 Battle Through 4.2 4.22 Sportsbet 4.20
3 Ipswich R1 Battle Through 4.2 4.22 SportsBetting 4.45
4 Ipswich R1 Battle Through 4.2 4.22 Bet365 4.20
df4的输出:
Race Horse Fluc 1 Fluc 2 Bookmaker AvgOdds
0 Ipswich R1 Battle Through 4.2 4.22 BetEasy 4.20
1 Ipswich R1 Battle Through 4.2 4.22 Neds 4.20
2 Ipswich R1 Battle Through 4.2 4.22 Sportsbet 4.20
3 Ipswich R1 Battle Through 4.2 4.22 SportsBetting 4.45
4 Ipswich R1 Battle Through 4.2 4.22 Bet365 4.20
dfmerge的输出:
Race Horse Fluc 1_x Fluc 2_x Bookmaker Odds Fluc 1_y Fluc 2_y AvgOdds
0 Ipswich R1 Battle Through 8.34 8.38 Neds 8.5 8.34 8.38 8.65
1 Ipswich R1 Battle Through 8.34 8.38 Sportsbet 8.0 8.34 8.38 8.65
2 Ipswich R1 Battle Through 8.34 8.38 SportsBetting 9.1 8.34 8.38 8.65
3 Ipswich R1 Battle Through 8.34 8.38 Bet365 9.0 8.34 8.38 8.65
4 Ipswich R1 Simply Fly 1.89 1.87 Neds 1.8 1.89 1.87 1.84
所需的dfmerge输出:
Race Horse Fluc 1 Fluc 2 Bookmaker Odds AvgOdds
0 Ipswich R1 Battle Through 4.2 4.22 BetEasy 4.20 4.2
1 Ipswich R1 Battle Through 4.2 4.22 Neds 4.20 4.2
2 Ipswich R1 Battle Through 4.2 4.22 Sportsbet 4.20 4.2
3 Ipswich R1 Battle Through 4.2 4.22 SportsBetting 4.45 4.2
4 Ipswich R1 Battle Through 4.2 4.22 Bet365 4.20 4.2
答案 0 :(得分:0)
尝试一下
dfmerge = pd.merge(df1, df4, on=['Race', 'Horse', 'Fluc 1', 'Fluc 2', 'Bookmaker'], how='inner')
print(dfmerge)
输出:
Race Horse Fluc 1 Fluc 2 Bookmaker Odds AvgOdds
0 Ipswich R1 Battle Through 4.2 4.22 BetEasy 4.20 4.20
1 Ipswich R1 Battle Through 4.2 4.22 Neds 4.20 4.20
2 Ipswich R1 Battle Through 4.2 4.22 Sportsbet 4.20 4.20
3 Ipswich R1 Battle Through 4.2 4.22 SportsBetting 4.45 4.45
4 Ipswich R1 Battle Through 4.2 4.22 Bet365 4.20 4.20