Question

嗨，我有一个数据框，如下所示：

df = pd.DataFrame()
df['Team1']   = ['A','B','C','D','E','F','A','B','C','D','E','F']
df['Score1']  = [1,2,3,1,2,4,1,2,3,1,2,4]
df['Team2']   = ['U','V','W','X','Y','Z','U','V','W','X','Y','Z']
df['Score2']  = [2,1,2,2,3,3,2,1,2,2,3,3]
df['Match']   = df['Team1']  + ' Vs '+ df['Team2']
df['Match_no']= [1,2,3,4,5,6,1,2,3,4,5,6]
df['model']  = ['ELO','ELO','ELO','ELO','ELO','ELO','xG','xG','xG','xG','xG','xG']
winner = df.Score1>df.Score2
df['winner']  = np.where(winner,df['Team1'],df['Team2'])

我要做的是为下一阶段的比赛创建另一个日期框架。在下一阶段，每个型号（ELO和xG）将有3个匹配项。我想按型号进行分组。这些比赛按照模型进行分组，第1场比赛和第1场比赛的获胜者，第3场比赛与第4场比赛的获胜者等等。（例如，U vs B，C vs X，Y vs F ）。然后有人可以建议我如何选拔那些队伍吗？

我期望的新数据框如下：

df1 =pd.DataFrame()
df1['Team1']   = ['U','C','Y','U','C','Y']
df1['Team2']   = ['B','X','F','B','X','F']

df1['Match']   = df1['Team1']  + ' Vs '+ df1['Team2']
df1['Match_no']= [1,2,3,1,2,3]
df1['model']  = ['ELO','ELO','ELO','xG','xG','xG']

我该如何设置？谢谢，

Zep

Answer 1

尽管我很难理解“奇数比赛获胜者，甚至是比赛号码获胜者”的意思，我会尽力给你一个答案。

如果这意味着比赛1和2配对的获胜者，然后是3和4等，那么您可以做一些简单的事情

df1['Team1'] = df.loc[::2, 'winner']
df1['Team2'] = df.loc[1::2, 'winner']

假设您的数据按显示顺序排序。您可以通过

df[df['model'] == 'ELO'].sort_values('Match_no')

等如果我说对了，pandas-groupby似乎并不需要。

Answer 2

您可以使用GroupBy.cumcount进行每组计数：

df1 = pd.DataFrame()
df1['Team1'] = df.loc[::2, 'winner'].values
df1['Team2'] = df.loc[1::2, 'winner'].values
df1['Match'] = df1['Team1']  + ' Vs '+ df1['Team2']
model = df.loc[::2, 'model'].values
df1['Match_no'] = df1.groupby(model).cumcount() + 1
df1['model'] = model
print (df1)
  Team1 Team2   Match  Match_no model
0     U     B  U Vs B         1   ELO
1     C     X  C Vs X         2   ELO
2     Y     F  Y Vs F         3   ELO
3     U     B  U Vs B         1    xG
4     C     X  C Vs X         2    xG
5     Y     F  Y Vs F         3    xG

使用groupby和loc设置新的数据框

2 个答案: