问题描述
我有一个数据框如下:
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'])
我想做的是为下一阶段的锦标赛创建另一个日期框架.在下一阶段，我们将为每个模型(ELO 和 xG)提供 3 个匹配项.我想按 模型 分组.这些比赛按型号分组，第 1 场比赛和第 1 场比赛的获胜者、第 3 场比赛的获胜者对第 4 场比赛的获胜者等将进行(即 U 对 B、C 对 X、Y 对 F).那么谁能告诉我如何提取这些团队?
What I want to do is to create another date frame for next stage of tournament. In next stage , we will have 3 matches for each Model (ELO and xG).I would like to groupby Model. These matches are groupped by Model, winner from match number 1 and match number 1,winner from Match number 3 vs match number 4 etc. will play (i.e. U vs B,C vs X, Y vs F). Then Can anyone advise me how to extract those teams?
我预期的新数据框如下:
my expected new dataframe will be as follow:
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
推荐答案
您可以使用 GroupBy.cumcount 用于每组计数:
You can use GroupBy.cumcount for count per groups:
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
这篇关于使用 groupby 和 loc 设置新的数据框的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！