[英]Enumerate row by group in python
I have a dataset with rounds in a game, names, and scores:我有一个包含游戏回合、名称和分数的数据集:
import pandas as pd
data = [[1,'tom', 10], [1,'nick', 15], [2,'juli', 14], [2,'peter', 20], [3,'juli', 3], [3,'peter', 13]]
have = pd.DataFrame(data, columns = ['Round', 'Name', 'Score'])
have.sort_values(by=['Round','Score'])
How do I get to a dataset with Round, WinnerName, LooserName, WinnerScore and LooserScore?如何获取包含 Round、WinnerName、LooserName、WinnerScore 和 LooserScore 的数据集?
I started trying to enumerate, but keep messing up the syntax我开始尝试枚举,但不断弄乱语法
This is my approach:这是我的方法:
min_max = have.groupby('Round').Score.agg(['idxmax','idxmin']).stack()
ret = pd.DataFrame(have.loc[min_max,["Name", "Score"]].values,
index=min_max.index,
columns=['Name','Score']).unstack()
# rename
ret.rename(mapper={"idxmax":'winner', 'idxmin':'looser'}, level=1, axis=1)
Output: Output:
Name Score
winner looser winner looser
Round
1 nick tom 15 10
2 peter juli 20 14
3 peter juli 13 3
this seems to me definitely the best approach在我看来,这绝对是最好的方法
since in each match only two teams compete,you can order using pandas.DataFrame.sort_values and use由于在每场比赛中只有两支球队参加比赛,您可以使用pandas.DataFrame.sort_values 排序并使用
Groupby.Series.first and Groupby.Series.last : Groupby.Series.first和Groupby.Series.last :
result=( have.sort_values('Score',ascending=False)
.groupby('Round')
.agg({'Name':{'Winner':'first','Looser':'last'},
'Score':{'WinnerScore':'first','LooserScore':'last'}}) )
print(result)
Name Score
Winner Looser WinnerScore LooserScore
Round
1 nick tom 15 10
2 peter juli 20 14
3 peter juli 13 3
You can use sort
+ cumcount
to label the outcomes based on score, then it's a pivot
.您可以使用
sort
+ cumcount
来 label 基于分数的结果,那么它就是pivot
。
data = [[1,'tom', 10], [1,'nick', 15], [2,'juli', 14],
[2,'peter', 20], [3,'juli', 3], [3,'peter', 13]]
have = pd.DataFrame(data, columns = ['Round', 'Name', 'Score'])
have = have.sort_values('Score')
have['outcome'] = have.groupby('Round').cumcount().map({0: 'Loser', 1: 'Winner'})
res = have.pivot(index='Round', columns='outcome', values=['Score', 'Name'])
Name Score
outcome Loser Winner Loser Winner
Round
1 tom nick 10 15
2 juli peter 14 20
3 juli peter 3 13
If you don't want the MultiIndex:如果您不想要 MultiIndex:
res.columns = [''.join(x[::-1]) for x in res.columns]
res = res.reset_index()
Round LoserScore WinnerScore LoserName WinnerName
0 1 10 15 tom nick
1 2 14 20 juli peter
2 3 3 13 juli peter
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