某些列行的平均值

Question

更新：原问题 此处: 我需要从H2H比赛中获得总进球数的平均值。

Home   Away   Home_goals Away_goals 
------------------------------------
Team 1 Team 2 2          1          
Team 3 Team 4 3          5
Team 2 Team 1 5          3
Team 4 Team 3 1          5

输出。

Home   Away   Home_goals Away_goals Mean
------------------------------------------------------
Team 1 Team 2 2          1          5.5 ((2+1+5+3)/2) 
Team 3 Team 4 3          5          7 ((3+5+1+5)/2)
Team 2 Team 1 5          3          5.5 ((2+1+5+3)/2) 
Team 4 Team 3 1          5          7 ((3+5+1+5)/2)

下面的代码工作正常，但我遇到了另一个问题。如果我有n场球队1和球队2之间的比赛，我想根据n-1场比赛计算平均数（不包括最后一场）。我可以修改下面的代码吗？

a = np.sort(df[["Home", "Away"]], axis=1)
df['Mean'] = (pd.DataFrame(a, index=df.index)
                .assign(sum = df[['Home_goals','Away_goals']].sum(axis=1))
                .groupby([0,1])['sum']
                .transform('mean'))

谢谢你

Answer 1

你可以添加 iloc 到lambda函数 GroupBy.transform:

a = np.sort(df[["Home", "Away"]], axis=1)
df['Mean'] = (pd.DataFrame(a, index=df.index)
                .assign(sum = df[['Home_goals','Away_goals']].sum(axis=1))
                .groupby([0,1])['sum']
                .transform(lambda x: x.iloc[:-1].mean()))

Answer 2

下面对每一个两队组合产生一个平均值，同时放弃最后一场比赛。

我添加了几场比赛来证明这一点。

Home   Away   Home_goals Away_goals 
Team-1 Team-2 2          1          
Team-3 Team-4 3          5
Team-2 Team-1 5          3
Team-4 Team-3 1          5
Team-2 Team-1 10        10
Team-4 Team-3 10        10

代码：

a = np.sort(df[["Home", "Away"]], axis=1)
df = pd.concat([df, pd.DataFrame(a, columns=["team1", "team2"])], axis="columns")
df["sum"] = df[["Home_goals", "Away_goals"]].sum(axis="columns")

drop_last = df.groupby(["team1", "team2"]).apply(lambda x: x.iloc[:-1]).drop(["team1", "team2"], axis="columns").reset_index()
drop_last["mean"] = drop_last.groupby(["team1", "team2"])["sum"].transform("mean")
drop_last = drop_last[["team1", "team2", "mean"]]
drop_last = drop_last.drop_duplicates()

res = pd.merge(df, drop_last, on = ["team1", "team2"])
print(res)

结果：

     Home    Away  Home_goals  Away_goals   team1   team2  sum  mean
0  Team-1  Team-2           2           1  Team-1  Team-2    3   5.5
1  Team-2  Team-1           5           3  Team-1  Team-2    8   5.5
2  Team-2  Team-1          10          10  Team-1  Team-2   20   5.5
3  Team-3  Team-4           3           5  Team-3  Team-4    8   7.0
4  Team-4  Team-3           1           5  Team-3  Team-4    6   7.0
5  Team-4  Team-3          10          10  Team-3  Team-4   20   7.0