我试图实现与分类汇总表所示这里,但 要么该代码不适用于最新的 Pandas 版本 (0.18.1),要么示例错误用于多列而不是一列。我这里的代码导致下表
2014 2015 2016
project__name person__username activity__name issue__subject
Influenster employee1 Development 161.0 122.0 104.0
Fix bug 22.0 0.0 0.0
Refactor view 0.0 7.0 0.0
Quality assurance 172.0 158.0 161.0
employee2 Development 119.0 137.0 155.0
Quality assurance 193.0 186.0 205.0
employee3 Development Refactor view 0.0 0.0 1.0
Profit tools employee1 Development 177.0 136.0 216.0
Quality assurance 162.0 122.0 182.0
employee2 Development 154.0 168.0 124.0
Quality assurance 130.0 183.0 192.0
Fix bug 22.0 0.0 0.0
All 1312.0 1219.0 1340.0
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我想要的输出是这样的:
2014 2015 2016
project__name person__username activity__name issue__subject
Influenster employee1 Development 161.0 122.0 104.0
Fix bug 22.0 0.0 0.0
Refactor view 0.0 7.0 0.0
Total xxx xxx xxx
Quality assurance 172.0 158.0 161.0
Total xxx xxx xxx
Total xxx xxx xxx
employee2 Development 119.0 137.0 155.0
Total xxx xxx xxx
Quality assurance 193.0 186.0 205.0
Total xxx xxx xxx
Total xxx xxx xxx
employee3 Development Refactor view 0.0 0.0 1.0
Total xxx xxx xxx
Total xxx xxx xxx
Total xxx xxx xxx
Profit tools employee1 Development 177.0 136.0 216.0
Total xxx xxx xxx
Quality assurance 162.0 122.0 182.0
Total xxx xxx xxx
Total xxx xxx xxx
employee2 Development 154.0 168.0 124.0
Total xxx xxx xxx
Quality assurance 130.0 183.0 192.0
Fix bug 22.0 0.0 0.0
Total xxx xxx xxx
Total xxx xxx xxx
Total xxx xxx xxx
All 1312.0 1219.0 1340.0
Run Code Online (Sandbox Code Playgroud)
任何有关如何实现这一目标的帮助表示赞赏。
groupby和applydef append_tot(df):
if hasattr(df, 'name') and df.name is not None:
xs = df.xs(df.name)
else:
xs = df
gb = xs.groupby(level=0)
n = xs.index.nlevels
name = tuple('Total' if i == 0 else '' for i in range(n))
tot = gb.sum().sum().rename(name).to_frame().T
if n > 1:
sm = gb.apply(append_tot3)
else:
sm = gb.sum()
return pd.concat([sm, tot])
fields = ['project__name', 'person__username',
'activity__name', 'issue__subject']
append_tot(df.set_index(fields))
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