Pandas 数据透视表百分比计算
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/37148787/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas pivot table Percent Calculations
提问by Dance Party2
Given the following data frame and pivot table:
给定以下数据框和数据透视表：
import pandas as pd
df=pd.DataFrame({'A':['x','y','z','x','y','z'],
'B':['one','one','one','two','two','two'],
'C':[2,18,2,8,2,18]})
df
A B C
0 x one 2
1 y one 18
2 z one 2
3 x two 8
4 y two 2
5 z two 18
table = pd.pivot_table(df, index=['A', 'B'],aggfunc=np.sum)
C
A B
x one 2
two 8
y one 18
two 2
z one 2
two 18
I'd like to add 2 columns to this pivot table; one showing the percent of all values and another for percent within column A like this:
我想在这个数据透视表中添加 2 列；一个显示所有值的百分比，另一个显示 A 列中的百分比，如下所示：
C % of Total % of B
A B
x one 2 4% 10%
two 18 36% 90%
y one 2 4% 20%
two 8 16% 80%
z one 2 4% 10%
two 18 36% 90%
Extra Credit:
额外学分：
I'd like a bottom summary row which has the sum of column C (it's okay if it also has 100% for the next 2 columns, but nothing is needed for those).
我想要一个底部汇总行，它包含 C 列的总和（如果接下来的 2 列也有 100% 也可以，但那些不需要任何内容）。
回答by jezrael
You can use:
您可以使用：
table['% of Total'] = (table.C / table.C.sum() * 100).astype(str) + '%'
table['% of B'] = (table.C / table.groupby(level=0).C.transform(sum) * 100).astype(str) + '%'
print table
C % of Total % of B
A B
x one 2 4.0% 20.0%
two 8 16.0% 80.0%
y one 18 36.0% 90.0%
two 2 4.0% 10.0%
z one 2 4.0% 10.0%
two 18 36.0% 90.0%
But with real data I think casting to intis not recommended, better is use round.
但是对于真实数据，我认为int不推荐强制转换为，更好的是使用round.
Extra Credit:
额外学分：
table['% of Total'] = (table.C / table.C.sum() * 100)
table['% of B'] = (table.C / table.groupby(level=0).C.transform(sum) * 100)
table.loc['total', :] = table.sum().values
print table
C % of Total % of B
A B
x one 2.0 4.0 20.0
two 8.0 16.0 80.0
y one 18.0 36.0 90.0
two 2.0 4.0 10.0
z one 2.0 4.0 10.0
two 18.0 36.0 90.0
total 50.0 100.0 300.0
