给定以下数据透视表：
df=pd.DataFrame({'A':['a','a','a','a','a','b','b','b','b'],
'B':['x','y','z','x','y','z','x','y','z'],
'C':['a','b','a','b','a','b','a','b','a'],
'D':[7,5,3,4,1,6,5,3,1]})
table = pd.pivot_table(df, index=['A', 'B','C'],aggfunc='sum')
table
D
A B C
a x a 7
b 4
y a 1
b 5
z a 3
b x a 5
y b 3
z a 1
b 6
I'd like to access each value of 'C' (or level 2) as a list to use for plotting.
I'd like to do the same for 'A' and 'B' (levels 0 and 1) in such a way that it preserves spacing so that I can use those lists as well. I'm ultimately trying to use them to create something like this via plotting:
这是这个问题的根源。 https://stackoverflow.com/questions/37173170/pandas-pivot-table-to-bar-chart-preserving-hierarchy/37173918#37173918
提前致谢！
您可以使用get_level_values http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Index.get_level_values.html#pandas.Index.get_level_values从多索引中获取特定级别的索引值：
In [127]:
table.index.get_level_values('C')
Out[127]:
Index(['a', 'b', 'a', 'b', 'a', 'a', 'b', 'a', 'b'], dtype='object', name='C')
In [128]:
table.index.get_level_values('B')
Out[128]:
Index(['x', 'x', 'y', 'y', 'z', 'x', 'y', 'z', 'z'], dtype='object', name='B')
In [129]:
table.index.get_level_values('A')
Out[129]:
Index(['a', 'a', 'a', 'a', 'a', 'b', 'b', 'b', 'b'], dtype='object', name='A')
get_level_values接受级别或标签的 int 参数
请注意，对于较高级别，这些值会重复以与最低级别的索引长度相对应，出于显示目的，您看不到此内容