pandas 数据透视表嵌套排序 [英] Pandas pivot table Nested Sorting

问题描述

给出此数据框和数据透视表:

Given this data frame and pivot table:

import pandas as pd
df=pd.DataFrame({'A':['x','y','z','x','y','z'],
                 'B':['one','one','one','two','two','two'],
                 'C':[7,5,3,4,1,6]})
df


    A   B       C
0   x   one     7
1   y   one     5
2   z   one     3
3   x   two     4
4   y   two     1
5   z   two     6

table = pd.pivot_table(df, index=['A', 'B'],aggfunc=np.sum)

table
A  B  
x  one    7
   two    4
y  one    5
   two    1
z  one    3
   two    6
Name: C, dtype: int64

我想对数据透视表进行排序，以使"A"的顺序为z，x，y，而"B"的顺序基于数据帧列"C"中的降序排序值.

I want to sort the pivot table such that the order of 'A' is z, x, y and the order of 'B' is based on the descendingly-sorted values from data frame column 'C'.

喜欢这个:

A  B  
z  two    6
   one    3
x  one    7
   two    4
y  one    5
   two    1

    Name: C, dtype: int64

提前谢谢！

推荐答案

我不认为有一种简单的方法可以实现您的目标.以下解决方案首先根据列C的值对表以降序排序.然后，它会根据您想要的顺序将每个切片连接起来.

I don't believe there is an easy way to accomplish your objective. The following solution first sorts your table is descending order based on the values of column C. It then concatenates each slice based on your desired order.

order = ['z', 'x', 'y']
table = table.reset_index().sort_values('C', ascending=False)
>>> pd.concat([table.loc[table.A == val, :].set_index(['A', 'B']) for val in order])
       C
A B     
z two  6
  one  3
x one  7
  two  4
y one  5
  two  1

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