Pandas series (58) - Multiple indexes

Multi-level index

Multi-level index (also known as hierarchical index) is an important function of pandas, you can have more than two, and two indexes on Series, DataFrame object.
In essence, a single stage Index object corresponding to the index, the index corresponding to the multi-stage MultiIndex object.

A multi-level index Series object

• Create a multi-level index Series object

import pandas as pd
import numpy as np

se1=pd.Series(np.random.randn(4),index=[list("aabb"),[1,2,1,2]])
se1
Out[6]: 
a  1    0.357171
   2    0.084055
b  1   -0.678752
   2    0.132007
dtype: float64

• Select a subset

se1 [ 'a']
Out[7]: 
1    0.357171
2    0.084055
dtype: float64
se1 [ 'a': 'b']
Out[8]: 
a  1    0.357171
   2    0.084055
b  1   -0.678752
   2    0.132007
dtype: float64　

• Select the inner layer

se1 [:, 1]
Out[9]: 
a    0.357171
b   -0.678752
dtype: float64
se1 [:, 2]
Out[10]: 
a    0.084055
b    0.132007
dtype: float64

Second, and more object-level index DataFrame

• create

df1=pd.DataFrame(np.arange(12).reshape(4,3),index=[list("AABB"),[1,2,1,2]],columns=[list("XXY"),[10,11,10]])
df1
Out[11]: 
     XY
    10  11  10
A 1  0   1   2
  2  3   4   5
B 1  6   7   8
  2  9  10  11

• Fu name

df1.columns.names=['XY','sum']
df1.index.names=['AB','num']
df1
Out[12]: 
XY      X       Y
sum    10  11  10
Surely AB           
A  1    0   1   2
   2    3   4   5
B  1    6   7   8
   2    9  10  11

• Re-create the object as an index MultiIndex

df1.index=pd.MultiIndex.from_arrays([list("AABB"),[3,4,3,4]],names=["AB","num"])
df1
Out[13]: 
XY      X       Y
sum    10  11  10
Surely AB           
A  3    0   1   2
   4    3   4   5
B  3    6   7   8
   4    9  10  11

• Can be interchanged index levels

Dfalkswplevel ( 'now', 'num')
Out[14]: 
XY      X       Y
sum    10  11  10
Surely AB           
3   A   0   1   2
4   A   3   4   5
3   B   6   7   8
4   B   9  10  11